2025-07-17T06:59:49.7112915Z Current runner version: '2.326.0' 2025-07-17T06:59:49.7119114Z Runner name: 'i-00d4fcac0f1d6282f' 2025-07-17T06:59:49.7120003Z Runner group name: 'default' 2025-07-17T06:59:49.7120966Z Machine name: 'ip-10-0-42-148' 2025-07-17T06:59:49.7123862Z ##[group]GITHUB_TOKEN Permissions 2025-07-17T06:59:49.7126268Z Contents: read 2025-07-17T06:59:49.7126823Z Metadata: read 2025-07-17T06:59:49.7127440Z ##[endgroup] 2025-07-17T06:59:49.7130075Z Secret source: Actions 2025-07-17T06:59:49.7130840Z Prepare workflow directory 2025-07-17T06:59:49.7735787Z Prepare all required actions 2025-07-17T06:59:49.7787981Z Getting action download info 2025-07-17T06:59:50.0280419Z Download action repository 'pytorch/test-infra@main' (SHA:a9ec424ad5e5851e47d68139cfd953b4031778d5) 2025-07-17T06:59:51.7376328Z Download action repository 'pytorch/pytorch@main' (SHA:d76323d41742cbc05ec6857319b267d2c7ea8fd9) 2025-07-17T07:00:05.3264981Z Download action repository 'actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065' (SHA:a26af69be951a213d495a4c3e4e4022e16d87065) 2025-07-17T07:00:05.6224278Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722) 2025-07-17T07:00:05.8177807Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076) 2025-07-17T07:00:05.9729460Z Download action repository 'seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-07-17T07:00:06.2286802Z Getting action download info 2025-07-17T07:00:06.3500785Z Download action repository 'actions/checkout@v4' (SHA:11bd71901bbe5b1630ceea73d27597364c9af683) 2025-07-17T07:00:06.6035797Z Getting action download info 2025-07-17T07:00:06.7071145Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e) 2025-07-17T07:00:06.9013070Z Getting action download info 2025-07-17T07:00:07.0124106Z Download action repository 'nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482' (SHA:3e91a01664abd3c5cd539100d10d33b9c5b68482) 2025-07-17T07:00:07.2004128Z Getting action download info 2025-07-17T07:00:07.3505942Z Uses: pytorch/pytorch/.github/workflows/_linux-test.yml@refs/heads/main (a38f433be2e94a64b095a44ba39879d02d0c2316) 2025-07-17T07:00:07.3510161Z ##[group] Inputs 2025-07-17T07:00:07.3510538Z build-environment: linux-jammy-py3.13-clang12 2025-07-17T07:00:07.3513616Z test-matrix: {"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "linux.2xlarge"}]} 2025-07-17T07:00:07.3517062Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:00:07.3517893Z sync-tag: 2025-07-17T07:00:07.3518688Z timeout-minutes: 600 2025-07-17T07:00:07.3518956Z use-gha: 2025-07-17T07:00:07.3519195Z dashboard-tag: 2025-07-17T07:00:07.3519437Z s3-bucket: gha-artifacts 2025-07-17T07:00:07.3519714Z aws-role-to-assume: 2025-07-17T07:00:07.3520283Z disable-monitor: false 2025-07-17T07:00:07.3520592Z monitor-log-interval: 5 2025-07-17T07:00:07.3521130Z monitor-data-collect-interval: 1 2025-07-17T07:00:07.3521575Z ##[endgroup] 2025-07-17T07:00:07.3522016Z Complete job name: linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T07:00:07.3966327Z A job started hook has been configured by the self-hosted runner administrator 2025-07-17T07:00:07.4070208Z ##[group]Run '/home/ec2-user/runner-scripts/before_job.sh' 2025-07-17T07:00:07.4079650Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:00:07.4080368Z ##[endgroup] 2025-07-17T07:00:08.8662011Z Runner Type: linux.2xlarge 2025-07-17T07:00:08.8662529Z Instance Type: c5.2xlarge 2025-07-17T07:00:08.8662795Z AMI Name: unknown 2025-07-17T07:00:08.8686468Z AMI ID: ami-05ffe3c48a9991133 2025-07-17T07:00:14.3278118Z ##[group]Run pytorch/test-infra/.github/actions/setup-ssh@main 2025-07-17T07:00:14.3278579Z with: 2025-07-17T07:00:14.3279163Z github-secret: *** 2025-07-17T07:00:14.3279914Z instructions: All testing is done inside the container, to start an interactive session run: docker exec -it $(docker container ps --format '{{.ID}}') bash 2025-07-17T07:00:14.3280742Z activate-with-label: false 2025-07-17T07:00:14.3281017Z label: with-ssh 2025-07-17T07:00:14.3281271Z remove-existing-keys: true 2025-07-17T07:00:14.3281565Z fail-silently: true 2025-07-17T07:00:14.3281814Z env: 2025-07-17T07:00:14.3282039Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:00:14.3282317Z ##[endgroup] 2025-07-17T07:00:14.4422639Z Please see https://github.com/pytorch/pytorch/wiki/Debugging-using-with-ssh-for-Github-Actions for more info. 2025-07-17T07:00:14.4424666Z Not on pull request and ciflow reference could not be extracted, skipping adding ssh keys 2025-07-17T07:00:14.4571252Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main 2025-07-17T07:00:14.4571724Z with: 2025-07-17T07:00:14.4571943Z no-sudo: true 2025-07-17T07:00:14.4572191Z submodules: recursive 2025-07-17T07:00:14.4572464Z fetch-depth: 0 2025-07-17T07:00:14.4572685Z env: 2025-07-17T07:00:14.4572904Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:00:14.4573183Z ##[endgroup] 2025-07-17T07:00:14.4659558Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-07-17T07:00:14.4660563Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-07-17T07:00:14.4669046Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:00:14.4669449Z env: 2025-07-17T07:00:14.4669699Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:00:14.4670273Z ##[endgroup] 2025-07-17T07:00:14.4765582Z ##[group]Run # Use all available CPUs for fetching 2025-07-17T07:00:14.4766038Z # Use all available CPUs for fetching 2025-07-17T07:00:14.4766390Z cd "${GITHUB_WORKSPACE}" 2025-07-17T07:00:14.4766740Z git config --global fetch.parallel 0 2025-07-17T07:00:14.4767144Z git config --global submodule.fetchJobs 0 2025-07-17T07:00:14.4767497Z  2025-07-17T07:00:14.4767871Z # Clean workspace. The default checkout action should also do this, but 2025-07-17T07:00:14.4768366Z # do it here as well just in case 2025-07-17T07:00:14.4768699Z if [[ -d .git ]]; then 2025-07-17T07:00:14.4768989Z  if [ -z "${NO_SUDO}" ]; then 2025-07-17T07:00:14.4769311Z  sudo git clean -ffdx 2025-07-17T07:00:14.4769602Z  else 2025-07-17T07:00:14.4769836Z  git clean -ffdx 2025-07-17T07:00:14.4770324Z  fi 2025-07-17T07:00:14.4770551Z fi 2025-07-17T07:00:14.4776206Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:00:14.4776607Z env: 2025-07-17T07:00:14.4776912Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:00:14.4777204Z NO_SUDO: true 2025-07-17T07:00:14.4777428Z ##[endgroup] 2025-07-17T07:00:14.4922960Z ##[group]Run actions/checkout@v4 2025-07-17T07:00:14.4923263Z with: 2025-07-17T07:00:14.4923523Z ref: a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:00:14.4924054Z fetch-depth: 0 2025-07-17T07:00:14.4924294Z submodules: recursive 2025-07-17T07:00:14.4924567Z show-progress: false 2025-07-17T07:00:14.4924844Z repository: pytorch/pytorch 2025-07-17T07:00:14.4925413Z token: *** 2025-07-17T07:00:14.4925637Z ssh-strict: true 2025-07-17T07:00:14.4925880Z ssh-user: git 2025-07-17T07:00:14.4926130Z persist-credentials: true 2025-07-17T07:00:14.4926395Z clean: true 2025-07-17T07:00:14.4926654Z sparse-checkout-cone-mode: true 2025-07-17T07:00:14.4926965Z fetch-tags: false 2025-07-17T07:00:14.4927188Z lfs: false 2025-07-17T07:00:14.4927420Z set-safe-directory: true 2025-07-17T07:00:14.4927695Z env: 2025-07-17T07:00:14.4927899Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:00:14.4928160Z ##[endgroup] 2025-07-17T07:00:14.6023459Z Syncing repository: pytorch/pytorch 2025-07-17T07:00:14.6024844Z ##[group]Getting Git version info 2025-07-17T07:00:14.6025346Z Working directory is '/home/ec2-user/actions-runner/_work/pytorch/pytorch' 2025-07-17T07:00:14.6026069Z [command]/usr/bin/git version 2025-07-17T07:00:14.6026354Z git version 2.47.1 2025-07-17T07:00:14.6034347Z ##[endgroup] 2025-07-17T07:00:14.6043427Z Copying '/home/ec2-user/.gitconfig' to '/home/ec2-user/actions-runner/_work/_temp/3b565ae8-7a1c-481a-b874-5ef1434ca114/.gitconfig' 2025-07-17T07:00:14.6064234Z Temporarily overriding HOME='/home/ec2-user/actions-runner/_work/_temp/3b565ae8-7a1c-481a-b874-5ef1434ca114' before making global git config changes 2025-07-17T07:00:14.6065286Z Adding repository directory to the temporary git global config as a safe directory 2025-07-17T07:00:14.6076184Z [command]/usr/bin/git config --global --add safe.directory /home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-07-17T07:00:14.6107548Z Deleting the contents of '/home/ec2-user/actions-runner/_work/pytorch/pytorch' 2025-07-17T07:00:14.6110114Z ##[group]Initializing the repository 2025-07-17T07:00:14.6113973Z [command]/usr/bin/git init /home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-07-17T07:00:14.6142038Z hint: Using 'master' as the name for the initial branch. This default branch name 2025-07-17T07:00:14.6142674Z hint: is subject to change. To configure the initial branch name to use in all 2025-07-17T07:00:14.6143273Z hint: of your new repositories, which will suppress this warning, call: 2025-07-17T07:00:14.6143708Z hint: 2025-07-17T07:00:14.6144003Z hint: git config --global init.defaultBranch 2025-07-17T07:00:14.6144365Z hint: 2025-07-17T07:00:14.6144709Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and 2025-07-17T07:00:14.6145300Z hint: 'development'. The just-created branch can be renamed via this command: 2025-07-17T07:00:14.6145757Z hint: 2025-07-17T07:00:14.6145986Z hint: git branch -m 2025-07-17T07:00:14.6146528Z Initialized empty Git repository in /home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/ 2025-07-17T07:00:14.6151222Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch 2025-07-17T07:00:14.6174313Z ##[endgroup] 2025-07-17T07:00:14.6174790Z ##[group]Disabling automatic garbage collection 2025-07-17T07:00:14.6177898Z [command]/usr/bin/git config --local gc.auto 0 2025-07-17T07:00:14.6201342Z ##[endgroup] 2025-07-17T07:00:14.6201766Z ##[group]Setting up auth 2025-07-17T07:00:14.6207251Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-07-17T07:00:14.6230946Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'core\.sshCommand' && git config --local --unset-all 'core.sshCommand' || :" 2025-07-17T07:00:14.6501383Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-07-17T07:00:14.6528013Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'http\.https\:\/\/github\.com\/\.extraheader' && git config --local --unset-all 'http.https://github.com/.extraheader' || :" 2025-07-17T07:00:14.6778121Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-07-17T07:00:14.6822085Z ##[endgroup] 2025-07-17T07:00:14.6822884Z ##[group]Fetching the repository 2025-07-17T07:00:14.6830916Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-07-17T07:01:08.6464880Z From https://github.com/pytorch/pytorch 2025-07-17T07:01:08.6465431Z * [new branch] 2.6.0.dev20241004+ -> origin/2.6.0.dev20241004+ 2025-07-17T07:01:08.6466082Z * [new branch] 20250616_dtype_docs -> origin/20250616_dtype_docs 2025-07-17T07:01:08.6466747Z * [new branch] HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes 2025-07-17T07:01:08.6467649Z * [new branch] JackCaoG/dynamo_make_fx_non_core_aten_ops -> origin/JackCaoG/dynamo_make_fx_non_core_aten_ops 2025-07-17T07:01:08.6468891Z * [new branch] PR-AOTInductorNoneBug -> origin/PR-AOTInductorNoneBug 2025-07-17T07:01:08.6471109Z * [new branch] PR-AOTInductorNoneBugFix -> origin/PR-AOTInductorNoneBugFix 2025-07-17T07:01:08.6473125Z * [new branch] PR-FixConfigsIssue -> origin/PR-FixConfigsIssue 2025-07-17T07:01:08.6474239Z * [new branch] PR-NoneBugFix-viable -> origin/PR-NoneBugFix-viable 2025-07-17T07:01:08.6475867Z * [new branch] PR-ResetToZero -> origin/PR-ResetToZero 2025-07-17T07:01:08.6477382Z * [new branch] Update-Flash-Packaging -> origin/Update-Flash-Packaging 2025-07-17T07:01:08.6479338Z * [new branch] ZainRizvi-patch-1 -> origin/ZainRizvi-patch-1 2025-07-17T07:01:08.6480467Z * [new branch] add-missing-args-normalization -> origin/add-missing-args-normalization 2025-07-17T07:01:08.6482008Z * [new branch] addUtilForLinuxBuild -> origin/addUtilForLinuxBuild 2025-07-17T07:01:08.6483455Z * [new branch] add_windows_testing_back -> origin/add_windows_testing_back 2025-07-17T07:01:08.6484898Z * [new branch] addmm-heuristic -> origin/addmm-heuristic 2025-07-17T07:01:08.6486648Z * [new branch] addsimde -> origin/addsimde 2025-07-17T07:01:08.6489043Z * [new branch] adi/test -> origin/adi/test 2025-07-17T07:01:08.6490489Z * [new branch] adi/test_fusions -> origin/adi/test_fusions 2025-07-17T07:01:08.6491988Z * [new branch] adi/test_presve_change -> origin/adi/test_presve_change 2025-07-17T07:01:08.6493390Z * [new branch] adi/testpresve_change -> origin/adi/testpresve_change 2025-07-17T07:01:08.6494965Z * [new branch] adi/update_openblas -> origin/adi/update_openblas 2025-07-17T07:01:08.6497302Z * [new branch] aditew01/test/vec_bf16 -> origin/aditew01/test/vec_bf16 2025-07-17T07:01:08.6498910Z * [new branch] ah-globalfeedback-hook -> origin/ah-globalfeedback-hook 2025-07-17T07:01:08.6500463Z * [new branch] albanD-patch-1 -> origin/albanD-patch-1 2025-07-17T07:01:08.6501888Z * [new branch] alt-disable -> origin/alt-disable 2025-07-17T07:01:08.6503781Z * [new branch] angelayi/155426 -> origin/angelayi/155426 2025-07-17T07:01:08.6505303Z * [new branch] angelayi/157183 -> origin/angelayi/157183 2025-07-17T07:01:08.6506758Z * [new branch] angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files 2025-07-17T07:01:08.6508549Z * [new branch] angelayi/aoti_custom_op -> origin/angelayi/aoti_custom_op 2025-07-17T07:01:08.6509537Z * [new branch] angelayi/benchmark -> origin/angelayi/benchmark 2025-07-17T07:01:08.6511143Z * [new branch] angelayi/benchmark2 -> origin/angelayi/benchmark2 2025-07-17T07:01:08.6512944Z * [new branch] angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization 2025-07-17T07:01:08.6514439Z * [new branch] angelayi/cpp_loader -> origin/angelayi/cpp_loader 2025-07-17T07:01:08.6516266Z * [new branch] angelayi/customop -> origin/angelayi/customop 2025-07-17T07:01:08.6518076Z * [new branch] angelayi/del_lib -> origin/angelayi/del_lib 2025-07-17T07:01:08.6519559Z * [new branch] angelayi/docs -> origin/angelayi/docs 2025-07-17T07:01:08.6521076Z * [new branch] angelayi/docs2 -> origin/angelayi/docs2 2025-07-17T07:01:08.6522668Z * [new branch] angelayi/dynamo_fake_input -> origin/angelayi/dynamo_fake_input 2025-07-17T07:01:08.6524042Z * [new branch] angelayi/errmsg -> origin/angelayi/errmsg 2025-07-17T07:01:08.6525546Z * [new branch] angelayi/fake_device -> origin/angelayi/fake_device 2025-07-17T07:01:08.6527030Z * [new branch] angelayi/int_lift_constants -> origin/angelayi/int_lift_constants 2025-07-17T07:01:08.6528581Z * [new branch] angelayi/logging.bak -> origin/angelayi/logging.bak 2025-07-17T07:01:08.6529927Z * [new branch] angelayi/logging2 -> origin/angelayi/logging2 2025-07-17T07:01:08.6531487Z * [new branch] angelayi/no_so_weight -> origin/angelayi/no_so_weight 2025-07-17T07:01:08.6533047Z * [new branch] angelayi/pytree -> origin/angelayi/pytree 2025-07-17T07:01:08.6534679Z * [new branch] angelayi/scan_layers -> origin/angelayi/scan_layers 2025-07-17T07:01:08.6536117Z * [new branch] angelayi/symint_input -> origin/angelayi/symint_input 2025-07-17T07:01:08.6537592Z * [new branch] angelayi/torch_size -> origin/angelayi/torch_size 2025-07-17T07:01:08.6539037Z * [new branch] angelayi/torchgenooops -> origin/angelayi/torchgenooops 2025-07-17T07:01:08.6540539Z * [new branch] angelayi/update_schema_msg -> origin/angelayi/update_schema_msg 2025-07-17T07:01:08.6541893Z * [new branch] aoti_static_linkage -> origin/aoti_static_linkage 2025-07-17T07:01:08.6543507Z * [new branch] atalman-inductor-perf-cu124 -> origin/atalman-inductor-perf-cu124 2025-07-17T07:01:08.6545033Z * [new branch] atalman-inductor-perf-cu124.1 -> 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* [new tag] ciflow/binaries_wheel/157928 -> ciflow/binaries_wheel/157928 2025-07-17T07:01:09.3590829Z * [new tag] ciflow/binaries_wheel/158408 -> ciflow/binaries_wheel/158408 2025-07-17T07:01:09.3591681Z * [new tag] ciflow/h100-cutlass-backend/156626 -> ciflow/h100-cutlass-backend/156626 2025-07-17T07:01:09.3592476Z * [new tag] ciflow/h100-distributed/144552 -> ciflow/h100-distributed/144552 2025-07-17T07:01:09.3593188Z * [new tag] ciflow/h100-distributed/150312 -> ciflow/h100-distributed/150312 2025-07-17T07:01:09.3593870Z * [new tag] ciflow/h100-distributed/156605 -> ciflow/h100-distributed/156605 2025-07-17T07:01:09.3594657Z * [new tag] ciflow/h100-distributed/156703 -> ciflow/h100-distributed/156703 2025-07-17T07:01:09.3595685Z * [new tag] ciflow/h100-symm-mem/151845 -> ciflow/h100-symm-mem/151845 2025-07-17T07:01:09.3596265Z * [new tag] ciflow/h100-symm-mem/157180 -> ciflow/h100-symm-mem/157180 2025-07-17T07:01:09.3596951Z * [new tag] ciflow/h100-symm-mem/157970 -> ciflow/h100-symm-mem/157970 2025-07-17T07:01:09.3597802Z * [new tag] ciflow/h100-symm-mem/158511 -> ciflow/h100-symm-mem/158511 2025-07-17T07:01:09.3598396Z * [new tag] ciflow/h100-symm-mem/158512 -> ciflow/h100-symm-mem/158512 2025-07-17T07:01:09.3599092Z * [new tag] ciflow/h100-symm-mem/158513 -> ciflow/h100-symm-mem/158513 2025-07-17T07:01:09.3599762Z * [new tag] ciflow/h100-symm-mem/158514 -> ciflow/h100-symm-mem/158514 2025-07-17T07:01:09.3600443Z * [new tag] ciflow/h100-symm-mem/158515 -> ciflow/h100-symm-mem/158515 2025-07-17T07:01:09.3601374Z * [new tag] ciflow/h100-symm-mem/158523 -> ciflow/h100-symm-mem/158523 2025-07-17T07:01:09.3602100Z * [new tag] ciflow/h100/156980 -> ciflow/h100/156980 2025-07-17T07:01:09.3602766Z * [new tag] ciflow/h100/158459 -> ciflow/h100/158459 2025-07-17T07:01:09.3604110Z * [new tag] ciflow/inductor-perf-test-nightly-rocm/151845 -> ciflow/inductor-perf-test-nightly-rocm/151845 2025-07-17T07:01:09.3604876Z * [new tag] ciflow/inductor-perf-test-nightly-rocm/156592 -> ciflow/inductor-perf-test-nightly-rocm/156592 2025-07-17T07:01:09.3605959Z * [new tag] ciflow/inductor-perf-test-nightly/156592 -> ciflow/inductor-perf-test-nightly/156592 2025-07-17T07:01:09.3606558Z * [new tag] ciflow/inductor-rocm/151845 -> ciflow/inductor-rocm/151845 2025-07-17T07:01:09.3607559Z * [new tag] ciflow/inductor-rocm/156192 -> ciflow/inductor-rocm/156192 2025-07-17T07:01:09.3608294Z * [new tag] ciflow/inductor-rocm/157191 -> ciflow/inductor-rocm/157191 2025-07-17T07:01:09.3608974Z * [new tag] ciflow/inductor-rocm/157520 -> ciflow/inductor-rocm/157520 2025-07-17T07:01:09.3609633Z * [new tag] ciflow/inductor-rocm/158074 -> ciflow/inductor-rocm/158074 2025-07-17T07:01:09.3610432Z * [new tag] ciflow/inductor-rocm/158102 -> ciflow/inductor-rocm/158102 2025-07-17T07:01:09.3611730Z * [new tag] ciflow/inductor-rocm/158103 -> ciflow/inductor-rocm/158103 2025-07-17T07:01:09.3612348Z * [new tag] ciflow/inductor-rocm/158459 -> ciflow/inductor-rocm/158459 2025-07-17T07:01:09.3613215Z * [new tag] ciflow/inductor/137400 -> ciflow/inductor/137400 2025-07-17T07:01:09.3613841Z * [new tag] ciflow/inductor/138214 -> ciflow/inductor/138214 2025-07-17T07:01:09.3614547Z * [new tag] ciflow/inductor/139561 -> ciflow/inductor/139561 2025-07-17T07:01:09.3615215Z * [new tag] ciflow/inductor/143712 -> ciflow/inductor/143712 2025-07-17T07:01:09.3615898Z * [new tag] ciflow/inductor/144516 -> ciflow/inductor/144516 2025-07-17T07:01:09.3616566Z * [new tag] ciflow/inductor/144556 -> ciflow/inductor/144556 2025-07-17T07:01:09.3617236Z * [new tag] ciflow/inductor/147470 -> ciflow/inductor/147470 2025-07-17T07:01:09.3617913Z * [new tag] ciflow/inductor/148180 -> ciflow/inductor/148180 2025-07-17T07:01:09.3618575Z * [new tag] ciflow/inductor/148328 -> ciflow/inductor/148328 2025-07-17T07:01:09.3619269Z * [new tag] ciflow/inductor/148484 -> ciflow/inductor/148484 2025-07-17T07:01:09.3619955Z * [new tag] ciflow/inductor/148492 -> ciflow/inductor/148492 2025-07-17T07:01:09.3620966Z * [new tag] ciflow/inductor/148569 -> ciflow/inductor/148569 2025-07-17T07:01:09.3621831Z * [new tag] ciflow/inductor/149003 -> ciflow/inductor/149003 2025-07-17T07:01:09.3622609Z * [new tag] ciflow/inductor/149961 -> ciflow/inductor/149961 2025-07-17T07:01:09.3623338Z * [new tag] ciflow/inductor/150762 -> ciflow/inductor/150762 2025-07-17T07:01:09.3624245Z * [new tag] ciflow/inductor/151777 -> ciflow/inductor/151777 2025-07-17T07:01:09.3624954Z * [new tag] ciflow/inductor/151845 -> ciflow/inductor/151845 2025-07-17T07:01:09.3625664Z * [new tag] ciflow/inductor/152624 -> ciflow/inductor/152624 2025-07-17T07:01:09.3626387Z * [new tag] ciflow/inductor/154149 -> ciflow/inductor/154149 2025-07-17T07:01:09.3627071Z * [new tag] ciflow/inductor/154199 -> ciflow/inductor/154199 2025-07-17T07:01:09.3627781Z * [new tag] ciflow/inductor/154551 -> ciflow/inductor/154551 2025-07-17T07:01:09.3628656Z * [new tag] ciflow/inductor/154694 -> ciflow/inductor/154694 2025-07-17T07:01:09.3629315Z * [new tag] ciflow/inductor/155452 -> ciflow/inductor/155452 2025-07-17T07:01:09.3630036Z * [new tag] ciflow/inductor/155608 -> ciflow/inductor/155608 2025-07-17T07:01:09.3630716Z * [new tag] ciflow/inductor/155877 -> ciflow/inductor/155877 2025-07-17T07:01:09.3631675Z * [new tag] ciflow/inductor/155958 -> ciflow/inductor/155958 2025-07-17T07:01:09.3632315Z * [new tag] ciflow/inductor/156049 -> ciflow/inductor/156049 2025-07-17T07:01:09.3633008Z * [new tag] ciflow/inductor/156118 -> ciflow/inductor/156118 2025-07-17T07:01:09.3633672Z * [new tag] ciflow/inductor/156141 -> ciflow/inductor/156141 2025-07-17T07:01:09.3634359Z * [new tag] ciflow/inductor/156175 -> ciflow/inductor/156175 2025-07-17T07:01:09.3635182Z * [new tag] ciflow/inductor/156192 -> ciflow/inductor/156192 2025-07-17T07:01:09.3636150Z * [new tag] ciflow/inductor/156296 -> ciflow/inductor/156296 2025-07-17T07:01:09.3636938Z * [new tag] ciflow/inductor/156369 -> ciflow/inductor/156369 2025-07-17T07:01:09.3637329Z * [new tag] ciflow/inductor/156370 -> ciflow/inductor/156370 2025-07-17T07:01:09.3638036Z * [new tag] ciflow/inductor/156371 -> ciflow/inductor/156371 2025-07-17T07:01:09.3638761Z * [new tag] ciflow/inductor/156416 -> ciflow/inductor/156416 2025-07-17T07:01:09.3639461Z * [new tag] ciflow/inductor/156460 -> ciflow/inductor/156460 2025-07-17T07:01:09.3640167Z * [new tag] ciflow/inductor/156592 -> ciflow/inductor/156592 2025-07-17T07:01:09.3640861Z * [new tag] ciflow/inductor/156605 -> ciflow/inductor/156605 2025-07-17T07:01:09.3641560Z * [new tag] ciflow/inductor/156626 -> ciflow/inductor/156626 2025-07-17T07:01:09.3642265Z * [new tag] ciflow/inductor/156652 -> ciflow/inductor/156652 2025-07-17T07:01:09.3643015Z * [new tag] ciflow/inductor/156781 -> ciflow/inductor/156781 2025-07-17T07:01:09.3643752Z * [new tag] ciflow/inductor/156851 -> ciflow/inductor/156851 2025-07-17T07:01:09.3644755Z * [new tag] ciflow/inductor/156874 -> ciflow/inductor/156874 2025-07-17T07:01:09.3645432Z * [new tag] ciflow/inductor/156977 -> ciflow/inductor/156977 2025-07-17T07:01:09.3646184Z * [new tag] ciflow/inductor/156980 -> ciflow/inductor/156980 2025-07-17T07:01:09.3646937Z * [new tag] ciflow/inductor/157152 -> ciflow/inductor/157152 2025-07-17T07:01:09.3647633Z * [new tag] ciflow/inductor/157298 -> ciflow/inductor/157298 2025-07-17T07:01:09.3648343Z * [new tag] ciflow/inductor/157520 -> ciflow/inductor/157520 2025-07-17T07:01:09.3649065Z * [new tag] ciflow/inductor/157572 -> ciflow/inductor/157572 2025-07-17T07:01:09.3649753Z * [new tag] ciflow/inductor/157580 -> ciflow/inductor/157580 2025-07-17T07:01:09.3650482Z * [new tag] ciflow/inductor/157594 -> ciflow/inductor/157594 2025-07-17T07:01:09.3651465Z * [new tag] ciflow/inductor/157633 -> ciflow/inductor/157633 2025-07-17T07:01:09.3652122Z * [new tag] ciflow/inductor/157635 -> ciflow/inductor/157635 2025-07-17T07:01:09.3652854Z * [new tag] ciflow/inductor/157685 -> ciflow/inductor/157685 2025-07-17T07:01:09.3653564Z * [new tag] ciflow/inductor/157686 -> ciflow/inductor/157686 2025-07-17T07:01:09.3654288Z * [new tag] ciflow/inductor/157689 -> ciflow/inductor/157689 2025-07-17T07:01:09.3654993Z * [new tag] ciflow/inductor/157699 -> ciflow/inductor/157699 2025-07-17T07:01:09.3656316Z * [new tag] ciflow/inductor/157743 -> ciflow/inductor/157743 2025-07-17T07:01:09.3657262Z * [new tag] ciflow/inductor/157748 -> ciflow/inductor/157748 2025-07-17T07:01:09.3658122Z * [new tag] ciflow/inductor/157804 -> ciflow/inductor/157804 2025-07-17T07:01:09.3658721Z * [new tag] ciflow/inductor/157822 -> ciflow/inductor/157822 2025-07-17T07:01:09.3659553Z * [new tag] ciflow/inductor/157854 -> ciflow/inductor/157854 2025-07-17T07:01:09.3660599Z * [new tag] ciflow/inductor/157887 -> ciflow/inductor/157887 2025-07-17T07:01:09.3661194Z * [new tag] ciflow/inductor/157902 -> ciflow/inductor/157902 2025-07-17T07:01:09.3661891Z * [new tag] ciflow/inductor/157927 -> ciflow/inductor/157927 2025-07-17T07:01:09.3662602Z * [new tag] ciflow/inductor/157944 -> ciflow/inductor/157944 2025-07-17T07:01:09.3663549Z * [new tag] ciflow/inductor/157951 -> ciflow/inductor/157951 2025-07-17T07:01:09.3664572Z * [new tag] ciflow/inductor/157954 -> ciflow/inductor/157954 2025-07-17T07:01:09.3665430Z * [new tag] ciflow/inductor/157967 -> ciflow/inductor/157967 2025-07-17T07:01:09.3666085Z * [new tag] ciflow/inductor/157969 -> ciflow/inductor/157969 2025-07-17T07:01:09.3666798Z * [new tag] ciflow/inductor/157971 -> ciflow/inductor/157971 2025-07-17T07:01:09.3667515Z * [new tag] ciflow/inductor/157979 -> ciflow/inductor/157979 2025-07-17T07:01:09.3668508Z * [new tag] ciflow/inductor/157982 -> ciflow/inductor/157982 2025-07-17T07:01:09.3669206Z * [new tag] ciflow/inductor/157993 -> ciflow/inductor/157993 2025-07-17T07:01:09.3669920Z * [new tag] ciflow/inductor/158004 -> ciflow/inductor/158004 2025-07-17T07:01:09.3670823Z * [new tag] ciflow/inductor/158011 -> ciflow/inductor/158011 2025-07-17T07:01:09.3671548Z * [new tag] ciflow/inductor/158015 -> ciflow/inductor/158015 2025-07-17T07:01:09.3672256Z * [new tag] ciflow/inductor/158046 -> ciflow/inductor/158046 2025-07-17T07:01:09.3673224Z * [new tag] ciflow/inductor/158047 -> ciflow/inductor/158047 2025-07-17T07:01:09.3673852Z * [new tag] ciflow/inductor/158048 -> ciflow/inductor/158048 2025-07-17T07:01:09.3674589Z * [new tag] ciflow/inductor/158049 -> ciflow/inductor/158049 2025-07-17T07:01:09.3675288Z * [new tag] ciflow/inductor/158061 -> ciflow/inductor/158061 2025-07-17T07:01:09.3676034Z * [new tag] ciflow/inductor/158062 -> ciflow/inductor/158062 2025-07-17T07:01:09.3676727Z * [new tag] ciflow/inductor/158072 -> ciflow/inductor/158072 2025-07-17T07:01:09.3677660Z * [new tag] ciflow/inductor/158074 -> ciflow/inductor/158074 2025-07-17T07:01:09.3678228Z * [new tag] ciflow/inductor/158075 -> ciflow/inductor/158075 2025-07-17T07:01:09.3678966Z * [new tag] ciflow/inductor/158084 -> ciflow/inductor/158084 2025-07-17T07:01:09.3679718Z * [new tag] ciflow/inductor/158091 -> ciflow/inductor/158091 2025-07-17T07:01:09.3680552Z * [new tag] ciflow/inductor/158097 -> ciflow/inductor/158097 2025-07-17T07:01:09.3681138Z * [new tag] ciflow/inductor/158098 -> ciflow/inductor/158098 2025-07-17T07:01:09.3681847Z * [new tag] ciflow/inductor/158104 -> ciflow/inductor/158104 2025-07-17T07:01:09.3682633Z * [new tag] ciflow/inductor/158119 -> ciflow/inductor/158119 2025-07-17T07:01:09.3683343Z * [new tag] ciflow/inductor/158156 -> ciflow/inductor/158156 2025-07-17T07:01:09.3684058Z * [new tag] ciflow/inductor/158171 -> ciflow/inductor/158171 2025-07-17T07:01:09.3685176Z * [new tag] ciflow/inductor/158174 -> ciflow/inductor/158174 2025-07-17T07:01:09.3685924Z * [new tag] ciflow/inductor/158188 -> ciflow/inductor/158188 2025-07-17T07:01:09.3686669Z * [new tag] ciflow/inductor/158193 -> ciflow/inductor/158193 2025-07-17T07:01:09.3687480Z * [new tag] ciflow/inductor/158211 -> ciflow/inductor/158211 2025-07-17T07:01:09.3688141Z * [new tag] ciflow/inductor/158223 -> ciflow/inductor/158223 2025-07-17T07:01:09.3688859Z * [new tag] ciflow/inductor/158237 -> ciflow/inductor/158237 2025-07-17T07:01:09.3689562Z * [new tag] ciflow/inductor/158259 -> ciflow/inductor/158259 2025-07-17T07:01:09.3690505Z * [new tag] ciflow/inductor/158284 -> ciflow/inductor/158284 2025-07-17T07:01:09.3691244Z * [new tag] ciflow/inductor/158289 -> ciflow/inductor/158289 2025-07-17T07:01:09.3691966Z * [new tag] ciflow/inductor/158311 -> ciflow/inductor/158311 2025-07-17T07:01:09.3692929Z * [new tag] ciflow/inductor/158312 -> ciflow/inductor/158312 2025-07-17T07:01:09.3693564Z * [new tag] ciflow/inductor/158318 -> ciflow/inductor/158318 2025-07-17T07:01:09.3694299Z * [new tag] ciflow/inductor/158321 -> ciflow/inductor/158321 2025-07-17T07:01:09.3695133Z * [new tag] ciflow/inductor/158338 -> ciflow/inductor/158338 2025-07-17T07:01:09.3695867Z * [new tag] ciflow/inductor/158349 -> ciflow/inductor/158349 2025-07-17T07:01:09.3696530Z * [new tag] ciflow/inductor/158350 -> ciflow/inductor/158350 2025-07-17T07:01:09.3697231Z * [new tag] ciflow/inductor/158351 -> ciflow/inductor/158351 2025-07-17T07:01:09.3697952Z * [new tag] ciflow/inductor/158360 -> ciflow/inductor/158360 2025-07-17T07:01:09.3698655Z * [new tag] ciflow/inductor/158361 -> ciflow/inductor/158361 2025-07-17T07:01:09.3699407Z * [new tag] ciflow/inductor/158363 -> ciflow/inductor/158363 2025-07-17T07:01:09.3700115Z * [new tag] ciflow/inductor/158368 -> ciflow/inductor/158368 2025-07-17T07:01:09.3700868Z * [new tag] ciflow/inductor/158377 -> ciflow/inductor/158377 2025-07-17T07:01:09.3701654Z * [new tag] ciflow/inductor/158379 -> ciflow/inductor/158379 2025-07-17T07:01:09.3702371Z * [new tag] ciflow/inductor/158381 -> ciflow/inductor/158381 2025-07-17T07:01:09.3703090Z * [new tag] ciflow/inductor/158391 -> ciflow/inductor/158391 2025-07-17T07:01:09.3704057Z * [new tag] ciflow/inductor/158394 -> ciflow/inductor/158394 2025-07-17T07:01:09.3704712Z * [new tag] ciflow/inductor/158397 -> ciflow/inductor/158397 2025-07-17T07:01:09.3706091Z * [new tag] ciflow/inductor/158400 -> ciflow/inductor/158400 2025-07-17T07:01:09.3706886Z * [new tag] ciflow/inductor/158404 -> ciflow/inductor/158404 2025-07-17T07:01:09.3707618Z * [new tag] ciflow/inductor/158406 -> ciflow/inductor/158406 2025-07-17T07:01:09.3708298Z * [new tag] ciflow/inductor/158410 -> ciflow/inductor/158410 2025-07-17T07:01:09.3709111Z * [new tag] ciflow/inductor/158418 -> ciflow/inductor/158418 2025-07-17T07:01:09.3709843Z * [new tag] ciflow/inductor/158424 -> ciflow/inductor/158424 2025-07-17T07:01:09.3710662Z * [new tag] ciflow/inductor/158426 -> ciflow/inductor/158426 2025-07-17T07:01:09.3711521Z * [new tag] ciflow/inductor/158427 -> ciflow/inductor/158427 2025-07-17T07:01:09.3712299Z * [new tag] ciflow/inductor/158430 -> ciflow/inductor/158430 2025-07-17T07:01:09.3713109Z * [new tag] ciflow/inductor/158435 -> ciflow/inductor/158435 2025-07-17T07:01:09.3713956Z * [new tag] ciflow/inductor/158442 -> ciflow/inductor/158442 2025-07-17T07:01:09.3714655Z * [new tag] ciflow/inductor/158449 -> ciflow/inductor/158449 2025-07-17T07:01:09.3715374Z * [new tag] ciflow/inductor/158456 -> ciflow/inductor/158456 2025-07-17T07:01:09.3716083Z * [new tag] ciflow/inductor/158458 -> ciflow/inductor/158458 2025-07-17T07:01:09.3716819Z * [new tag] ciflow/inductor/158459 -> ciflow/inductor/158459 2025-07-17T07:01:09.3717530Z * [new tag] ciflow/inductor/158460 -> ciflow/inductor/158460 2025-07-17T07:01:09.3718243Z * [new tag] ciflow/inductor/158462 -> ciflow/inductor/158462 2025-07-17T07:01:09.3718986Z * [new tag] ciflow/inductor/158467 -> ciflow/inductor/158467 2025-07-17T07:01:09.3719715Z * [new tag] ciflow/inductor/158468 -> ciflow/inductor/158468 2025-07-17T07:01:09.3720428Z * [new tag] ciflow/inductor/158476 -> ciflow/inductor/158476 2025-07-17T07:01:09.3721420Z * [new tag] ciflow/inductor/158479 -> ciflow/inductor/158479 2025-07-17T07:01:09.3722049Z * [new tag] ciflow/inductor/158480 -> ciflow/inductor/158480 2025-07-17T07:01:09.3722766Z * [new tag] ciflow/inductor/158485 -> ciflow/inductor/158485 2025-07-17T07:01:09.3723489Z * [new tag] ciflow/inductor/158490 -> ciflow/inductor/158490 2025-07-17T07:01:09.3724215Z * [new tag] ciflow/inductor/158492 -> ciflow/inductor/158492 2025-07-17T07:01:09.3725190Z * [new tag] ciflow/inductor/158494 -> ciflow/inductor/158494 2025-07-17T07:01:09.3726075Z * [new tag] ciflow/inductor/158495 -> ciflow/inductor/158495 2025-07-17T07:01:09.3729986Z * [new tag] ciflow/inductor/158498 -> ciflow/inductor/158498 2025-07-17T07:01:09.3730319Z * [new tag] ciflow/inductor/158499 -> ciflow/inductor/158499 2025-07-17T07:01:09.3730510Z * [new tag] ciflow/inductor/158500 -> ciflow/inductor/158500 2025-07-17T07:01:09.3730694Z * [new tag] ciflow/inductor/158501 -> ciflow/inductor/158501 2025-07-17T07:01:09.3731029Z * [new tag] ciflow/inductor/158504 -> ciflow/inductor/158504 2025-07-17T07:01:09.3731325Z * [new tag] ciflow/inductor/158509 -> ciflow/inductor/158509 2025-07-17T07:01:09.3731603Z * [new tag] ciflow/inductor/158520 -> ciflow/inductor/158520 2025-07-17T07:01:09.3732002Z * [new tag] ciflow/inductor/158524 -> ciflow/inductor/158524 2025-07-17T07:01:09.3732864Z * [new tag] ciflow/inductor/158525 -> ciflow/inductor/158525 2025-07-17T07:01:09.3733613Z * [new tag] ciflow/inductor/158526 -> ciflow/inductor/158526 2025-07-17T07:01:09.3734364Z * [new tag] ciflow/inductor/158528 -> ciflow/inductor/158528 2025-07-17T07:01:09.3735130Z * [new tag] ciflow/inductor/158534 -> ciflow/inductor/158534 2025-07-17T07:01:09.3736195Z * [new tag] ciflow/inductor/158535 -> ciflow/inductor/158535 2025-07-17T07:01:09.3736891Z * [new tag] ciflow/inductor/158537 -> ciflow/inductor/158537 2025-07-17T07:01:09.3737549Z * [new tag] ciflow/inductor/158538 -> ciflow/inductor/158538 2025-07-17T07:01:09.3738352Z * [new tag] ciflow/inductor/158543 -> ciflow/inductor/158543 2025-07-17T07:01:09.3739373Z * [new tag] ciflow/inductor/3b9a386 -> ciflow/inductor/3b9a386 2025-07-17T07:01:09.3740220Z * [new tag] ciflow/inductor/3d4b92b -> ciflow/inductor/3d4b92b 2025-07-17T07:01:09.3740984Z * [new tag] ciflow/inductor/d224ac7 -> ciflow/inductor/d224ac7 2025-07-17T07:01:09.3741986Z * [new tag] ciflow/linux-aarch64/157520 -> ciflow/linux-aarch64/157520 2025-07-17T07:01:09.3742634Z * [new tag] ciflow/linux-aarch64/157782 -> ciflow/linux-aarch64/157782 2025-07-17T07:01:09.3743325Z * [new tag] ciflow/linux-aarch64/157994 -> ciflow/linux-aarch64/157994 2025-07-17T07:01:09.3744214Z * [new tag] ciflow/linux-aarch64/158445 -> ciflow/linux-aarch64/158445 2025-07-17T07:01:09.3744952Z * [new tag] ciflow/mps/155200 -> ciflow/mps/155200 2025-07-17T07:01:09.3745823Z * [new tag] ciflow/mps/157553 -> ciflow/mps/157553 2025-07-17T07:01:09.3746487Z * [new tag] ciflow/mps/157875 -> ciflow/mps/157875 2025-07-17T07:01:09.3747052Z * [new tag] ciflow/mps/157876 -> ciflow/mps/157876 2025-07-17T07:01:09.3747769Z * [new tag] ciflow/mps/158237 -> ciflow/mps/158237 2025-07-17T07:01:09.3748716Z * [new tag] ciflow/mps/158349 -> ciflow/mps/158349 2025-07-17T07:01:09.3749376Z * [new tag] ciflow/mps/158350 -> ciflow/mps/158350 2025-07-17T07:01:09.3750163Z * [new tag] ciflow/mps/158351 -> ciflow/mps/158351 2025-07-17T07:01:09.3751235Z * [new tag] ciflow/periodic-rocm-mi300/156192 -> ciflow/periodic-rocm-mi300/156192 2025-07-17T07:01:09.3751898Z * [new tag] ciflow/periodic-rocm-mi300/157191 -> ciflow/periodic-rocm-mi300/157191 2025-07-17T07:01:09.3752607Z * [new tag] ciflow/periodic-rocm-mi300/158102 -> ciflow/periodic-rocm-mi300/158102 2025-07-17T07:01:09.3753281Z * [new tag] ciflow/periodic-rocm-mi300/158103 -> ciflow/periodic-rocm-mi300/158103 2025-07-17T07:01:09.3754279Z * [new tag] ciflow/periodic/054a2fd -> ciflow/periodic/054a2fd 2025-07-17T07:01:09.3754907Z * [new tag] ciflow/periodic/143959 -> ciflow/periodic/143959 2025-07-17T07:01:09.3755755Z * [new tag] ciflow/periodic/156559 -> ciflow/periodic/156559 2025-07-17T07:01:09.3756489Z * [new tag] ciflow/periodic/156900 -> ciflow/periodic/156900 2025-07-17T07:01:09.3757172Z * [new tag] ciflow/periodic/157748 -> ciflow/periodic/157748 2025-07-17T07:01:09.3757987Z * [new tag] ciflow/periodic/157939 -> ciflow/periodic/157939 2025-07-17T07:01:09.3758746Z * [new tag] ciflow/periodic/158145 -> ciflow/periodic/158145 2025-07-17T07:01:09.3759676Z * [new tag] ciflow/periodic/2a6d37d -> ciflow/periodic/2a6d37d 2025-07-17T07:01:09.3760476Z * [new tag] ciflow/periodic/317eeb8 -> ciflow/periodic/317eeb8 2025-07-17T07:01:09.3761293Z * [new tag] ciflow/periodic/3c32 -> ciflow/periodic/3c32 2025-07-17T07:01:09.3762203Z * [new tag] ciflow/periodic/3e98831 -> ciflow/periodic/3e98831 2025-07-17T07:01:09.3763497Z * [new tag] ciflow/periodic/94512-point -> ciflow/periodic/94512-point 2025-07-17T07:01:09.3764581Z * [new tag] ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519 2025-07-17T07:01:09.3765658Z * [new tag] ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275 2025-07-17T07:01:09.3766789Z * [new tag] ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761 2025-07-17T07:01:09.3767538Z * [new tag] ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12 2025-07-17T07:01:09.3768557Z * [new tag] ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0 2025-07-17T07:01:09.3769538Z * [new tag] ciflow/periodic/sha-ec5b83 -> ciflow/periodic/sha-ec5b83 2025-07-17T07:01:09.3770522Z * [new tag] ciflow/rocm-mi300/156192 -> ciflow/rocm-mi300/156192 2025-07-17T07:01:09.3771181Z * [new tag] ciflow/rocm-mi300/157191 -> ciflow/rocm-mi300/157191 2025-07-17T07:01:09.3771890Z * [new tag] ciflow/rocm-mi300/157520 -> ciflow/rocm-mi300/157520 2025-07-17T07:01:09.3772561Z * [new tag] ciflow/rocm-mi300/158102 -> ciflow/rocm-mi300/158102 2025-07-17T07:01:09.3773206Z * [new tag] ciflow/rocm-mi300/158103 -> ciflow/rocm-mi300/158103 2025-07-17T07:01:09.3774131Z * [new tag] ciflow/rocm-mi300/158221 -> ciflow/rocm-mi300/158221 2025-07-17T07:01:09.3774816Z * [new tag] ciflow/rocm-mi300/158459 -> ciflow/rocm-mi300/158459 2025-07-17T07:01:09.3775656Z * [new tag] ciflow/rocm/148492 -> ciflow/rocm/148492 2025-07-17T07:01:09.3776315Z * [new tag] ciflow/rocm/149601 -> ciflow/rocm/149601 2025-07-17T07:01:09.3776942Z * [new tag] ciflow/rocm/150312 -> ciflow/rocm/150312 2025-07-17T07:01:09.3777642Z * [new tag] ciflow/rocm/151845 -> ciflow/rocm/151845 2025-07-17T07:01:09.3778293Z * [new tag] ciflow/rocm/155200 -> ciflow/rocm/155200 2025-07-17T07:01:09.3779010Z * [new tag] ciflow/rocm/155877 -> ciflow/rocm/155877 2025-07-17T07:01:09.3779701Z * [new tag] ciflow/rocm/156165 -> ciflow/rocm/156165 2025-07-17T07:01:09.3780386Z * [new tag] ciflow/rocm/156192 -> ciflow/rocm/156192 2025-07-17T07:01:09.3781030Z * [new tag] ciflow/rocm/156592 -> ciflow/rocm/156592 2025-07-17T07:01:09.3781682Z * [new tag] ciflow/rocm/157520 -> ciflow/rocm/157520 2025-07-17T07:01:09.3782525Z * [new tag] ciflow/rocm/157964 -> ciflow/rocm/157964 2025-07-17T07:01:09.3783428Z * [new tag] ciflow/rocm/158037 -> ciflow/rocm/158037 2025-07-17T07:01:09.3784430Z * [new tag] ciflow/rocm/158074 -> ciflow/rocm/158074 2025-07-17T07:01:09.3785291Z * [new tag] ciflow/rocm/158219 -> ciflow/rocm/158219 2025-07-17T07:01:09.3786003Z * [new tag] ciflow/rocm/158220 -> ciflow/rocm/158220 2025-07-17T07:01:09.3786692Z * [new tag] ciflow/rocm/158224 -> ciflow/rocm/158224 2025-07-17T07:01:09.3787543Z * [new tag] ciflow/rocm/158271 -> ciflow/rocm/158271 2025-07-17T07:01:09.3788294Z * [new tag] ciflow/rocm/158408 -> ciflow/rocm/158408 2025-07-17T07:01:09.3788941Z * [new tag] ciflow/rocm/158459 -> ciflow/rocm/158459 2025-07-17T07:01:09.3789811Z * [new tag] ciflow/s390/143959 -> ciflow/s390/143959 2025-07-17T07:01:09.3790562Z * [new tag] ciflow/s390/151447 -> ciflow/s390/151447 2025-07-17T07:01:09.3791569Z * [new tag] ciflow/slow/01c7106 -> ciflow/slow/01c7106 2025-07-17T07:01:09.3792373Z * [new tag] ciflow/slow/0577043 -> ciflow/slow/0577043 2025-07-17T07:01:09.3793982Z * [new tag] ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym 2025-07-17T07:01:09.3794333Z * [new tag] ciflow/slow/0e81104 -> ciflow/slow/0e81104 2025-07-17T07:01:09.3794979Z * [new tag] ciflow/slow/157385 -> ciflow/slow/157385 2025-07-17T07:01:09.3795713Z * [new tag] ciflow/slow/157748 -> ciflow/slow/157748 2025-07-17T07:01:09.3796384Z * [new tag] ciflow/slow/158222 -> ciflow/slow/158222 2025-07-17T07:01:09.3797016Z * [new tag] ciflow/slow/158312 -> ciflow/slow/158312 2025-07-17T07:01:09.3797993Z * [new tag] ciflow/slow/158424 -> ciflow/slow/158424 2025-07-17T07:01:09.3799204Z * [new tag] ciflow/slow/1732077 -> ciflow/slow/1732077 2025-07-17T07:01:09.3800200Z * [new tag] ciflow/slow/187eb7c -> ciflow/slow/187eb7c 2025-07-17T07:01:09.3801143Z * [new tag] ciflow/slow/1faef89 -> ciflow/slow/1faef89 2025-07-17T07:01:09.3802009Z * [new tag] ciflow/slow/3920ec1 -> ciflow/slow/3920ec1 2025-07-17T07:01:09.3802965Z * [new tag] ciflow/slow/3b7c6b2 -> ciflow/slow/3b7c6b2 2025-07-17T07:01:09.3803777Z * [new tag] ciflow/slow/59a3759 -> ciflow/slow/59a3759 2025-07-17T07:01:09.3804646Z * [new tag] ciflow/slow/70ef0bb -> ciflow/slow/70ef0bb 2025-07-17T07:01:09.3806077Z * [new tag] ciflow/slow/788ff06 -> ciflow/slow/788ff06 2025-07-17T07:01:09.3807580Z * [new tag] ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym 2025-07-17T07:01:09.3807942Z * [new tag] ciflow/slow/9d85864 -> ciflow/slow/9d85864 2025-07-17T07:01:09.3808699Z * [new tag] ciflow/slow/9ffad5b -> ciflow/slow/9ffad5b 2025-07-17T07:01:09.3809604Z * [new tag] ciflow/slow/a206e8b -> ciflow/slow/a206e8b 2025-07-17T07:01:09.3810430Z * [new tag] ciflow/slow/a837609 -> ciflow/slow/a837609 2025-07-17T07:01:09.3811379Z * [new tag] ciflow/slow/af841f3 -> ciflow/slow/af841f3 2025-07-17T07:01:09.3812976Z * [new tag] ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym 2025-07-17T07:01:09.3813487Z * [new tag] ciflow/triton_binaries/158408 -> ciflow/triton_binaries/158408 2025-07-17T07:01:09.3814031Z * [new tag] ciflow/triton_binaries/158459 -> ciflow/triton_binaries/158459 2025-07-17T07:01:09.3815327Z * [new tag] ciflow/trunk/113258 -> ciflow/trunk/113258 2025-07-17T07:01:09.3815860Z * [new tag] ciflow/trunk/137400 -> ciflow/trunk/137400 2025-07-17T07:01:09.3816567Z * [new tag] ciflow/trunk/139971 -> ciflow/trunk/139971 2025-07-17T07:01:09.3817270Z * [new tag] ciflow/trunk/143712 -> ciflow/trunk/143712 2025-07-17T07:01:09.3817929Z * [new tag] ciflow/trunk/144557 -> ciflow/trunk/144557 2025-07-17T07:01:09.3818612Z * [new tag] ciflow/trunk/147470 -> ciflow/trunk/147470 2025-07-17T07:01:09.3819267Z * [new tag] ciflow/trunk/148180 -> ciflow/trunk/148180 2025-07-17T07:01:09.3819971Z * [new tag] ciflow/trunk/148328 -> ciflow/trunk/148328 2025-07-17T07:01:09.3820608Z * [new tag] ciflow/trunk/148492 -> ciflow/trunk/148492 2025-07-17T07:01:09.3821340Z * [new tag] ciflow/trunk/149003 -> ciflow/trunk/149003 2025-07-17T07:01:09.3822095Z * [new tag] ciflow/trunk/149601 -> ciflow/trunk/149601 2025-07-17T07:01:09.3823056Z * [new tag] ciflow/trunk/149961 -> ciflow/trunk/149961 2025-07-17T07:01:09.3824020Z * [new tag] ciflow/trunk/150312 -> ciflow/trunk/150312 2025-07-17T07:01:09.3824893Z * [new tag] ciflow/trunk/150691 -> ciflow/trunk/150691 2025-07-17T07:01:09.3825603Z * [new tag] ciflow/trunk/150762 -> ciflow/trunk/150762 2025-07-17T07:01:09.3826376Z * [new tag] ciflow/trunk/151777 -> ciflow/trunk/151777 2025-07-17T07:01:09.3827057Z * [new tag] ciflow/trunk/151845 -> ciflow/trunk/151845 2025-07-17T07:01:09.3827812Z * [new tag] ciflow/trunk/152624 -> ciflow/trunk/152624 2025-07-17T07:01:09.3828690Z * [new tag] ciflow/trunk/153666 -> ciflow/trunk/153666 2025-07-17T07:01:09.3829409Z * [new tag] ciflow/trunk/154149 -> ciflow/trunk/154149 2025-07-17T07:01:09.3830120Z * [new tag] ciflow/trunk/154199 -> ciflow/trunk/154199 2025-07-17T07:01:09.3830851Z * [new tag] ciflow/trunk/154694 -> ciflow/trunk/154694 2025-07-17T07:01:09.3831585Z * [new tag] ciflow/trunk/154983 -> ciflow/trunk/154983 2025-07-17T07:01:09.3832249Z * [new tag] ciflow/trunk/155489 -> ciflow/trunk/155489 2025-07-17T07:01:09.3832962Z * [new tag] ciflow/trunk/155958 -> ciflow/trunk/155958 2025-07-17T07:01:09.3833795Z * [new tag] ciflow/trunk/156049 -> ciflow/trunk/156049 2025-07-17T07:01:09.3834535Z * [new tag] ciflow/trunk/156097 -> ciflow/trunk/156097 2025-07-17T07:01:09.3835271Z * [new tag] ciflow/trunk/156141 -> ciflow/trunk/156141 2025-07-17T07:01:09.3835960Z * [new tag] ciflow/trunk/156165 -> ciflow/trunk/156165 2025-07-17T07:01:09.3836729Z * [new tag] ciflow/trunk/156175 -> ciflow/trunk/156175 2025-07-17T07:01:09.3837425Z * [new tag] ciflow/trunk/156192 -> ciflow/trunk/156192 2025-07-17T07:01:09.3838112Z * [new tag] ciflow/trunk/156296 -> ciflow/trunk/156296 2025-07-17T07:01:09.3838827Z * [new tag] ciflow/trunk/156370 -> ciflow/trunk/156370 2025-07-17T07:01:09.3839550Z * [new tag] ciflow/trunk/156559 -> ciflow/trunk/156559 2025-07-17T07:01:09.3840251Z * [new tag] ciflow/trunk/156605 -> ciflow/trunk/156605 2025-07-17T07:01:09.3840969Z * [new tag] ciflow/trunk/156626 -> ciflow/trunk/156626 2025-07-17T07:01:09.3842811Z * [new tag] ciflow/trunk/156666 -> ciflow/trunk/156666 2025-07-17T07:01:09.3843563Z * [new tag] ciflow/trunk/156753 -> ciflow/trunk/156753 2025-07-17T07:01:09.3844266Z * [new tag] ciflow/trunk/156781 -> ciflow/trunk/156781 2025-07-17T07:01:09.3844995Z * [new tag] ciflow/trunk/156874 -> ciflow/trunk/156874 2025-07-17T07:01:09.3845790Z * [new tag] ciflow/trunk/157199 -> ciflow/trunk/157199 2025-07-17T07:01:09.3846578Z * [new tag] ciflow/trunk/157432 -> ciflow/trunk/157432 2025-07-17T07:01:09.3847367Z * [new tag] ciflow/trunk/157520 -> ciflow/trunk/157520 2025-07-17T07:01:09.3848044Z * [new tag] ciflow/trunk/157550 -> ciflow/trunk/157550 2025-07-17T07:01:09.3848769Z * [new tag] ciflow/trunk/157552 -> ciflow/trunk/157552 2025-07-17T07:01:09.3849513Z * [new tag] ciflow/trunk/157580 -> ciflow/trunk/157580 2025-07-17T07:01:09.3850247Z * [new tag] ciflow/trunk/157685 -> ciflow/trunk/157685 2025-07-17T07:01:09.3850953Z * [new tag] ciflow/trunk/157689 -> ciflow/trunk/157689 2025-07-17T07:01:09.3851686Z * [new tag] ciflow/trunk/157699 -> ciflow/trunk/157699 2025-07-17T07:01:09.3852417Z * [new tag] ciflow/trunk/157748 -> ciflow/trunk/157748 2025-07-17T07:01:09.3853148Z * [new tag] ciflow/trunk/157791 -> ciflow/trunk/157791 2025-07-17T07:01:09.3853888Z * [new tag] ciflow/trunk/157804 -> ciflow/trunk/157804 2025-07-17T07:01:09.3854689Z * [new tag] ciflow/trunk/157887 -> ciflow/trunk/157887 2025-07-17T07:01:09.3855333Z * [new tag] ciflow/trunk/157908 -> ciflow/trunk/157908 2025-07-17T07:01:09.3855989Z * [new tag] ciflow/trunk/157910 -> ciflow/trunk/157910 2025-07-17T07:01:09.3856909Z * [new tag] ciflow/trunk/157935 -> ciflow/trunk/157935 2025-07-17T07:01:09.3857760Z * [new tag] ciflow/trunk/157963 -> ciflow/trunk/157963 2025-07-17T07:01:09.3858458Z * [new tag] ciflow/trunk/157994 -> ciflow/trunk/157994 2025-07-17T07:01:09.3859201Z * [new tag] ciflow/trunk/158015 -> ciflow/trunk/158015 2025-07-17T07:01:09.3859893Z * [new tag] ciflow/trunk/158037 -> ciflow/trunk/158037 2025-07-17T07:01:09.3860618Z * [new tag] ciflow/trunk/158062 -> ciflow/trunk/158062 2025-07-17T07:01:09.3861350Z * [new tag] ciflow/trunk/158072 -> ciflow/trunk/158072 2025-07-17T07:01:09.3862085Z * [new tag] ciflow/trunk/158091 -> ciflow/trunk/158091 2025-07-17T07:01:09.3862833Z * [new tag] ciflow/trunk/158104 -> ciflow/trunk/158104 2025-07-17T07:01:09.3864085Z * [new tag] ciflow/trunk/158119 -> ciflow/trunk/158119 2025-07-17T07:01:09.3864718Z * [new tag] ciflow/trunk/158148 -> ciflow/trunk/158148 2025-07-17T07:01:09.3865578Z * [new tag] ciflow/trunk/158185 -> ciflow/trunk/158185 2025-07-17T07:01:09.3866488Z * [new tag] ciflow/trunk/158203 -> ciflow/trunk/158203 2025-07-17T07:01:09.3867219Z * [new tag] ciflow/trunk/158219 -> ciflow/trunk/158219 2025-07-17T07:01:09.3867890Z * [new tag] ciflow/trunk/158220 -> ciflow/trunk/158220 2025-07-17T07:01:09.3868611Z * [new tag] ciflow/trunk/158222 -> ciflow/trunk/158222 2025-07-17T07:01:09.3869328Z * [new tag] ciflow/trunk/158223 -> ciflow/trunk/158223 2025-07-17T07:01:09.3870176Z * [new tag] ciflow/trunk/158224 -> ciflow/trunk/158224 2025-07-17T07:01:09.3875088Z * [new tag] ciflow/trunk/158229 -> ciflow/trunk/158229 2025-07-17T07:01:09.3875884Z * [new tag] ciflow/trunk/158249 -> ciflow/trunk/158249 2025-07-17T07:01:09.3876648Z * [new tag] ciflow/trunk/158259 -> ciflow/trunk/158259 2025-07-17T07:01:09.3877312Z * [new tag] ciflow/trunk/158289 -> ciflow/trunk/158289 2025-07-17T07:01:09.3878066Z * [new tag] ciflow/trunk/158312 -> ciflow/trunk/158312 2025-07-17T07:01:09.3879046Z * [new tag] ciflow/trunk/158323 -> ciflow/trunk/158323 2025-07-17T07:01:09.3879811Z * [new tag] ciflow/trunk/158356 -> ciflow/trunk/158356 2025-07-17T07:01:09.3880535Z * [new tag] ciflow/trunk/158363 -> ciflow/trunk/158363 2025-07-17T07:01:09.3881263Z * [new tag] ciflow/trunk/158368 -> ciflow/trunk/158368 2025-07-17T07:01:09.3882174Z * [new tag] ciflow/trunk/158373 -> ciflow/trunk/158373 2025-07-17T07:01:09.3882902Z * [new tag] ciflow/trunk/158377 -> ciflow/trunk/158377 2025-07-17T07:01:09.3883793Z * [new tag] ciflow/trunk/158380 -> ciflow/trunk/158380 2025-07-17T07:01:09.3884472Z * [new tag] ciflow/trunk/158400 -> ciflow/trunk/158400 2025-07-17T07:01:09.3885164Z * [new tag] ciflow/trunk/158418 -> ciflow/trunk/158418 2025-07-17T07:01:09.3885972Z * [new tag] ciflow/trunk/158424 -> ciflow/trunk/158424 2025-07-17T07:01:09.3886798Z * [new tag] ciflow/trunk/158430 -> ciflow/trunk/158430 2025-07-17T07:01:09.3887474Z * [new tag] ciflow/trunk/158442 -> ciflow/trunk/158442 2025-07-17T07:01:09.3888290Z * [new tag] ciflow/trunk/158458 -> ciflow/trunk/158458 2025-07-17T07:01:09.3888926Z * [new tag] ciflow/trunk/158459 -> ciflow/trunk/158459 2025-07-17T07:01:09.3889772Z * [new tag] ciflow/trunk/158473 -> ciflow/trunk/158473 2025-07-17T07:01:09.3890478Z * [new tag] ciflow/trunk/158479 -> ciflow/trunk/158479 2025-07-17T07:01:09.3891173Z * [new tag] ciflow/trunk/158485 -> ciflow/trunk/158485 2025-07-17T07:01:09.3891943Z * [new tag] ciflow/trunk/158492 -> ciflow/trunk/158492 2025-07-17T07:01:09.3892641Z * [new tag] ciflow/trunk/158524 -> ciflow/trunk/158524 2025-07-17T07:01:09.3893548Z * [new tag] ciflow/trunk/158532 -> ciflow/trunk/158532 2025-07-17T07:01:09.3894222Z * [new tag] ciflow/trunk/158543 -> ciflow/trunk/158543 2025-07-17T07:01:09.3895423Z * [new tag] ciflow/unstable/123 -> ciflow/unstable/123 2025-07-17T07:01:09.3896220Z * [new tag] ciflow/win-arm64/157935 -> ciflow/win-arm64/157935 2025-07-17T07:01:09.3897013Z * [new tag] ciflow/xpu/139971 -> ciflow/xpu/139971 2025-07-17T07:01:09.3897725Z * [new tag] ciflow/xpu/150218 -> ciflow/xpu/150218 2025-07-17T07:01:09.3898524Z * [new tag] ciflow/xpu/155200 -> ciflow/xpu/155200 2025-07-17T07:01:09.3899776Z * [new tag] ciflow/xpu/156812 -> ciflow/xpu/156812 2025-07-17T07:01:09.3900350Z * [new tag] ciflow/xpu/157699 -> ciflow/xpu/157699 2025-07-17T07:01:09.3901050Z * [new tag] ciflow/xpu/157954 -> ciflow/xpu/157954 2025-07-17T07:01:09.3901762Z * [new tag] ciflow/xpu/158336 -> ciflow/xpu/158336 2025-07-17T07:01:09.3902619Z * [new tag] ciflow/xpu/158337 -> ciflow/xpu/158337 2025-07-17T07:01:09.3903396Z * [new tag] ciflow/xpu/158340 -> ciflow/xpu/158340 2025-07-17T07:01:09.3904231Z * [new tag] ciflow/xpu/158533 -> ciflow/xpu/158533 2025-07-17T07:01:09.3904907Z * [new tag] ciflow/xpu/158542 -> ciflow/xpu/158542 2025-07-17T07:01:09.3905704Z * [new tag] cslpull75 -> cslpull75 2025-07-17T07:01:09.3906476Z * [new tag] cslpull76 -> cslpull76 2025-07-17T07:01:09.3907243Z * [new tag] cslpull77 -> cslpull77 2025-07-17T07:01:09.3907978Z * [new tag] cslpull78 -> cslpull78 2025-07-17T07:01:09.3909149Z * [new tag] cslpull79 -> cslpull79 2025-07-17T07:01:09.3910145Z * [new tag] cslpull80 -> cslpull80 2025-07-17T07:01:09.3910988Z * [new tag] cslpull81 -> cslpull81 2025-07-17T07:01:09.3911850Z * [new tag] cslpull82 -> cslpull82 2025-07-17T07:01:09.3912682Z * [new tag] cslpull83 -> cslpull83 2025-07-17T07:01:09.3913490Z * [new tag] cslpull84 -> cslpull84 2025-07-17T07:01:09.3914282Z * [new tag] cslpull85 -> cslpull85 2025-07-17T07:01:09.3915165Z * [new tag] cslpull86 -> cslpull86 2025-07-17T07:01:09.3915976Z * [new tag] cslpull87 -> cslpull87 2025-07-17T07:01:09.3916848Z * [new tag] cslpull88 -> cslpull88 2025-07-17T07:01:09.3917605Z * [new tag] cslpull89 -> cslpull89 2025-07-17T07:01:09.3918303Z * [new tag] cslpull90 -> cslpull90 2025-07-17T07:01:09.3919676Z * [new tag] cslpull91 -> cslpull91 2025-07-17T07:01:09.3920498Z * [new tag] cslpull92 -> cslpull92 2025-07-17T07:01:09.3921208Z * [new tag] flight_5 -> flight_5 2025-07-17T07:01:09.3922088Z * [new tag] flight_5.1 -> flight_5.1 2025-07-17T07:01:09.3922974Z * [new tag] flight_5.2 -> flight_5.2 2025-07-17T07:01:09.3923673Z * [new tag] flight_5.3 -> flight_5.3 2025-07-17T07:01:09.3924556Z * [new tag] forpull1 -> forpull1 2025-07-17T07:01:09.3925797Z * [new tag] malfet/tag-2ef5611 -> malfet/tag-2ef5611 2025-07-17T07:01:09.3927110Z * [new tag] malfet/tag-317b1a0 -> malfet/tag-317b1a0 2025-07-17T07:01:09.3927815Z * [new tag] malfet/tag-ec6f767 -> malfet/tag-ec6f767 2025-07-17T07:01:09.3928721Z * [new tag] nightly-binary -> nightly-binary 2025-07-17T07:01:09.3929423Z * [new tag] sqzhang_flight4_plus -> sqzhang_flight4_plus 2025-07-17T07:01:09.3930362Z * [new tag] sqzhang_flight_3 -> sqzhang_flight_3 2025-07-17T07:01:09.3931834Z * [new tag] trunk/0083032e7559dc8f02483ba60373adfcdaf9dae6 -> trunk/0083032e7559dc8f02483ba60373adfcdaf9dae6 2025-07-17T07:01:09.3932703Z * [new tag] trunk/008345be9d0c32f67459bcf3e6705be43d496f74 -> trunk/008345be9d0c32f67459bcf3e6705be43d496f74 2025-07-17T07:01:09.3933912Z * [new tag] trunk/00ae620b9f72cc751672c2fd92a04fc86704a87a -> trunk/00ae620b9f72cc751672c2fd92a04fc86704a87a 2025-07-17T07:01:09.3934692Z * [new tag] trunk/0105cd89ab508ec56126c1de85c8f5b5acc446b5 -> trunk/0105cd89ab508ec56126c1de85c8f5b5acc446b5 2025-07-17T07:01:09.3935556Z * [new tag] trunk/011026205a9d4c38458130f8ca242028f6184bf0 -> trunk/011026205a9d4c38458130f8ca242028f6184bf0 2025-07-17T07:01:09.3936354Z * [new tag] trunk/013cf1e3302d27de36588cf7a7130d76a5686bad -> trunk/013cf1e3302d27de36588cf7a7130d76a5686bad 2025-07-17T07:01:09.3937199Z * [new tag] trunk/013dfeabb405274546f19637c04f8a5f75923316 -> trunk/013dfeabb405274546f19637c04f8a5f75923316 2025-07-17T07:01:09.3938103Z * [new tag] trunk/018e9826a2ed09cfcf7424e0b3215bef5ad6499e -> trunk/018e9826a2ed09cfcf7424e0b3215bef5ad6499e 2025-07-17T07:01:09.3939291Z * [new tag] trunk/019e30e3b80d091d64253df4cdd149713e3e910e -> trunk/019e30e3b80d091d64253df4cdd149713e3e910e 2025-07-17T07:01:09.3940178Z * [new tag] trunk/01b0f09931d47bd2716398a0c335b2807dc3074d -> trunk/01b0f09931d47bd2716398a0c335b2807dc3074d 2025-07-17T07:01:09.3941021Z * [new tag] trunk/01b8f5e685fdb34aa50b73a84a55fc285e6b904a -> trunk/01b8f5e685fdb34aa50b73a84a55fc285e6b904a 2025-07-17T07:01:09.3941950Z * [new tag] trunk/02080c2cd94b37ad92e3d8803bc773f6abd2ae2f -> trunk/02080c2cd94b37ad92e3d8803bc773f6abd2ae2f 2025-07-17T07:01:09.3942717Z * [new tag] trunk/020da744370f6ee23e377357e9acc330b5610a67 -> trunk/020da744370f6ee23e377357e9acc330b5610a67 2025-07-17T07:01:09.3943641Z * [new tag] trunk/023887fc5af5a7273d7eb0388fdf1f0e87eafb28 -> trunk/023887fc5af5a7273d7eb0388fdf1f0e87eafb28 2025-07-17T07:01:09.3944410Z * [new tag] trunk/02608e560a1d7b669ad450a89542f7e9ba068658 -> trunk/02608e560a1d7b669ad450a89542f7e9ba068658 2025-07-17T07:01:09.3945314Z * [new tag] trunk/02715d0876bc66f46b9c7b4f277bedf8e251cc82 -> trunk/02715d0876bc66f46b9c7b4f277bedf8e251cc82 2025-07-17T07:01:09.3946507Z * [new tag] trunk/02724b5f649b93ef7960962bdde7a667c0893d21 -> trunk/02724b5f649b93ef7960962bdde7a667c0893d21 2025-07-17T07:01:09.3947341Z * [new tag] trunk/029e2b05c225588098d3eba445fd04189691f77d -> trunk/029e2b05c225588098d3eba445fd04189691f77d 2025-07-17T07:01:09.3948300Z * [new tag] trunk/02a9d9095f397f56fe64ef07ced8e7ffed6dcba1 -> trunk/02a9d9095f397f56fe64ef07ced8e7ffed6dcba1 2025-07-17T07:01:09.3949068Z * [new tag] trunk/02c7ab2f9baac05bd199392b70bc016d55f99b13 -> trunk/02c7ab2f9baac05bd199392b70bc016d55f99b13 2025-07-17T07:01:09.3949821Z * [new tag] trunk/03023f178c611249d41c62369ba95fe54316fe90 -> trunk/03023f178c611249d41c62369ba95fe54316fe90 2025-07-17T07:01:09.3950643Z * [new tag] trunk/03488d820c292b8ec4bfd9a4e25d5f28068c9375 -> trunk/03488d820c292b8ec4bfd9a4e25d5f28068c9375 2025-07-17T07:01:09.3951511Z * [new tag] trunk/034a7f6437bec853a938dbc19b549b9319b67f69 -> trunk/034a7f6437bec853a938dbc19b549b9319b67f69 2025-07-17T07:01:09.3952289Z * [new tag] trunk/0364db7cd14ffa67b48ef8c27fefbb3eed2b065d -> trunk/0364db7cd14ffa67b48ef8c27fefbb3eed2b065d 2025-07-17T07:01:09.3953191Z * [new tag] trunk/03852ddc22350eb8b6ed6b61777639ce6080f3dc -> trunk/03852ddc22350eb8b6ed6b61777639ce6080f3dc 2025-07-17T07:01:09.3954064Z * [new tag] trunk/039a1ce0ebbeb0adacbf9537c4085d977dba150a -> trunk/039a1ce0ebbeb0adacbf9537c4085d977dba150a 2025-07-17T07:01:09.3954878Z * [new tag] trunk/03b307575a98dc1d953c9d3521a9489e0e61e70c -> trunk/03b307575a98dc1d953c9d3521a9489e0e61e70c 2025-07-17T07:01:09.3955789Z * [new tag] trunk/04178d347c6baec5613f8063a2c77cf6f9657ee2 -> trunk/04178d347c6baec5613f8063a2c77cf6f9657ee2 2025-07-17T07:01:09.3956703Z * [new tag] trunk/04349f9ee541c7d07cc057bbe739f46bd4c30dcc -> trunk/04349f9ee541c7d07cc057bbe739f46bd4c30dcc 2025-07-17T07:01:09.3957629Z * [new tag] trunk/049dc48d1edf49c26d493fdb271fe5e5adc9c985 -> trunk/049dc48d1edf49c26d493fdb271fe5e5adc9c985 2025-07-17T07:01:09.3958565Z * [new tag] trunk/04b91a9e43518fcd34a474a832bac05d4583fcc3 -> trunk/04b91a9e43518fcd34a474a832bac05d4583fcc3 2025-07-17T07:01:09.3959427Z * [new tag] trunk/04bd7e6850e8efec77994963ffee87549555b9c3 -> trunk/04bd7e6850e8efec77994963ffee87549555b9c3 2025-07-17T07:01:09.3960323Z * [new tag] trunk/04cf2c9d24b7d9e7f7cdd4cf98c8bd0908c38110 -> trunk/04cf2c9d24b7d9e7f7cdd4cf98c8bd0908c38110 2025-07-17T07:01:09.3961145Z * [new tag] trunk/0504480f37714a289b2ba32c9cf32a5e50e86d38 -> trunk/0504480f37714a289b2ba32c9cf32a5e50e86d38 2025-07-17T07:01:09.3962019Z * [new tag] trunk/054cd4ca28d17507df46054fe355c697f6a07ce8 -> trunk/054cd4ca28d17507df46054fe355c697f6a07ce8 2025-07-17T07:01:09.3963148Z * [new tag] trunk/058fb1790f2c474cd4ecb5ec625eef896c554544 -> trunk/058fb1790f2c474cd4ecb5ec625eef896c554544 2025-07-17T07:01:09.3963926Z * [new tag] trunk/0596323c35d245099a4f4d3172b0efa20a639c84 -> trunk/0596323c35d245099a4f4d3172b0efa20a639c84 2025-07-17T07:01:09.3964819Z * [new tag] trunk/05d7288e316ae5c9c661c4529f9f130a46263e5b -> trunk/05d7288e316ae5c9c661c4529f9f130a46263e5b 2025-07-17T07:01:09.3965807Z * [new tag] trunk/05dd638ee98b36254c84095894c36fd0e7d95544 -> trunk/05dd638ee98b36254c84095894c36fd0e7d95544 2025-07-17T07:01:09.3966775Z * [new tag] trunk/05dfd312cfbfdecc6cb1e7d1d0bb4ee18370ae7e -> trunk/05dfd312cfbfdecc6cb1e7d1d0bb4ee18370ae7e 2025-07-17T07:01:09.3967516Z * [new tag] trunk/05faba40287cf7d8734da96cb2e904f39710bf29 -> trunk/05faba40287cf7d8734da96cb2e904f39710bf29 2025-07-17T07:01:09.3969518Z * [new tag] trunk/060838c2312ad207c7afe2c86f8a484afea5f328 -> trunk/060838c2312ad207c7afe2c86f8a484afea5f328 2025-07-17T07:01:09.3970399Z * [new tag] trunk/0629dfb860b00a10550d91dd395968f663f45fdd -> trunk/0629dfb860b00a10550d91dd395968f663f45fdd 2025-07-17T07:01:09.3971338Z * [new tag] trunk/06408dae49d06b6146fdd9d7a37eb5dde4f5e78d -> trunk/06408dae49d06b6146fdd9d7a37eb5dde4f5e78d 2025-07-17T07:01:09.3972244Z * [new tag] trunk/0640cfa38c1426a41ab4a0b3e3dab7c730cdc2ad -> trunk/0640cfa38c1426a41ab4a0b3e3dab7c730cdc2ad 2025-07-17T07:01:09.3973279Z * [new tag] trunk/064288cbab94c9931ca2296a2b9723e864f9050a -> trunk/064288cbab94c9931ca2296a2b9723e864f9050a 2025-07-17T07:01:09.3974156Z * [new tag] trunk/064a7db7fc3b06eb8e14d6c7d767f87fcf396ab6 -> trunk/064a7db7fc3b06eb8e14d6c7d767f87fcf396ab6 2025-07-17T07:01:09.3974923Z * [new tag] trunk/067fd0b3abd28f1b7dae883ffec5bc7459d35970 -> trunk/067fd0b3abd28f1b7dae883ffec5bc7459d35970 2025-07-17T07:01:09.3975747Z * [new tag] trunk/06930706a195144cd6172a5f2eb505cec56e9ec3 -> trunk/06930706a195144cd6172a5f2eb505cec56e9ec3 2025-07-17T07:01:09.3976543Z * [new tag] trunk/06a40b685056f60c4fbdc10d09a85b9fc3fca34f -> trunk/06a40b685056f60c4fbdc10d09a85b9fc3fca34f 2025-07-17T07:01:09.3977455Z * [new tag] trunk/06a67a8948dac9d02f22b3e2591a43b60981cdb4 -> trunk/06a67a8948dac9d02f22b3e2591a43b60981cdb4 2025-07-17T07:01:09.3978327Z * [new tag] trunk/06b3265cb1a27ea3090dc1fc86a6ce17518f989c -> trunk/06b3265cb1a27ea3090dc1fc86a6ce17518f989c 2025-07-17T07:01:09.3979167Z * [new tag] trunk/06f39a71b6cd14e0844b5eb1e0e085f7ae78d221 -> trunk/06f39a71b6cd14e0844b5eb1e0e085f7ae78d221 2025-07-17T07:01:09.3979917Z * [new tag] trunk/070aa59e491aa6987459cd1941ef647f2ad13858 -> trunk/070aa59e491aa6987459cd1941ef647f2ad13858 2025-07-17T07:01:09.3980800Z * [new tag] trunk/070e580d301efd626e327d1f88e0921b476d0f30 -> trunk/070e580d301efd626e327d1f88e0921b476d0f30 2025-07-17T07:01:09.3981591Z * [new tag] trunk/0756ebcd4890b19072e586fb2cbd2b25a80f91f4 -> trunk/0756ebcd4890b19072e586fb2cbd2b25a80f91f4 2025-07-17T07:01:09.3982622Z * [new tag] trunk/0797b2b6a80cf70a7accc3d5413186e7693d4451 -> trunk/0797b2b6a80cf70a7accc3d5413186e7693d4451 2025-07-17T07:01:09.3983376Z * [new tag] trunk/07bb097698223fe42d54b019638dd026c75f09a9 -> trunk/07bb097698223fe42d54b019638dd026c75f09a9 2025-07-17T07:01:09.3984291Z * [new tag] trunk/07da8a469bdd69966e1f832e3d09d991798f854c -> trunk/07da8a469bdd69966e1f832e3d09d991798f854c 2025-07-17T07:01:09.3985162Z * [new tag] trunk/07e340e29ccbe18ef59e8f60ec3f03ccc44e5e9c -> trunk/07e340e29ccbe18ef59e8f60ec3f03ccc44e5e9c 2025-07-17T07:01:09.3986205Z * [new tag] trunk/07eb374e7eefaa84a997d0adaaeecb4706d60e74 -> trunk/07eb374e7eefaa84a997d0adaaeecb4706d60e74 2025-07-17T07:01:09.3987105Z * [new tag] trunk/08274640028f68418d8f889d01af577b90ac2ec1 -> trunk/08274640028f68418d8f889d01af577b90ac2ec1 2025-07-17T07:01:09.3987874Z * [new tag] trunk/085f270a00b4452bbb005d6b3d448e9d0b9d6fa0 -> trunk/085f270a00b4452bbb005d6b3d448e9d0b9d6fa0 2025-07-17T07:01:09.3988842Z * [new tag] trunk/0860606729d16b9855157404da9b0d4654f3c626 -> trunk/0860606729d16b9855157404da9b0d4654f3c626 2025-07-17T07:01:09.3989589Z * [new tag] trunk/08799217aeb17128d89d675ce5b537761286417a -> trunk/08799217aeb17128d89d675ce5b537761286417a 2025-07-17T07:01:09.3990487Z * [new tag] trunk/08d15d3ec15b9b3fce81713cde20901806ecef42 -> trunk/08d15d3ec15b9b3fce81713cde20901806ecef42 2025-07-17T07:01:09.3991229Z * [new tag] trunk/08dae945ae380d80efbaf140a95abfc5d96e5100 -> trunk/08dae945ae380d80efbaf140a95abfc5d96e5100 2025-07-17T07:01:09.3992133Z * [new tag] trunk/08e9dd280f497fc820e35c458c843dc44f0282c6 -> trunk/08e9dd280f497fc820e35c458c843dc44f0282c6 2025-07-17T07:01:09.3992981Z * [new tag] trunk/092aed1b18c31042d7772a6f9ec1959df4bf5c3c -> trunk/092aed1b18c31042d7772a6f9ec1959df4bf5c3c 2025-07-17T07:01:09.3993887Z * [new tag] trunk/09328eb02f5412d2211b5fd638ce82d0e03b9c1f -> trunk/09328eb02f5412d2211b5fd638ce82d0e03b9c1f 2025-07-17T07:01:09.3994725Z * [new tag] trunk/0935a97d959918727700ae2c1ebeadc5b12a2b6c -> trunk/0935a97d959918727700ae2c1ebeadc5b12a2b6c 2025-07-17T07:01:09.3995551Z * [new tag] trunk/093aaccae254355b3637ef8760e762a3f9c3783c -> trunk/093aaccae254355b3637ef8760e762a3f9c3783c 2025-07-17T07:01:09.3996807Z * [new tag] trunk/093fd47dbef4f08691210de6c08cf269f28e4de5 -> trunk/093fd47dbef4f08691210de6c08cf269f28e4de5 2025-07-17T07:01:09.3997617Z * [new tag] trunk/099d0d6121125062ebc05771c8330cb7cd8d053a -> trunk/099d0d6121125062ebc05771c8330cb7cd8d053a 2025-07-17T07:01:09.3998482Z * [new tag] trunk/09db3a22e8783c4841697317688ba9467c7cc457 -> trunk/09db3a22e8783c4841697317688ba9467c7cc457 2025-07-17T07:01:09.3999438Z * [new tag] trunk/09ffba3cf79eeedf48a0fb39a26dcc0294872480 -> trunk/09ffba3cf79eeedf48a0fb39a26dcc0294872480 2025-07-17T07:01:09.4000342Z * [new tag] trunk/0a0023d9840570938a10472418eaac85098ec41b -> trunk/0a0023d9840570938a10472418eaac85098ec41b 2025-07-17T07:01:09.4001257Z * [new tag] trunk/0a092c7de67767eed3adb7abc0d49dfd3d26d0cd -> trunk/0a092c7de67767eed3adb7abc0d49dfd3d26d0cd 2025-07-17T07:01:09.4002158Z * [new tag] trunk/0a16818d5b3fdf0fb8148dd6b849687251a56376 -> trunk/0a16818d5b3fdf0fb8148dd6b849687251a56376 2025-07-17T07:01:09.4002942Z * [new tag] trunk/0a2ec7681d2af973d8daaf7905431a088739dc90 -> trunk/0a2ec7681d2af973d8daaf7905431a088739dc90 2025-07-17T07:01:09.4003878Z * [new tag] trunk/0a624c2dc5675e35917976467a8c533baf2a98a0 -> trunk/0a624c2dc5675e35917976467a8c533baf2a98a0 2025-07-17T07:01:09.4004772Z * [new tag] trunk/0a63053fe90405cc6ee5e42fa007e32ed1e2cbac -> trunk/0a63053fe90405cc6ee5e42fa007e32ed1e2cbac 2025-07-17T07:01:09.4005648Z * [new tag] trunk/0a6b66c881cba3f6a6c1a3cb8ddf698846d99822 -> trunk/0a6b66c881cba3f6a6c1a3cb8ddf698846d99822 2025-07-17T07:01:09.4006658Z * [new tag] trunk/0a99b026d6bd0f67dc2c0a20fe3228ddc4144854 -> trunk/0a99b026d6bd0f67dc2c0a20fe3228ddc4144854 2025-07-17T07:01:09.4007450Z * [new tag] trunk/0a9d450168ce58b2bb7f2cedc27a61012123564f -> trunk/0a9d450168ce58b2bb7f2cedc27a61012123564f 2025-07-17T07:01:09.4008312Z * [new tag] trunk/0ab075a69e4577a60c4dcbff7bcc2ecd0a15ce46 -> trunk/0ab075a69e4577a60c4dcbff7bcc2ecd0a15ce46 2025-07-17T07:01:09.4009162Z * [new tag] trunk/0ad88a2224e9f0a2ed4f405e827a745945d505ce -> trunk/0ad88a2224e9f0a2ed4f405e827a745945d505ce 2025-07-17T07:01:09.4010091Z * [new tag] trunk/0aed855b2bde6d9bd045bb20cc24544a9f2fb72b -> trunk/0aed855b2bde6d9bd045bb20cc24544a9f2fb72b 2025-07-17T07:01:09.4011045Z * [new tag] trunk/0b19d463d963a0b2ee5558d2c0bb79b2cbff6e64 -> trunk/0b19d463d963a0b2ee5558d2c0bb79b2cbff6e64 2025-07-17T07:01:09.4011882Z * [new tag] trunk/0b62465b99b23cb4afcd07424676cce34a676041 -> trunk/0b62465b99b23cb4afcd07424676cce34a676041 2025-07-17T07:01:09.4012830Z * [new tag] trunk/0b677560e686d828f9f5ed1cb87b1d7a54ee2781 -> trunk/0b677560e686d828f9f5ed1cb87b1d7a54ee2781 2025-07-17T07:01:09.4013696Z * [new tag] trunk/0b6c0898e6c352c8ea93daec854e704b41485375 -> trunk/0b6c0898e6c352c8ea93daec854e704b41485375 2025-07-17T07:01:09.4014564Z * [new tag] trunk/0bb733ba230051301b3fb3fa49d1d6662744b395 -> trunk/0bb733ba230051301b3fb3fa49d1d6662744b395 2025-07-17T07:01:09.4015408Z * [new tag] trunk/0bce39026917d10995ff47352c3da9fff0ec31ff -> trunk/0bce39026917d10995ff47352c3da9fff0ec31ff 2025-07-17T07:01:09.4016504Z * [new tag] trunk/0c58bdd8fb5f269aef100af8e2c43cfcf5f1f9dd -> trunk/0c58bdd8fb5f269aef100af8e2c43cfcf5f1f9dd 2025-07-17T07:01:09.4017355Z * [new tag] trunk/0ca2a79f5b80c1ec8be95e6f7de4182dd90f3502 -> trunk/0ca2a79f5b80c1ec8be95e6f7de4182dd90f3502 2025-07-17T07:01:09.4018206Z * [new tag] trunk/0cb36e2d62c811fcddea4c6d28b1c65246cdd160 -> trunk/0cb36e2d62c811fcddea4c6d28b1c65246cdd160 2025-07-17T07:01:09.4019094Z * [new tag] trunk/0cb85c188f3665c23766cda25c8169f1a436d36b -> trunk/0cb85c188f3665c23766cda25c8169f1a436d36b 2025-07-17T07:01:09.4020029Z * [new tag] trunk/0d01bafc34fc99a0b3e46cbf1ecfd8f97563efa6 -> trunk/0d01bafc34fc99a0b3e46cbf1ecfd8f97563efa6 2025-07-17T07:01:09.4020759Z * [new tag] trunk/0d17029fea3d96bb88b19912946648b47f8e003d -> trunk/0d17029fea3d96bb88b19912946648b47f8e003d 2025-07-17T07:01:09.4021533Z * [new tag] trunk/0d3d84d866040fad1b21a618c44802951a3cb15e -> trunk/0d3d84d866040fad1b21a618c44802951a3cb15e 2025-07-17T07:01:09.4022464Z * [new tag] trunk/0d77364ee3ff6435aa93df3b0303db66b5fc3254 -> trunk/0d77364ee3ff6435aa93df3b0303db66b5fc3254 2025-07-17T07:01:09.4023232Z * [new tag] trunk/0d8c029584b61da059b6225537764eadd2fa1223 -> trunk/0d8c029584b61da059b6225537764eadd2fa1223 2025-07-17T07:01:09.4024110Z * [new tag] trunk/0d8e4e2327137b370d91bd23931cd7691a95cc33 -> trunk/0d8e4e2327137b370d91bd23931cd7691a95cc33 2025-07-17T07:01:09.4024973Z * [new tag] trunk/0db3e0cf29604dae1007a678603e4dffd1c57562 -> trunk/0db3e0cf29604dae1007a678603e4dffd1c57562 2025-07-17T07:01:09.4025829Z * [new tag] trunk/0decd966af9cdcb7ab4410cf475d2fc09f2dea0c -> trunk/0decd966af9cdcb7ab4410cf475d2fc09f2dea0c 2025-07-17T07:01:09.4026679Z * [new tag] trunk/0e2013a12da944930012265bd1b75d0a19af4d7c -> trunk/0e2013a12da944930012265bd1b75d0a19af4d7c 2025-07-17T07:01:09.4027545Z * [new tag] trunk/0e47312ae5a687f0aed61db753d03180118cddc4 -> trunk/0e47312ae5a687f0aed61db753d03180118cddc4 2025-07-17T07:01:09.4028405Z * [new tag] trunk/0e9d8032a3431505c8a6a341375af9cb27afd537 -> trunk/0e9d8032a3431505c8a6a341375af9cb27afd537 2025-07-17T07:01:09.4029257Z * [new tag] trunk/0edc1b91f708c7635cf0f286f43724665934dc89 -> trunk/0edc1b91f708c7635cf0f286f43724665934dc89 2025-07-17T07:01:09.4030066Z * [new tag] trunk/0f0c01071476145fca7d70c68d029a88aeefe72c -> trunk/0f0c01071476145fca7d70c68d029a88aeefe72c 2025-07-17T07:01:09.4030937Z * [new tag] trunk/0f21fa84fb605c61482e4218df89f8bb1ef70c14 -> trunk/0f21fa84fb605c61482e4218df89f8bb1ef70c14 2025-07-17T07:01:09.4031763Z * [new tag] trunk/0f31445139d7ffaeeae95a230c536ef97970af5c -> trunk/0f31445139d7ffaeeae95a230c536ef97970af5c 2025-07-17T07:01:09.4032514Z * [new tag] trunk/0f47e76937f092263dd579e71d45e3193fbbc5df -> trunk/0f47e76937f092263dd579e71d45e3193fbbc5df 2025-07-17T07:01:09.4033326Z * [new tag] trunk/0f9c1b374fbb6f3b999855b26ebb869387b33dfb -> trunk/0f9c1b374fbb6f3b999855b26ebb869387b33dfb 2025-07-17T07:01:09.4034162Z * [new tag] trunk/0fa361e4295bbd8ac8b1f1ea74852535326f08f2 -> trunk/0fa361e4295bbd8ac8b1f1ea74852535326f08f2 2025-07-17T07:01:09.4035049Z * [new tag] trunk/0fd711df19a6523c9de6c820640ae53e32de14c6 -> trunk/0fd711df19a6523c9de6c820640ae53e32de14c6 2025-07-17T07:01:09.4035825Z * [new tag] trunk/1036f6d114bc22a9b4cf620cf7f8364ea2fd7a60 -> trunk/1036f6d114bc22a9b4cf620cf7f8364ea2fd7a60 2025-07-17T07:01:09.4036880Z * [new tag] trunk/104493487852f0cc232547ecbf7bebf5c7fe5982 -> trunk/104493487852f0cc232547ecbf7bebf5c7fe5982 2025-07-17T07:01:09.4037691Z * [new tag] trunk/1051b93192710d2e4bdf5fecd8e66c61731b55e1 -> trunk/1051b93192710d2e4bdf5fecd8e66c61731b55e1 2025-07-17T07:01:09.4038625Z * [new tag] trunk/10cd1de5183e4fcd6e316be497904b9c86d4db67 -> trunk/10cd1de5183e4fcd6e316be497904b9c86d4db67 2025-07-17T07:01:09.4039575Z * [new tag] trunk/10cef1e25d39c1ff1ac93036302ce1b008cd4469 -> trunk/10cef1e25d39c1ff1ac93036302ce1b008cd4469 2025-07-17T07:01:09.4040411Z * [new tag] trunk/10d41c7d20747829a4ee5b994bf466071e4c7e32 -> trunk/10d41c7d20747829a4ee5b994bf466071e4c7e32 2025-07-17T07:01:09.4041405Z * [new tag] trunk/10fb98a004e129ea2a2074cc05e5173c056f728c -> trunk/10fb98a004e129ea2a2074cc05e5173c056f728c 2025-07-17T07:01:09.4042298Z * [new tag] trunk/110ae0f4333b289b1ee798ab93447e6ede16300f -> trunk/110ae0f4333b289b1ee798ab93447e6ede16300f 2025-07-17T07:01:09.4043092Z * [new tag] trunk/1155c53e7d8c25dabc618d7f7b324ee97c89f40e -> trunk/1155c53e7d8c25dabc618d7f7b324ee97c89f40e 2025-07-17T07:01:09.4044013Z * [new tag] trunk/117db5601d78cbc746b35eef71fc815e042e903f -> trunk/117db5601d78cbc746b35eef71fc815e042e903f 2025-07-17T07:01:09.4044778Z * [new tag] trunk/11a86ad2fa3be5cf91a7a2b99c4df44017bc92c7 -> trunk/11a86ad2fa3be5cf91a7a2b99c4df44017bc92c7 2025-07-17T07:01:09.4045727Z * [new tag] trunk/11bb1ece50ade57b963afe29b27cab6a0a56ff7d -> trunk/11bb1ece50ade57b963afe29b27cab6a0a56ff7d 2025-07-17T07:01:09.4046568Z * [new tag] trunk/11bc29856d8180571146209cea987ac9397ab444 -> trunk/11bc29856d8180571146209cea987ac9397ab444 2025-07-17T07:01:09.4047483Z * [new tag] trunk/11d6ad8b2e7359e2f654474f31692ba1aec67980 -> trunk/11d6ad8b2e7359e2f654474f31692ba1aec67980 2025-07-17T07:01:09.4048395Z * [new tag] trunk/11f7e2f1459b09b1ece26ea785b6be77daa36923 -> trunk/11f7e2f1459b09b1ece26ea785b6be77daa36923 2025-07-17T07:01:09.4049339Z * [new tag] trunk/12151c96d9202875638ea2c695d5647c38368c46 -> trunk/12151c96d9202875638ea2c695d5647c38368c46 2025-07-17T07:01:09.4050194Z * [new tag] trunk/127695eb5c973f9fdba24c47b465e30a19292582 -> trunk/127695eb5c973f9fdba24c47b465e30a19292582 2025-07-17T07:01:09.4051456Z * [new tag] trunk/12b02137af5cd6743adfe5a0ffe0d9b453cd013e -> trunk/12b02137af5cd6743adfe5a0ffe0d9b453cd013e 2025-07-17T07:01:09.4052222Z * [new tag] trunk/12cb06e574738a15a59ee9384493682fb5bc6d2b -> trunk/12cb06e574738a15a59ee9384493682fb5bc6d2b 2025-07-17T07:01:09.4053566Z * [new tag] trunk/12f9942b107acc9d7acf9591818c826ef972a0f5 -> trunk/12f9942b107acc9d7acf9591818c826ef972a0f5 2025-07-17T07:01:09.4054419Z * [new tag] trunk/130d4973bd036e539e995dd0bc20080c2570b6da -> trunk/130d4973bd036e539e995dd0bc20080c2570b6da 2025-07-17T07:01:09.4055358Z * [new tag] trunk/132babe7e0b668d31e6efdf339687d48b2ccedc7 -> trunk/132babe7e0b668d31e6efdf339687d48b2ccedc7 2025-07-17T07:01:09.4056235Z * [new tag] trunk/1339e88105cf72586d728d4f7e0d71b81e08d933 -> trunk/1339e88105cf72586d728d4f7e0d71b81e08d933 2025-07-17T07:01:09.4057071Z * [new tag] trunk/134dfb3fe64323d7c615e866c43ea346ad987556 -> trunk/134dfb3fe64323d7c615e866c43ea346ad987556 2025-07-17T07:01:09.4057996Z * [new tag] trunk/1393f71e0714d067ed5ec1f57f135431d20619bc -> trunk/1393f71e0714d067ed5ec1f57f135431d20619bc 2025-07-17T07:01:09.4059006Z * [new tag] trunk/13bf2655c1404aff64e05e50dd7b0ce4c8dc0fcf -> trunk/13bf2655c1404aff64e05e50dd7b0ce4c8dc0fcf 2025-07-17T07:01:09.4059979Z * [new tag] trunk/13ea0f2c0a06101d9aab9ce12c30043be7c92d38 -> trunk/13ea0f2c0a06101d9aab9ce12c30043be7c92d38 2025-07-17T07:01:09.4060819Z * [new tag] trunk/13efb2c858c41141776ad42f7c44f1709948de71 -> trunk/13efb2c858c41141776ad42f7c44f1709948de71 2025-07-17T07:01:09.4061782Z * [new tag] trunk/144965ca9af478515736665b0577cded22fa692e -> trunk/144965ca9af478515736665b0577cded22fa692e 2025-07-17T07:01:09.4062568Z * [new tag] trunk/14ecc0336185f2ca5591858bc74cd4aadf2d1161 -> trunk/14ecc0336185f2ca5591858bc74cd4aadf2d1161 2025-07-17T07:01:09.4063508Z * [new tag] trunk/14f3639e09d692e53c9b9714776e3ca48fed7c4c -> trunk/14f3639e09d692e53c9b9714776e3ca48fed7c4c 2025-07-17T07:01:09.4064447Z * [new tag] trunk/154a39bfbd6e0cc6b7e6f3bce708ab0157ce1c50 -> trunk/154a39bfbd6e0cc6b7e6f3bce708ab0157ce1c50 2025-07-17T07:01:09.4065274Z * [new tag] trunk/156a377f4cf9b5b5255575e26d27f745c111a6ae -> trunk/156a377f4cf9b5b5255575e26d27f745c111a6ae 2025-07-17T07:01:09.4066232Z * [new tag] trunk/156b28e62a225214a5685088a848c5efe6a4b95e -> trunk/156b28e62a225214a5685088a848c5efe6a4b95e 2025-07-17T07:01:09.4067248Z * [new tag] trunk/156bc243f0edbf79d4a24d5affb48198551b58dd -> trunk/156bc243f0edbf79d4a24d5affb48198551b58dd 2025-07-17T07:01:09.4068180Z * [new tag] trunk/157683d8623a683a7e05755176f86a41c7bf518a -> trunk/157683d8623a683a7e05755176f86a41c7bf518a 2025-07-17T07:01:09.4069013Z * [new tag] trunk/1586521461c8dc642735466fc143b7d366a858d0 -> trunk/1586521461c8dc642735466fc143b7d366a858d0 2025-07-17T07:01:09.4070086Z * [new tag] trunk/159a39ad344cca84347e7b3be653ec13834cefdc -> trunk/159a39ad344cca84347e7b3be653ec13834cefdc 2025-07-17T07:01:09.4071012Z * [new tag] trunk/162ca185ff06fc7440e9f52d249e0b465976449a -> trunk/162ca185ff06fc7440e9f52d249e0b465976449a 2025-07-17T07:01:09.4071950Z * [new tag] trunk/163f0d8f2ab0a602a16f606db6d873298088e3a7 -> trunk/163f0d8f2ab0a602a16f606db6d873298088e3a7 2025-07-17T07:01:09.4073046Z * [new tag] trunk/16c3b4143b6fdabbee45ea5a64bb922a5969145a -> trunk/16c3b4143b6fdabbee45ea5a64bb922a5969145a 2025-07-17T07:01:09.4073880Z * [new tag] trunk/172853547ac842bb5ed8bf6e07702c76ff2cf043 -> trunk/172853547ac842bb5ed8bf6e07702c76ff2cf043 2025-07-17T07:01:09.4074798Z * [new tag] trunk/178fe7aa98987111a73534375099f4ad255e8b59 -> trunk/178fe7aa98987111a73534375099f4ad255e8b59 2025-07-17T07:01:09.4075676Z * [new tag] trunk/179dcc10e4e0c742fb7d93b832021d0c177798bf -> trunk/179dcc10e4e0c742fb7d93b832021d0c177798bf 2025-07-17T07:01:09.4076613Z * [new tag] trunk/17b38b850e5362c2f5d7cd75e6552e3d149232f2 -> trunk/17b38b850e5362c2f5d7cd75e6552e3d149232f2 2025-07-17T07:01:09.4077549Z * [new tag] trunk/17eb649d5596c52bae65a069e03b4550155ad57f -> trunk/17eb649d5596c52bae65a069e03b4550155ad57f 2025-07-17T07:01:09.4078463Z * [new tag] trunk/1839e8d04b81ee6eda0cff6fbfc218a7a600f6f7 -> trunk/1839e8d04b81ee6eda0cff6fbfc218a7a600f6f7 2025-07-17T07:01:09.4089914Z * [new tag] trunk/1851f50866a11e7ddede5d07c583e2c5407e7708 -> trunk/1851f50866a11e7ddede5d07c583e2c5407e7708 2025-07-17T07:01:09.4090967Z * [new tag] trunk/187828dcb4145cdfda916ff670207bfb17abdef8 -> trunk/187828dcb4145cdfda916ff670207bfb17abdef8 2025-07-17T07:01:09.4091767Z * [new tag] trunk/18b01afa9ed1dbc696a06de1b69bf5c021c18c10 -> trunk/18b01afa9ed1dbc696a06de1b69bf5c021c18c10 2025-07-17T07:01:09.4092718Z * [new tag] trunk/18bf6addc4741852953ac0b8d555411c347e67aa -> trunk/18bf6addc4741852953ac0b8d555411c347e67aa 2025-07-17T07:01:09.4093184Z * [new tag] trunk/18e4c461fb4e2bbdef889c3b1a2cdb29c0fb31cd -> trunk/18e4c461fb4e2bbdef889c3b1a2cdb29c0fb31cd 2025-07-17T07:01:09.4093582Z * [new tag] trunk/190f76fa313410df8dbb4111c586a516bf55515c -> trunk/190f76fa313410df8dbb4111c586a516bf55515c 2025-07-17T07:01:09.4094013Z * [new tag] trunk/1913c915e0d2b08e7af00889dc50e78d0a9b9198 -> trunk/1913c915e0d2b08e7af00889dc50e78d0a9b9198 2025-07-17T07:01:09.4094455Z * [new tag] trunk/191693ac854de1bb5fcf4280b7a93ab29cc12b5c -> trunk/191693ac854de1bb5fcf4280b7a93ab29cc12b5c 2025-07-17T07:01:09.4094897Z * [new tag] trunk/194539e9c33dc793fe67fbb68c7cee12f399e276 -> trunk/194539e9c33dc793fe67fbb68c7cee12f399e276 2025-07-17T07:01:09.4095286Z * [new tag] trunk/194c221e0abc9daf178e14ca2608c5d6804a3eb7 -> trunk/194c221e0abc9daf178e14ca2608c5d6804a3eb7 2025-07-17T07:01:09.4095731Z * [new tag] trunk/195ef1bce8f17419139fb81406b91f476eba7257 -> trunk/195ef1bce8f17419139fb81406b91f476eba7257 2025-07-17T07:01:09.4096108Z * [new tag] trunk/19625daf889f0a6192a76e200205817e3ee27f26 -> trunk/19625daf889f0a6192a76e200205817e3ee27f26 2025-07-17T07:01:09.4096486Z * [new tag] trunk/196c95d463367f15999c0cddc9eb89031e9988ab -> trunk/196c95d463367f15999c0cddc9eb89031e9988ab 2025-07-17T07:01:09.4097017Z * [new tag] trunk/197c1869f5467b4cfa1e197bbe394be82ba40554 -> trunk/197c1869f5467b4cfa1e197bbe394be82ba40554 2025-07-17T07:01:09.4097418Z * [new tag] trunk/1982ec2d22c5145e4ffeec08064c5ca17e969c25 -> trunk/1982ec2d22c5145e4ffeec08064c5ca17e969c25 2025-07-17T07:01:09.4097836Z * [new tag] trunk/19a01382bc623cf30cdfa7215e47a6b69d8598ff -> trunk/19a01382bc623cf30cdfa7215e47a6b69d8598ff 2025-07-17T07:01:09.4098260Z * [new tag] trunk/19ae5afdaa3a59135e6adbaea197b7a2456f1865 -> trunk/19ae5afdaa3a59135e6adbaea197b7a2456f1865 2025-07-17T07:01:09.4098665Z * [new tag] trunk/19f851ce10b16f0ed11d18d937ca7b32746153b0 -> trunk/19f851ce10b16f0ed11d18d937ca7b32746153b0 2025-07-17T07:01:09.4099090Z * [new tag] trunk/19ffb5e6f7606436249742b0f3efc0bab244dc55 -> trunk/19ffb5e6f7606436249742b0f3efc0bab244dc55 2025-07-17T07:01:09.4099498Z * [new tag] trunk/19ffdf4ea053bc5befe7eaa737fd1fafaaeb34a2 -> trunk/19ffdf4ea053bc5befe7eaa737fd1fafaaeb34a2 2025-07-17T07:01:09.4099949Z * [new tag] trunk/1a195bf7d6155b027f7ca81a97d71a3af34ce11e -> trunk/1a195bf7d6155b027f7ca81a97d71a3af34ce11e 2025-07-17T07:01:09.4100335Z * [new tag] trunk/1a568f4e5d1c0e2e8994d64f01e1e8a3104a1a48 -> trunk/1a568f4e5d1c0e2e8994d64f01e1e8a3104a1a48 2025-07-17T07:01:09.4100747Z * [new tag] trunk/1b032384b186154bb140c7368e2e700cb1419b86 -> trunk/1b032384b186154bb140c7368e2e700cb1419b86 2025-07-17T07:01:09.4101153Z * [new tag] trunk/1b389025ba0cc640e07991314bfba8b6ca385bd2 -> trunk/1b389025ba0cc640e07991314bfba8b6ca385bd2 2025-07-17T07:01:09.4102074Z * [new tag] trunk/1b3d69b59f92383633731aada8383ab88da3ed60 -> trunk/1b3d69b59f92383633731aada8383ab88da3ed60 2025-07-17T07:01:09.4102940Z * [new tag] trunk/1b50c12584909bda00009f4f0fd0d38ec792d019 -> trunk/1b50c12584909bda00009f4f0fd0d38ec792d019 2025-07-17T07:01:09.4103951Z * [new tag] trunk/1b58e7adab91fe20bbfb1568403d72869317e75c -> trunk/1b58e7adab91fe20bbfb1568403d72869317e75c 2025-07-17T07:01:09.4104861Z * [new tag] trunk/1b6772a90f5c334cab7b9d055a7f819ce4c3478c -> trunk/1b6772a90f5c334cab7b9d055a7f819ce4c3478c 2025-07-17T07:01:09.4105802Z * [new tag] trunk/1bb9b1858b84ee07ff1bc33157d4ea7a980bb6b5 -> trunk/1bb9b1858b84ee07ff1bc33157d4ea7a980bb6b5 2025-07-17T07:01:09.4106705Z * [new tag] trunk/1c6057fd179b0373686a790b0a0b7fc68fe7f27d -> trunk/1c6057fd179b0373686a790b0a0b7fc68fe7f27d 2025-07-17T07:01:09.4107659Z * [new tag] trunk/1c8844d9e7b2d72fb80b67ed51df4f6a1295b3b5 -> trunk/1c8844d9e7b2d72fb80b67ed51df4f6a1295b3b5 2025-07-17T07:01:09.4108576Z * [new tag] trunk/1c960c5638b6f20f7a1cbe1e9036c14a4845a195 -> trunk/1c960c5638b6f20f7a1cbe1e9036c14a4845a195 2025-07-17T07:01:09.4109480Z * [new tag] trunk/1cb0597a890bc50b8ed3937d6bdf5a734691bd91 -> trunk/1cb0597a890bc50b8ed3937d6bdf5a734691bd91 2025-07-17T07:01:09.4110289Z * [new tag] trunk/1cc62c2cb91e56ae50494f88f369cd6ec466a118 -> trunk/1cc62c2cb91e56ae50494f88f369cd6ec466a118 2025-07-17T07:01:09.4111161Z * [new tag] trunk/1ccc57e4288e231210c9b2c29943b2752259bf44 -> trunk/1ccc57e4288e231210c9b2c29943b2752259bf44 2025-07-17T07:01:09.4112091Z * [new tag] trunk/1cce73b5f4806f266fbbcf3383057af5f2e3a0aa -> trunk/1cce73b5f4806f266fbbcf3383057af5f2e3a0aa 2025-07-17T07:01:09.4113859Z * [new tag] trunk/1cfdcb975a3b0c685c34c6ae0e378b9bc92e0050 -> trunk/1cfdcb975a3b0c685c34c6ae0e378b9bc92e0050 2025-07-17T07:01:09.4114659Z * [new tag] trunk/1d0f45d5d15389b83312b6942ac2017c8d7ebedc -> trunk/1d0f45d5d15389b83312b6942ac2017c8d7ebedc 2025-07-17T07:01:09.4115582Z * [new tag] trunk/1d584761622ff6e5519c5e3dbbb62a21b89ffe8a -> trunk/1d584761622ff6e5519c5e3dbbb62a21b89ffe8a 2025-07-17T07:01:09.4116543Z * [new tag] trunk/1d993fa3092e4f0b5745f2470024b35cac96da14 -> trunk/1d993fa3092e4f0b5745f2470024b35cac96da14 2025-07-17T07:01:09.4117440Z * [new tag] trunk/1dc1eedd4369f6e6bb79d5315e3ffc1bdc59b709 -> trunk/1dc1eedd4369f6e6bb79d5315e3ffc1bdc59b709 2025-07-17T07:01:09.4118363Z * [new tag] trunk/1dd0b1d12ba48d7879a57391cab6213742dcadb6 -> trunk/1dd0b1d12ba48d7879a57391cab6213742dcadb6 2025-07-17T07:01:09.4119327Z * [new tag] trunk/1e373d02d57ff65c70febc4ec427bf6d1708483e -> trunk/1e373d02d57ff65c70febc4ec427bf6d1708483e 2025-07-17T07:01:09.4120272Z * [new tag] trunk/1e474cc9c8ddab22ed314ad8be641002b0161498 -> trunk/1e474cc9c8ddab22ed314ad8be641002b0161498 2025-07-17T07:01:09.4121167Z * [new tag] trunk/1e4c5b666afe6434cbe3b830aaf70864074d40f5 -> trunk/1e4c5b666afe6434cbe3b830aaf70864074d40f5 2025-07-17T07:01:09.4122082Z * [new tag] trunk/1e4d8b5a4a67220473bf0027c58baaa08a036714 -> trunk/1e4d8b5a4a67220473bf0027c58baaa08a036714 2025-07-17T07:01:09.4122986Z * [new tag] trunk/1e690b6c41677bf1fe3147e3fc011eb9805365f5 -> trunk/1e690b6c41677bf1fe3147e3fc011eb9805365f5 2025-07-17T07:01:09.4123928Z * [new tag] trunk/1e6a653234c299ccecf702233a1eeb7455b1ce77 -> trunk/1e6a653234c299ccecf702233a1eeb7455b1ce77 2025-07-17T07:01:09.4124663Z * [new tag] trunk/1e7e21ec5dd6ea28b27c57fe92bcf31ea5983913 -> trunk/1e7e21ec5dd6ea28b27c57fe92bcf31ea5983913 2025-07-17T07:01:09.4125517Z * [new tag] trunk/1e8e9f745e43fa38bbfc7b67b30bc66c0e7ebbd6 -> trunk/1e8e9f745e43fa38bbfc7b67b30bc66c0e7ebbd6 2025-07-17T07:01:09.4126604Z * [new tag] trunk/1ea9cde598ead20194dbb6c5cb26e74e36e6ad55 -> trunk/1ea9cde598ead20194dbb6c5cb26e74e36e6ad55 2025-07-17T07:01:09.4127512Z * [new tag] trunk/1ed243f01c8efb329055c6124ba0aa5f48747cfe -> trunk/1ed243f01c8efb329055c6124ba0aa5f48747cfe 2025-07-17T07:01:09.4128475Z * [new tag] trunk/1eea2c4fe35ffbdcbfccbeb7ac6c3ec02137385d -> trunk/1eea2c4fe35ffbdcbfccbeb7ac6c3ec02137385d 2025-07-17T07:01:09.4129448Z * [new tag] trunk/1f0eb79e3e91f09f99b53aa4d331eb47a1f66101 -> trunk/1f0eb79e3e91f09f99b53aa4d331eb47a1f66101 2025-07-17T07:01:09.4130245Z * [new tag] trunk/1f1f22991dcca01ed27fad44c21f0827d47bdd6b -> trunk/1f1f22991dcca01ed27fad44c21f0827d47bdd6b 2025-07-17T07:01:09.4131182Z * [new tag] trunk/1f3cc4875cb9d9b579a41b6699f97820c16c3868 -> trunk/1f3cc4875cb9d9b579a41b6699f97820c16c3868 2025-07-17T07:01:09.4131969Z * [new tag] trunk/1f57e0e04da9d334e238cec346f7ae3667bed9d1 -> trunk/1f57e0e04da9d334e238cec346f7ae3667bed9d1 2025-07-17T07:01:09.4133135Z * [new tag] trunk/1fff6356d9f99ec2980052c498dc0b70d513bc6d -> trunk/1fff6356d9f99ec2980052c498dc0b70d513bc6d 2025-07-17T07:01:09.4133969Z * [new tag] trunk/2002e3a311968d18afd0fa5d195943676f134fa2 -> trunk/2002e3a311968d18afd0fa5d195943676f134fa2 2025-07-17T07:01:09.4134901Z * [new tag] trunk/2022588295295fa1fdee7a500adad3bd0c28b9d6 -> trunk/2022588295295fa1fdee7a500adad3bd0c28b9d6 2025-07-17T07:01:09.4135820Z * [new tag] trunk/202d2ae53a493700da813ed7d6055c0b62c7fc6c -> trunk/202d2ae53a493700da813ed7d6055c0b62c7fc6c 2025-07-17T07:01:09.4136806Z * [new tag] trunk/204db27a0c4478c36dbb15fa2d4caed783a90265 -> trunk/204db27a0c4478c36dbb15fa2d4caed783a90265 2025-07-17T07:01:09.4137792Z * [new tag] trunk/205241a0d5149d05e44dc113dc0273e8eceff9f0 -> trunk/205241a0d5149d05e44dc113dc0273e8eceff9f0 2025-07-17T07:01:09.4138642Z * [new tag] trunk/208ec60e72a63f366c757a5bc895089ceb323fcc -> trunk/208ec60e72a63f366c757a5bc895089ceb323fcc 2025-07-17T07:01:09.4139585Z * [new tag] trunk/20a74c370b8427cce369b1abf0c470344d01dc8e -> trunk/20a74c370b8427cce369b1abf0c470344d01dc8e 2025-07-17T07:01:09.4140466Z * [new tag] trunk/20e40492b046b9287726d3ec656117e4dc38f0e2 -> trunk/20e40492b046b9287726d3ec656117e4dc38f0e2 2025-07-17T07:01:09.4141412Z * [new tag] trunk/210632fae1aa2cd994645a70836ff6c602e1beb9 -> trunk/210632fae1aa2cd994645a70836ff6c602e1beb9 2025-07-17T07:01:09.4142227Z * [new tag] trunk/212575f994abbc362da2517510c49f7a34e0a838 -> trunk/212575f994abbc362da2517510c49f7a34e0a838 2025-07-17T07:01:09.4143126Z * [new tag] trunk/214e2959dcdbf91a999d5c0a5d40c91e4442e8c5 -> trunk/214e2959dcdbf91a999d5c0a5d40c91e4442e8c5 2025-07-17T07:01:09.4144005Z * [new tag] trunk/2161be849702330509b452fefc2e103d3be54cd4 -> trunk/2161be849702330509b452fefc2e103d3be54cd4 2025-07-17T07:01:09.4144907Z * [new tag] trunk/216bd6091ec52865052282eced7e6d5d2a4b4fb4 -> trunk/216bd6091ec52865052282eced7e6d5d2a4b4fb4 2025-07-17T07:01:09.4145826Z * [new tag] trunk/2179afd7149c117dace9e552419082094b10a386 -> trunk/2179afd7149c117dace9e552419082094b10a386 2025-07-17T07:01:09.4146698Z * [new tag] trunk/21990fbad97acec769f737b450033774c7be8737 -> trunk/21990fbad97acec769f737b450033774c7be8737 2025-07-17T07:01:09.4147593Z * [new tag] trunk/21b5dc7a6aadb5da6c3f5be61f6204719dae00ca -> trunk/21b5dc7a6aadb5da6c3f5be61f6204719dae00ca 2025-07-17T07:01:09.4148494Z * [new tag] trunk/22edb457c9bf13e0d66631dff4f4ace5c38e0f3b -> trunk/22edb457c9bf13e0d66631dff4f4ace5c38e0f3b 2025-07-17T07:01:09.4149443Z * [new tag] trunk/22f3347fd9482bdf1006c9aa92353b739b7e868b -> trunk/22f3347fd9482bdf1006c9aa92353b739b7e868b 2025-07-17T07:01:09.4150545Z * [new tag] trunk/231eb9902ba78a4ef70203243058f3c7c0ced15d -> trunk/231eb9902ba78a4ef70203243058f3c7c0ced15d 2025-07-17T07:01:09.4151350Z * [new tag] trunk/23491519d288dedb2a54cfad5fef7fcb2ad8eade -> trunk/23491519d288dedb2a54cfad5fef7fcb2ad8eade 2025-07-17T07:01:09.4152229Z * [new tag] trunk/2380115f9738f97cf706affefd647d2cb6dfbb3f -> trunk/2380115f9738f97cf706affefd647d2cb6dfbb3f 2025-07-17T07:01:09.4153170Z * [new tag] trunk/24063ad10994e728087b3958cae9cc27dd376630 -> trunk/24063ad10994e728087b3958cae9cc27dd376630 2025-07-17T07:01:09.4154064Z * [new tag] trunk/242eb19c8383b4b197963a8a564475d52c85ac66 -> trunk/242eb19c8383b4b197963a8a564475d52c85ac66 2025-07-17T07:01:09.4155286Z * [new tag] trunk/243b12e5657a516d6e7b1a0a3f55851ce99bd4cb -> trunk/243b12e5657a516d6e7b1a0a3f55851ce99bd4cb 2025-07-17T07:01:09.4156133Z * [new tag] trunk/247113e03e3fc3e933138b52f856f33a8be33071 -> trunk/247113e03e3fc3e933138b52f856f33a8be33071 2025-07-17T07:01:09.4157185Z * [new tag] trunk/2471cc33550fc00164e2759b1d9928960e9cfaf6 -> trunk/2471cc33550fc00164e2759b1d9928960e9cfaf6 2025-07-17T07:01:09.4158267Z * [new tag] trunk/247f83e0a475bc7eea97c76719f8b5ffa87edced -> trunk/247f83e0a475bc7eea97c76719f8b5ffa87edced 2025-07-17T07:01:09.4159166Z * [new tag] trunk/2481c4b2ea5db7a6d6f60f5d27426000c2779dc8 -> trunk/2481c4b2ea5db7a6d6f60f5d27426000c2779dc8 2025-07-17T07:01:09.4160046Z * [new tag] trunk/24b49b98810bb77f3cfa4c15baa9a15c9be3db61 -> trunk/24b49b98810bb77f3cfa4c15baa9a15c9be3db61 2025-07-17T07:01:09.4160964Z * [new tag] trunk/250ae2531c55dcc50f558ec739941324e3f9a4d4 -> trunk/250ae2531c55dcc50f558ec739941324e3f9a4d4 2025-07-17T07:01:09.4161874Z * [new tag] trunk/25717da8c869a06befed60bc1a0e3dcdac7fd7d9 -> trunk/25717da8c869a06befed60bc1a0e3dcdac7fd7d9 2025-07-17T07:01:09.4162770Z * [new tag] trunk/2578796e235d1d878272084253bee3e2cc02a5b1 -> trunk/2578796e235d1d878272084253bee3e2cc02a5b1 2025-07-17T07:01:09.4163634Z * [new tag] trunk/2585960b47d6429a119665216123cb00435efde9 -> trunk/2585960b47d6429a119665216123cb00435efde9 2025-07-17T07:01:09.4164478Z * [new tag] trunk/2596e3d0617852469241be8777cf46db5c83928c -> trunk/2596e3d0617852469241be8777cf46db5c83928c 2025-07-17T07:01:09.4165568Z * [new tag] trunk/2620361d19f9c4bf37a71c8477823d605191c93a -> trunk/2620361d19f9c4bf37a71c8477823d605191c93a 2025-07-17T07:01:09.4166389Z * [new tag] trunk/2625c70aecc6eced1dbe108279feab7509733bef -> trunk/2625c70aecc6eced1dbe108279feab7509733bef 2025-07-17T07:01:09.4167322Z * [new tag] trunk/262654ee518eb314678f53baf4e133e4767eca3d -> trunk/262654ee518eb314678f53baf4e133e4767eca3d 2025-07-17T07:01:09.4168272Z * [new tag] trunk/26807dcf277feb2d99ab88d7b6da526488baea93 -> trunk/26807dcf277feb2d99ab88d7b6da526488baea93 2025-07-17T07:01:09.4169206Z * [new tag] trunk/26f066bb614c2ee5c0eff598c97855b1df011ef8 -> trunk/26f066bb614c2ee5c0eff598c97855b1df011ef8 2025-07-17T07:01:09.4170292Z * [new tag] trunk/26f7ca39724ff43b7b1e22190feeea67d2212f2d -> trunk/26f7ca39724ff43b7b1e22190feeea67d2212f2d 2025-07-17T07:01:09.4171380Z * [new tag] trunk/271ca679a8a0e40f1ecca49db76b5f8d6a9713d6 -> trunk/271ca679a8a0e40f1ecca49db76b5f8d6a9713d6 2025-07-17T07:01:09.4172078Z * [new tag] trunk/276c790010b015b79a7ca110e28f8e2111cfdb79 -> trunk/276c790010b015b79a7ca110e28f8e2111cfdb79 2025-07-17T07:01:09.4173518Z * [new tag] trunk/2796f31b5e3c90268365e961e2374df3ea93ff53 -> trunk/2796f31b5e3c90268365e961e2374df3ea93ff53 2025-07-17T07:01:09.4174331Z * [new tag] trunk/279cae52e750d5b4e0b49f3f1abca6c2027dd063 -> trunk/279cae52e750d5b4e0b49f3f1abca6c2027dd063 2025-07-17T07:01:09.4175450Z * [new tag] trunk/27c50799c1ca156166bf49ce72a5e97097a44d7d -> trunk/27c50799c1ca156166bf49ce72a5e97097a44d7d 2025-07-17T07:01:09.4176290Z * [new tag] trunk/27df0c56b7c6b75a5f77f5714aeef2ef8f1faa2c -> trunk/27df0c56b7c6b75a5f77f5714aeef2ef8f1faa2c 2025-07-17T07:01:09.4177185Z * [new tag] trunk/2815ade9a80e1f557370e86500b21cbc465a8ffe -> trunk/2815ade9a80e1f557370e86500b21cbc465a8ffe 2025-07-17T07:01:09.4178301Z * [new tag] trunk/2815eea0d0e02eaa0243fa8d1b9d8935b13b3aa5 -> trunk/2815eea0d0e02eaa0243fa8d1b9d8935b13b3aa5 2025-07-17T07:01:09.4179185Z * [new tag] trunk/2860f5c4f5328224ab7998bc90b9fb395b5b068b -> trunk/2860f5c4f5328224ab7998bc90b9fb395b5b068b 2025-07-17T07:01:09.4180132Z * [new tag] trunk/28796f71d04302029290f473a286efc2aba339c2 -> trunk/28796f71d04302029290f473a286efc2aba339c2 2025-07-17T07:01:09.4180928Z * [new tag] trunk/28aae93f24556c6aa8c972c0479b01b908b67fbe -> trunk/28aae93f24556c6aa8c972c0479b01b908b67fbe 2025-07-17T07:01:09.4181974Z * [new tag] trunk/2903e5ad3c4304b90daa6e5ed44a379225571b3a -> trunk/2903e5ad3c4304b90daa6e5ed44a379225571b3a 2025-07-17T07:01:09.4182862Z * [new tag] trunk/2908c10259bac21b00e9b36318e364801e0ae910 -> trunk/2908c10259bac21b00e9b36318e364801e0ae910 2025-07-17T07:01:09.4183934Z * [new tag] trunk/29391c7cf927857123108fa5e9dae6ed3db489f1 -> trunk/29391c7cf927857123108fa5e9dae6ed3db489f1 2025-07-17T07:01:09.4184798Z * [new tag] trunk/297805fd8f59b76a28048a79e8bced2616ed8713 -> trunk/297805fd8f59b76a28048a79e8bced2616ed8713 2025-07-17T07:01:09.4185736Z * [new tag] trunk/297daa1d30c80826b939d8f2dcd07422dec72642 -> trunk/297daa1d30c80826b939d8f2dcd07422dec72642 2025-07-17T07:01:09.4186993Z * [new tag] trunk/29867b211ab74355a0e03bdc9e204d89668c291a -> trunk/29867b211ab74355a0e03bdc9e204d89668c291a 2025-07-17T07:01:09.4187862Z * [new tag] trunk/29e6033ff38f0deb8dde1146a1612e64ed00e3b7 -> trunk/29e6033ff38f0deb8dde1146a1612e64ed00e3b7 2025-07-17T07:01:09.4188954Z * [new tag] trunk/29f76ec0f3eccf619a0aee03e3abbd4914a1b4b2 -> trunk/29f76ec0f3eccf619a0aee03e3abbd4914a1b4b2 2025-07-17T07:01:09.4189867Z * [new tag] trunk/2a3b41cbd077b229bbdd59f6f068c9b643a78b0b -> trunk/2a3b41cbd077b229bbdd59f6f068c9b643a78b0b 2025-07-17T07:01:09.4190822Z * [new tag] trunk/2a4e357192a2b01c9acaeb2168349e5396c9192a -> trunk/2a4e357192a2b01c9acaeb2168349e5396c9192a 2025-07-17T07:01:09.4191828Z * [new tag] trunk/2a8795a981c02f57a57f8699d0e85e42c53b6117 -> trunk/2a8795a981c02f57a57f8699d0e85e42c53b6117 2025-07-17T07:01:09.4192665Z * [new tag] trunk/2aade5ee9fafe52aef4e60624e6c950bc25f8a3e -> trunk/2aade5ee9fafe52aef4e60624e6c950bc25f8a3e 2025-07-17T07:01:09.4193549Z * [new tag] trunk/2ad5c25cfc603c3656e6699d6137419dbb009495 -> trunk/2ad5c25cfc603c3656e6699d6137419dbb009495 2025-07-17T07:01:09.4194421Z * [new tag] trunk/2af7c67e48cad59d648a3e85501f74eade5a3268 -> trunk/2af7c67e48cad59d648a3e85501f74eade5a3268 2025-07-17T07:01:09.4195387Z * [new tag] trunk/2b0f9b1f6172a0d5817c7ac7406200897311da5f -> trunk/2b0f9b1f6172a0d5817c7ac7406200897311da5f 2025-07-17T07:01:09.4196337Z * [new tag] trunk/2b19d85d70ecf1b7121e6d35f2adff06e1eb2e06 -> trunk/2b19d85d70ecf1b7121e6d35f2adff06e1eb2e06 2025-07-17T07:01:09.4197291Z * [new tag] trunk/2b9d638e3333e6e9ae324e1486774e83292e1883 -> trunk/2b9d638e3333e6e9ae324e1486774e83292e1883 2025-07-17T07:01:09.4198134Z * [new tag] trunk/2ba930d4ce04f417195f3061e55479a1a8b16b9d -> trunk/2ba930d4ce04f417195f3061e55479a1a8b16b9d 2025-07-17T07:01:09.4199075Z * [new tag] trunk/2bb33e7a08c4710024b3cb249a13cd2f5d0f6473 -> trunk/2bb33e7a08c4710024b3cb249a13cd2f5d0f6473 2025-07-17T07:01:09.4199982Z * [new tag] trunk/2c0d94a7debe83e96a821548a6e0cb18a0f5cfc3 -> trunk/2c0d94a7debe83e96a821548a6e0cb18a0f5cfc3 2025-07-17T07:01:09.4201085Z * [new tag] trunk/2c1a93a0ae7ebd7963a5931d7b34c885d57844d9 -> trunk/2c1a93a0ae7ebd7963a5931d7b34c885d57844d9 2025-07-17T07:01:09.4201920Z * [new tag] trunk/2c6324a1ebf3e3f6a12be6d18fc0bcdbe00f2a0a -> trunk/2c6324a1ebf3e3f6a12be6d18fc0bcdbe00f2a0a 2025-07-17T07:01:09.4202814Z * [new tag] trunk/2c68c3e8d5e9a235f5861be6486de4959f80c840 -> trunk/2c68c3e8d5e9a235f5861be6486de4959f80c840 2025-07-17T07:01:09.4203788Z * [new tag] trunk/2c76f31221e117b217b8a6a96a5405f626d2218a -> trunk/2c76f31221e117b217b8a6a96a5405f626d2218a 2025-07-17T07:01:09.4204636Z * [new tag] trunk/2cdcd16e836a144f36996104b1340b03041eb07a -> trunk/2cdcd16e836a144f36996104b1340b03041eb07a 2025-07-17T07:01:09.4205582Z * [new tag] trunk/2d3615f577894c7a117a55e85bb8371bb598ec50 -> trunk/2d3615f577894c7a117a55e85bb8371bb598ec50 2025-07-17T07:01:09.4206391Z * [new tag] trunk/2d39a48d524021995269411bd49fe792e59d9f94 -> trunk/2d39a48d524021995269411bd49fe792e59d9f94 2025-07-17T07:01:09.4207311Z * [new tag] trunk/2d7e6c6241971106a56073d7a53c7d1336b11a51 -> trunk/2d7e6c6241971106a56073d7a53c7d1336b11a51 2025-07-17T07:01:09.4208183Z * [new tag] trunk/2d832c9587fd99db295b62d0c9b459d509c19d06 -> trunk/2d832c9587fd99db295b62d0c9b459d509c19d06 2025-07-17T07:01:09.4209262Z * [new tag] trunk/2db1a54465b6121993ad7827f1327ed319c81d70 -> trunk/2db1a54465b6121993ad7827f1327ed319c81d70 2025-07-17T07:01:09.4210102Z * [new tag] trunk/2dc16274519841dc2778cba6962cb0357d1ee8dc -> trunk/2dc16274519841dc2778cba6962cb0357d1ee8dc 2025-07-17T07:01:09.4210985Z * [new tag] trunk/2e0e08588e7cb04f49ee5bbc000b18b72864dfa1 -> trunk/2e0e08588e7cb04f49ee5bbc000b18b72864dfa1 2025-07-17T07:01:09.4212135Z * [new tag] trunk/2e14069081172faf9a51bd34c1e0b85dbf39cb4b -> trunk/2e14069081172faf9a51bd34c1e0b85dbf39cb4b 2025-07-17T07:01:09.4212935Z * [new tag] trunk/2e2ea7290a1cf2da3c3efd6e6ad4836bb94beaeb -> trunk/2e2ea7290a1cf2da3c3efd6e6ad4836bb94beaeb 2025-07-17T07:01:09.4213785Z * [new tag] trunk/2e64e45b0b260e2efc2bde641ec2b3b8ed910194 -> trunk/2e64e45b0b260e2efc2bde641ec2b3b8ed910194 2025-07-17T07:01:09.4214663Z * [new tag] trunk/2e9bd03f6075b9b93b070c3770bf58f60be5508e -> trunk/2e9bd03f6075b9b93b070c3770bf58f60be5508e 2025-07-17T07:01:09.4215682Z * [new tag] trunk/2eb744c08d600e84b167dbda7daa792243a2c235 -> trunk/2eb744c08d600e84b167dbda7daa792243a2c235 2025-07-17T07:01:09.4216409Z * [new tag] trunk/2ee23175d96aa022a9c94209c14bbb7f8e064760 -> trunk/2ee23175d96aa022a9c94209c14bbb7f8e064760 2025-07-17T07:01:09.4217326Z * [new tag] trunk/2efa5eaa652f9a6505635d96178e3f119b20adf7 -> trunk/2efa5eaa652f9a6505635d96178e3f119b20adf7 2025-07-17T07:01:09.4218317Z * [new tag] trunk/2eff14c4455de22628ea599a0d4ba047a7eba6ae -> trunk/2eff14c4455de22628ea599a0d4ba047a7eba6ae 2025-07-17T07:01:09.4219282Z * [new tag] trunk/2f1c5c4131047d25f822ac278bac8c13deff4079 -> trunk/2f1c5c4131047d25f822ac278bac8c13deff4079 2025-07-17T07:01:09.4220455Z * [new tag] trunk/2f94f69b7c83370ef0cc65e3ab96bb5bf11a7b1a -> trunk/2f94f69b7c83370ef0cc65e3ab96bb5bf11a7b1a 2025-07-17T07:01:09.4221261Z * [new tag] trunk/2fde2090d001a9ae63ef41413f11897761eb4de9 -> trunk/2fde2090d001a9ae63ef41413f11897761eb4de9 2025-07-17T07:01:09.4222094Z * [new tag] trunk/2ff3280c77c705e11c5211d4be8fef9853cd0559 -> trunk/2ff3280c77c705e11c5211d4be8fef9853cd0559 2025-07-17T07:01:09.4222947Z * [new tag] trunk/3003c681ef1f8efbfa83470173c62930d195364b -> trunk/3003c681ef1f8efbfa83470173c62930d195364b 2025-07-17T07:01:09.4223864Z * [new tag] trunk/30293b8b5edca86cfc80f24874b0968620a8e72d -> trunk/30293b8b5edca86cfc80f24874b0968620a8e72d 2025-07-17T07:01:09.4225001Z * [new tag] trunk/30387ab2e485384ab2e67084a1e2c5569190ba92 -> trunk/30387ab2e485384ab2e67084a1e2c5569190ba92 2025-07-17T07:01:09.4225808Z * [new tag] trunk/3040ca6d0f8558e39919b14eebeacc34ddf980f5 -> trunk/3040ca6d0f8558e39919b14eebeacc34ddf980f5 2025-07-17T07:01:09.4226714Z * [new tag] trunk/30587195d314eb5eb02ce63f39a9be4c943629ef -> trunk/30587195d314eb5eb02ce63f39a9be4c943629ef 2025-07-17T07:01:09.4227526Z * [new tag] trunk/306dd19216b656467143483395ef582feb5d7d07 -> trunk/306dd19216b656467143483395ef582feb5d7d07 2025-07-17T07:01:09.4228444Z * [new tag] trunk/30a1cc11a47e63c4612ac862f1f2d984ab4dbf24 -> trunk/30a1cc11a47e63c4612ac862f1f2d984ab4dbf24 2025-07-17T07:01:09.4229307Z * [new tag] trunk/30d2648a4ae1585e70189e6fdca6dc9ac3d074ec -> trunk/30d2648a4ae1585e70189e6fdca6dc9ac3d074ec 2025-07-17T07:01:09.4230216Z * [new tag] trunk/30d3cf62fb813819364007e26b3eda84f7cddf3b -> trunk/30d3cf62fb813819364007e26b3eda84f7cddf3b 2025-07-17T07:01:09.4231172Z * [new tag] trunk/3106a33e410db9d1c2b0e47f9e329611d344a827 -> trunk/3106a33e410db9d1c2b0e47f9e329611d344a827 2025-07-17T07:01:09.4232079Z * [new tag] trunk/310e8361c565ca1602e719e4c812dc3931ec84d7 -> trunk/310e8361c565ca1602e719e4c812dc3931ec84d7 2025-07-17T07:01:09.4233457Z * [new tag] trunk/31326a9ad7db53e5bf4e03f8e52b75da944d0298 -> trunk/31326a9ad7db53e5bf4e03f8e52b75da944d0298 2025-07-17T07:01:09.4234305Z * [new tag] trunk/313a6a8ef94d689331b2bd8161f95c23d42eb22d -> trunk/313a6a8ef94d689331b2bd8161f95c23d42eb22d 2025-07-17T07:01:09.4235208Z * [new tag] trunk/3159ee2ad3e586573edb977c4c1745a26d9f1007 -> trunk/3159ee2ad3e586573edb977c4c1745a26d9f1007 2025-07-17T07:01:09.4236162Z * [new tag] trunk/31659964a5b546a84a4c18bb9a0828a0f63b8ccb -> trunk/31659964a5b546a84a4c18bb9a0828a0f63b8ccb 2025-07-17T07:01:09.4237088Z * [new tag] trunk/3173616532ecf0d5c0b78595d6054f1b4bd2bd75 -> trunk/3173616532ecf0d5c0b78595d6054f1b4bd2bd75 2025-07-17T07:01:09.4237941Z * [new tag] trunk/317520bf6ed5c1f2ef324f841e8ec0d8d80cb58a -> trunk/317520bf6ed5c1f2ef324f841e8ec0d8d80cb58a 2025-07-17T07:01:09.4238819Z * [new tag] trunk/317af4c87b7b8b03b8a08a4ead84d4065dd920e0 -> trunk/317af4c87b7b8b03b8a08a4ead84d4065dd920e0 2025-07-17T07:01:09.4239624Z * [new tag] trunk/31e127459789f9d97b3b35001c50e76f1b580cd5 -> trunk/31e127459789f9d97b3b35001c50e76f1b580cd5 2025-07-17T07:01:09.4240647Z * [new tag] trunk/3232b57cd87fbd15c990fbf87d181716a1993a55 -> trunk/3232b57cd87fbd15c990fbf87d181716a1993a55 2025-07-17T07:01:09.4241440Z * [new tag] trunk/326e751d07b92f788bece086227da9288206a27a -> trunk/326e751d07b92f788bece086227da9288206a27a 2025-07-17T07:01:09.4242403Z * [new tag] trunk/32983ea698842a2ca331eabb06acce9c99acb082 -> trunk/32983ea698842a2ca331eabb06acce9c99acb082 2025-07-17T07:01:09.4243542Z * [new tag] trunk/32c1611263ecc8832a8d7494480654ad851911c0 -> trunk/32c1611263ecc8832a8d7494480654ad851911c0 2025-07-17T07:01:09.4244437Z * [new tag] trunk/32eee8ed225d9f10fbbcb38c24b8b44c24c0c97c -> trunk/32eee8ed225d9f10fbbcb38c24b8b44c24c0c97c 2025-07-17T07:01:09.4245482Z * [new tag] trunk/3321acc92e24859dbe2ac6499067d1afde5622c3 -> trunk/3321acc92e24859dbe2ac6499067d1afde5622c3 2025-07-17T07:01:09.4246407Z * [new tag] trunk/333e0e61472c71cb2ad51a59cc5c56f6a47bc747 -> trunk/333e0e61472c71cb2ad51a59cc5c56f6a47bc747 2025-07-17T07:01:09.4247592Z * [new tag] trunk/3341c131b767a4036c152624c1e43baaf24cadf9 -> trunk/3341c131b767a4036c152624c1e43baaf24cadf9 2025-07-17T07:01:09.4248451Z * [new tag] trunk/336bff6d58ceb50b12d9d67764fd9f238bc0adb5 -> trunk/336bff6d58ceb50b12d9d67764fd9f238bc0adb5 2025-07-17T07:01:09.4249390Z * [new tag] trunk/336f1e2d35dfc63925754e884543491cc3f98f8c -> trunk/336f1e2d35dfc63925754e884543491cc3f98f8c 2025-07-17T07:01:09.4250310Z * [new tag] trunk/338a8c7853ab9b3e67dbcb402d30fec066bdd856 -> trunk/338a8c7853ab9b3e67dbcb402d30fec066bdd856 2025-07-17T07:01:09.4251260Z * [new tag] trunk/3404c1f0cfe4c8fd41d718d38316c24a3c0474b0 -> trunk/3404c1f0cfe4c8fd41d718d38316c24a3c0474b0 2025-07-17T07:01:09.4252158Z * [new tag] trunk/344731fb257440ab04f2d634929821be9be3fa80 -> trunk/344731fb257440ab04f2d634929821be9be3fa80 2025-07-17T07:01:09.4254340Z * [new tag] trunk/347ace4c7ac2dbb14799089c30bd01a9ac312791 -> trunk/347ace4c7ac2dbb14799089c30bd01a9ac312791 2025-07-17T07:01:09.4255163Z * [new tag] trunk/348e2a76dfe9c8a1995ab6ce4902dbeba935c984 -> trunk/348e2a76dfe9c8a1995ab6ce4902dbeba935c984 2025-07-17T07:01:09.4256046Z * [new tag] trunk/348fd45065620f20080299774f37f45233ef8f6b -> trunk/348fd45065620f20080299774f37f45233ef8f6b 2025-07-17T07:01:09.4256988Z * [new tag] trunk/3490a4f906aeaa867a390c2e97b357f17b01fcf2 -> trunk/3490a4f906aeaa867a390c2e97b357f17b01fcf2 2025-07-17T07:01:09.4257783Z * [new tag] trunk/34c8033fd3dea404db1706e264761912d095f723 -> trunk/34c8033fd3dea404db1706e264761912d095f723 2025-07-17T07:01:09.4258699Z * [new tag] trunk/34d8e64ef64d88324092a2028884c54c13e086b3 -> trunk/34d8e64ef64d88324092a2028884c54c13e086b3 2025-07-17T07:01:09.4259833Z * [new tag] trunk/35321b2ad6e86a58ca5d5be90ad8edce5945e16c -> trunk/35321b2ad6e86a58ca5d5be90ad8edce5945e16c 2025-07-17T07:01:09.4260570Z * [new tag] trunk/3580b8dde44d8bf4f229537ae9897ddd5e70f5db -> trunk/3580b8dde44d8bf4f229537ae9897ddd5e70f5db 2025-07-17T07:01:09.4261709Z * [new tag] trunk/3584e84c2434a2681b7288bcbd3bdb163c793df5 -> trunk/3584e84c2434a2681b7288bcbd3bdb163c793df5 2025-07-17T07:01:09.4262499Z * [new tag] trunk/3596c0c77f28c74e6cfb50769402ed52dbe10c67 -> trunk/3596c0c77f28c74e6cfb50769402ed52dbe10c67 2025-07-17T07:01:09.4263430Z * [new tag] trunk/359e8f5d691cdbbc54beafea25c06fc0ce321ad6 -> trunk/359e8f5d691cdbbc54beafea25c06fc0ce321ad6 2025-07-17T07:01:09.4264342Z * [new tag] trunk/35d03398e511fa0921c9db928c661dc9531ff2fc -> trunk/35d03398e511fa0921c9db928c661dc9531ff2fc 2025-07-17T07:01:09.4265212Z * [new tag] trunk/35e44067c4d9cc9be2652c0b9098885c5a321029 -> trunk/35e44067c4d9cc9be2652c0b9098885c5a321029 2025-07-17T07:01:09.4266136Z * [new tag] trunk/35e8f2593cdb72036c88a4b8d01487747204ba03 -> trunk/35e8f2593cdb72036c88a4b8d01487747204ba03 2025-07-17T07:01:09.4266983Z * [new tag] trunk/35ecd7c2d44a4e370e21ddab76b6c28266188846 -> trunk/35ecd7c2d44a4e370e21ddab76b6c28266188846 2025-07-17T07:01:09.4267873Z * [new tag] trunk/3608737347bcbb1ec1e23d85a29811abfd75c7a1 -> trunk/3608737347bcbb1ec1e23d85a29811abfd75c7a1 2025-07-17T07:01:09.4268763Z * [new tag] trunk/3644b41a7ccda62c066d525d956a08c9eac686c0 -> trunk/3644b41a7ccda62c066d525d956a08c9eac686c0 2025-07-17T07:01:09.4269676Z * [new tag] trunk/365ce465f393a6426b4ab3148da9a92445bf61d3 -> trunk/365ce465f393a6426b4ab3148da9a92445bf61d3 2025-07-17T07:01:09.4270985Z * [new tag] trunk/3684be056d9af667400ba071a116be8b1112bba8 -> trunk/3684be056d9af667400ba071a116be8b1112bba8 2025-07-17T07:01:09.4273855Z * [new tag] trunk/36a722e20d081c1a5a6df417d0f8333f6c082476 -> trunk/36a722e20d081c1a5a6df417d0f8333f6c082476 2025-07-17T07:01:09.4274689Z * [new tag] trunk/36bf81e36396c5f08eb8cab7f7858555282ca6c2 -> trunk/36bf81e36396c5f08eb8cab7f7858555282ca6c2 2025-07-17T07:01:09.4275797Z * [new tag] trunk/36dd598bdac5c665e46f05d00a38d6863a99615f -> trunk/36dd598bdac5c665e46f05d00a38d6863a99615f 2025-07-17T07:01:09.4276462Z * [new tag] trunk/36f7a027b595083f3a3761b407120b3f1f4e8634 -> trunk/36f7a027b595083f3a3761b407120b3f1f4e8634 2025-07-17T07:01:09.4277343Z * [new tag] trunk/36fd1ac9324429c095f8fbc5f6d2bd4b71f18d61 -> trunk/36fd1ac9324429c095f8fbc5f6d2bd4b71f18d61 2025-07-17T07:01:09.4278350Z * [new tag] trunk/370fc49dde9e8635957d9a910d43154085264225 -> trunk/370fc49dde9e8635957d9a910d43154085264225 2025-07-17T07:01:09.4279197Z * [new tag] trunk/376c16703c7f55a7eab9d5751bfc0e91af26a735 -> trunk/376c16703c7f55a7eab9d5751bfc0e91af26a735 2025-07-17T07:01:09.4280074Z * [new tag] trunk/378c121d5e1c8d2c24124f0c0b6cf08a1341e9d9 -> trunk/378c121d5e1c8d2c24124f0c0b6cf08a1341e9d9 2025-07-17T07:01:09.4281264Z * [new tag] trunk/37ccc532f75d8537c5b5d74b1c92a7f20df96353 -> trunk/37ccc532f75d8537c5b5d74b1c92a7f20df96353 2025-07-17T07:01:09.4282159Z * [new tag] trunk/380e30a723c1fb3530cad12ac44706412df7aa71 -> trunk/380e30a723c1fb3530cad12ac44706412df7aa71 2025-07-17T07:01:09.4283492Z * [new tag] trunk/3819584f12e2a46463a9799612ace1f59d76b9cd -> trunk/3819584f12e2a46463a9799612ace1f59d76b9cd 2025-07-17T07:01:09.4284361Z * [new tag] trunk/382598ef872b2afb9a03f8d88277a6c2edeb507f -> trunk/382598ef872b2afb9a03f8d88277a6c2edeb507f 2025-07-17T07:01:09.4285294Z * [new tag] trunk/382c6190c1329e96e71eef21a19737a3eda0040b -> trunk/382c6190c1329e96e71eef21a19737a3eda0040b 2025-07-17T07:01:09.4286193Z * [new tag] trunk/38371f693b07a485705119407da2e5dc64cec4eb -> trunk/38371f693b07a485705119407da2e5dc64cec4eb 2025-07-17T07:01:09.4287139Z * [new tag] trunk/38410cf9b57079f3360c1e79601973a01cb2588c -> trunk/38410cf9b57079f3360c1e79601973a01cb2588c 2025-07-17T07:01:09.4287946Z * [new tag] trunk/3863bbb55b38985c7d64c8a0be7beb2005a9cc07 -> trunk/3863bbb55b38985c7d64c8a0be7beb2005a9cc07 2025-07-17T07:01:09.4288969Z * [new tag] trunk/386aa7200324519ea9a8eff5eb1b3c0517756d24 -> trunk/386aa7200324519ea9a8eff5eb1b3c0517756d24 2025-07-17T07:01:09.4289856Z * [new tag] trunk/386bc9e2e990a6ac29bb90ba97b71c5b85e11080 -> trunk/386bc9e2e990a6ac29bb90ba97b71c5b85e11080 2025-07-17T07:01:09.4291006Z * [new tag] trunk/38757d94f1b3d65295b5ca2d7527ea0d582a5d3b -> trunk/38757d94f1b3d65295b5ca2d7527ea0d582a5d3b 2025-07-17T07:01:09.4291834Z * [new tag] trunk/38bfd462b8fb035de08a8c0d2b7b13eba78ee870 -> trunk/38bfd462b8fb035de08a8c0d2b7b13eba78ee870 2025-07-17T07:01:09.4293049Z * [new tag] trunk/38c4d05535f4e031a2ad5f39a4a415cc3a919cfb -> trunk/38c4d05535f4e031a2ad5f39a4a415cc3a919cfb 2025-07-17T07:01:09.4293821Z * [new tag] trunk/38e1e5d54ce42d42f8920ff46d9102800b94482d -> trunk/38e1e5d54ce42d42f8920ff46d9102800b94482d 2025-07-17T07:01:09.4294792Z * [new tag] trunk/38e5e81e55fc5d85d6cf8a83c96c88578995e3fe -> trunk/38e5e81e55fc5d85d6cf8a83c96c88578995e3fe 2025-07-17T07:01:09.4295669Z * [new tag] trunk/391473cca0b0fa9667ad54c972e7b63bc589cd6d -> trunk/391473cca0b0fa9667ad54c972e7b63bc589cd6d 2025-07-17T07:01:09.4297549Z * [new tag] trunk/39270430c9e4dc7010a9754f522774d17ae9d578 -> trunk/39270430c9e4dc7010a9754f522774d17ae9d578 2025-07-17T07:01:09.4298401Z * [new tag] trunk/39456edbbad97a09e6507792e1df3ee1f2a16f98 -> trunk/39456edbbad97a09e6507792e1df3ee1f2a16f98 2025-07-17T07:01:09.4299201Z * [new tag] trunk/398fca9dcfcb9f90eae9258d728fab71f5b59db2 -> trunk/398fca9dcfcb9f90eae9258d728fab71f5b59db2 2025-07-17T07:01:09.4300123Z * [new tag] trunk/39a8f66d5939e892bcb07ef97462af47d3201491 -> trunk/39a8f66d5939e892bcb07ef97462af47d3201491 2025-07-17T07:01:09.4300917Z * [new tag] trunk/39b71d11fc2dd9b4da6d23a34eb29aefbb1df672 -> trunk/39b71d11fc2dd9b4da6d23a34eb29aefbb1df672 2025-07-17T07:01:09.4301802Z * [new tag] trunk/39c605e8b3c13e7f6b5b1bbbe3f4060e24b2a3e4 -> trunk/39c605e8b3c13e7f6b5b1bbbe3f4060e24b2a3e4 2025-07-17T07:01:09.4302672Z * [new tag] trunk/3a43dba21ff5d01bb8b259af3839c90e447c6ec0 -> trunk/3a43dba21ff5d01bb8b259af3839c90e447c6ec0 2025-07-17T07:01:09.4303595Z * [new tag] trunk/3a5677a380c79810cc370dce6ef79b0871ddcf8c -> trunk/3a5677a380c79810cc370dce6ef79b0871ddcf8c 2025-07-17T07:01:09.4304353Z * [new tag] trunk/3a7ff829c597ef26a271d52ae2a3c8354b2f447e -> trunk/3a7ff829c597ef26a271d52ae2a3c8354b2f447e 2025-07-17T07:01:09.4305234Z * [new tag] trunk/3b4b5f8d474a9c664f622012c6a61414ea7799a9 -> trunk/3b4b5f8d474a9c664f622012c6a61414ea7799a9 2025-07-17T07:01:09.4306321Z * [new tag] trunk/3b6569b1ef4b9ff25f5b75fe0a216d6d084d573f -> trunk/3b6569b1ef4b9ff25f5b75fe0a216d6d084d573f 2025-07-17T07:01:09.4307124Z * [new tag] trunk/3b7c5e6fa5c0be64ddde3a8edc5bcdc10390f1e3 -> trunk/3b7c5e6fa5c0be64ddde3a8edc5bcdc10390f1e3 2025-07-17T07:01:09.4307887Z * [new tag] trunk/3bc6bdc8660c052d932f550d5734da6f801c2630 -> trunk/3bc6bdc8660c052d932f550d5734da6f801c2630 2025-07-17T07:01:09.4308853Z * [new tag] trunk/3bdd5ae334b85a114a2b62fa17dcf204413eda32 -> trunk/3bdd5ae334b85a114a2b62fa17dcf204413eda32 2025-07-17T07:01:09.4309742Z * [new tag] trunk/3beb915004f4e26b1e7c5e7692e6e8ca9b75de46 -> trunk/3beb915004f4e26b1e7c5e7692e6e8ca9b75de46 2025-07-17T07:01:09.4310711Z * [new tag] trunk/3bec588bf5c4eda9a4d42ae4c25e6f87af7f078c -> trunk/3bec588bf5c4eda9a4d42ae4c25e6f87af7f078c 2025-07-17T07:01:09.4311698Z * [new tag] trunk/3c2324c64ac6b7497d630788a66c82705bbb044e -> trunk/3c2324c64ac6b7497d630788a66c82705bbb044e 2025-07-17T07:01:09.4312648Z * [new tag] trunk/3c7079959c8e61d7acb4f704a0ecf74c61425c2e -> trunk/3c7079959c8e61d7acb4f704a0ecf74c61425c2e 2025-07-17T07:01:09.4313594Z * [new tag] trunk/3c72b9fd8feed4588a040bc681ffe83cc7acd26d -> trunk/3c72b9fd8feed4588a040bc681ffe83cc7acd26d 2025-07-17T07:01:09.4314478Z * [new tag] trunk/3cb11877aa30c04be7ffa9b4ca1722f1270a5828 -> trunk/3cb11877aa30c04be7ffa9b4ca1722f1270a5828 2025-07-17T07:01:09.4315309Z * [new tag] trunk/3cbae6dde8f2a9c3b4a3e4e079e97307c3aa52d8 -> trunk/3cbae6dde8f2a9c3b4a3e4e079e97307c3aa52d8 2025-07-17T07:01:09.4316162Z * [new tag] trunk/3d06ff82a84a118f0ed246864d4fc01ac4726328 -> trunk/3d06ff82a84a118f0ed246864d4fc01ac4726328 2025-07-17T07:01:09.4317083Z * [new tag] trunk/3d595fd5595f38bb5ed3d390dc50e1715e173ad6 -> trunk/3d595fd5595f38bb5ed3d390dc50e1715e173ad6 2025-07-17T07:01:09.4318373Z * [new tag] trunk/3d82a1dfb59fa5e248f7499a7ecdf784d4f61c0e -> trunk/3d82a1dfb59fa5e248f7499a7ecdf784d4f61c0e 2025-07-17T07:01:09.4319129Z * [new tag] trunk/3dabc351bb5581f69825eee6b24fbac9f9260241 -> trunk/3dabc351bb5581f69825eee6b24fbac9f9260241 2025-07-17T07:01:09.4319978Z * [new tag] trunk/3dd872e6d53560933d8d7fc11357617746d37168 -> trunk/3dd872e6d53560933d8d7fc11357617746d37168 2025-07-17T07:01:09.4320897Z * [new tag] trunk/3dda80e990121eaf156014fffe6e2a4602c8b195 -> trunk/3dda80e990121eaf156014fffe6e2a4602c8b195 2025-07-17T07:01:09.4321796Z * [new tag] trunk/3df6360e8c956edd25453b21f6b7f56e0366dcb4 -> trunk/3df6360e8c956edd25453b21f6b7f56e0366dcb4 2025-07-17T07:01:09.4322694Z * [new tag] trunk/3e131f7779af03b462f0598afb2569092b57c840 -> trunk/3e131f7779af03b462f0598afb2569092b57c840 2025-07-17T07:01:09.4323782Z * [new tag] trunk/3e38feb05fffdf5b181a1f4c7a6f43b00ef1c526 -> trunk/3e38feb05fffdf5b181a1f4c7a6f43b00ef1c526 2025-07-17T07:01:09.4324534Z * [new tag] trunk/3e56a9cdfb98a9b06568ee54e3157c800d98a17e -> trunk/3e56a9cdfb98a9b06568ee54e3157c800d98a17e 2025-07-17T07:01:09.4325480Z * [new tag] trunk/3eb7084f7a3657f4ba6626aca63721a0020f1bd7 -> trunk/3eb7084f7a3657f4ba6626aca63721a0020f1bd7 2025-07-17T07:01:09.4326446Z * [new tag] trunk/3ed4384f5b4bb7ae7d12298632a258385a51446e -> trunk/3ed4384f5b4bb7ae7d12298632a258385a51446e 2025-07-17T07:01:09.4327294Z * [new tag] trunk/3ee75b7eacef6758db602e87287ef9574609b327 -> trunk/3ee75b7eacef6758db602e87287ef9574609b327 2025-07-17T07:01:09.4328188Z * [new tag] trunk/3ee8828c87ce6186607c3d3ab3852518fca49228 -> trunk/3ee8828c87ce6186607c3d3ab3852518fca49228 2025-07-17T07:01:09.4329147Z * [new tag] trunk/3efb22e09111b92bedb01b2a8385c789fe69090a -> trunk/3efb22e09111b92bedb01b2a8385c789fe69090a 2025-07-17T07:01:09.4330063Z * [new tag] trunk/3effe0c293219b00a0eae7e139fe2d9aed84bc03 -> trunk/3effe0c293219b00a0eae7e139fe2d9aed84bc03 2025-07-17T07:01:09.4330936Z * [new tag] trunk/3f29642ecf039129032cc61c986d7b62807163c0 -> trunk/3f29642ecf039129032cc61c986d7b62807163c0 2025-07-17T07:01:09.4331843Z * [new tag] trunk/3f569f9af77d51d0328f16434e64252756681daa -> trunk/3f569f9af77d51d0328f16434e64252756681daa 2025-07-17T07:01:09.4332794Z * [new tag] trunk/3f65e38b73cb8f0d0b4fb2e9a6671085d371ec40 -> trunk/3f65e38b73cb8f0d0b4fb2e9a6671085d371ec40 2025-07-17T07:01:09.4333650Z * [new tag] trunk/3f69e3b3a07efd5e9aa86d37773bf2a24dc0ea70 -> trunk/3f69e3b3a07efd5e9aa86d37773bf2a24dc0ea70 2025-07-17T07:01:09.4334483Z * [new tag] trunk/3f83e3eeca0645f4b2cd16fa7d5a591e9cf810d4 -> trunk/3f83e3eeca0645f4b2cd16fa7d5a591e9cf810d4 2025-07-17T07:01:09.4335597Z * [new tag] trunk/3f920f3d8f5bd15d2222758f21f9a5d36e4dad1f -> trunk/3f920f3d8f5bd15d2222758f21f9a5d36e4dad1f 2025-07-17T07:01:09.4336434Z * [new tag] trunk/3fd84a8592a2a87d04f0e3f236a92605e2be12df -> trunk/3fd84a8592a2a87d04f0e3f236a92605e2be12df 2025-07-17T07:01:09.4337309Z * [new tag] trunk/400f439670ff8859c17a870eb83dc5cae5a9c2e4 -> trunk/400f439670ff8859c17a870eb83dc5cae5a9c2e4 2025-07-17T07:01:09.4338192Z * [new tag] trunk/402ae09e41005ebff686e97e2f120a6b79e2afb7 -> trunk/402ae09e41005ebff686e97e2f120a6b79e2afb7 2025-07-17T07:01:09.4339200Z * [new tag] trunk/404008e3efdabeaf5b140a3aff77131461c33a0a -> trunk/404008e3efdabeaf5b140a3aff77131461c33a0a 2025-07-17T07:01:09.4340069Z * [new tag] trunk/4048a144abf82041f9b6653d9d4aa600a6a5409a -> trunk/4048a144abf82041f9b6653d9d4aa600a6a5409a 2025-07-17T07:01:09.4341464Z * [new tag] trunk/408d9884b07cf7268961bae7138a6436916d4a43 -> trunk/408d9884b07cf7268961bae7138a6436916d4a43 2025-07-17T07:01:09.4342339Z * [new tag] trunk/40a785103cf94a1dbc3e0e43d1ed6c41fb60bedb -> trunk/40a785103cf94a1dbc3e0e43d1ed6c41fb60bedb 2025-07-17T07:01:09.4343179Z * [new tag] trunk/40d02eb481670325ba80dcb42b40c3ebb347f1c7 -> trunk/40d02eb481670325ba80dcb42b40c3ebb347f1c7 2025-07-17T07:01:09.4344123Z * [new tag] trunk/40e39ae21f15f200828ab32826bed1a4b62532ba -> trunk/40e39ae21f15f200828ab32826bed1a4b62532ba 2025-07-17T07:01:09.4345084Z * [new tag] trunk/40fefe2871a5561b67ec268bab19db60e733f2d4 -> trunk/40fefe2871a5561b67ec268bab19db60e733f2d4 2025-07-17T07:01:09.4345857Z * [new tag] trunk/414ad470450c654d97e73bef704a7b596b5b4cbc -> trunk/414ad470450c654d97e73bef704a7b596b5b4cbc 2025-07-17T07:01:09.4347064Z * [new tag] trunk/415dfabe9b569b71098a2f874f3fc67ad2a4fc2e -> trunk/415dfabe9b569b71098a2f874f3fc67ad2a4fc2e 2025-07-17T07:01:09.4347867Z * [new tag] trunk/4162c0f70297818abd70f2fe7424dcd3cc9b2543 -> trunk/4162c0f70297818abd70f2fe7424dcd3cc9b2543 2025-07-17T07:01:09.4348712Z * [new tag] trunk/41910d7a94d2f3ffe06f7c0c30971c71b9c3b09e -> trunk/41910d7a94d2f3ffe06f7c0c30971c71b9c3b09e 2025-07-17T07:01:09.4349831Z * [new tag] trunk/41971335c98b0881e0784085096eceace575d563 -> trunk/41971335c98b0881e0784085096eceace575d563 2025-07-17T07:01:09.4350695Z * [new tag] trunk/41e8b826d07bbf707bc2c64a78b4dc15e8f3c358 -> trunk/41e8b826d07bbf707bc2c64a78b4dc15e8f3c358 2025-07-17T07:01:09.4351565Z * [new tag] trunk/41f6acef83d280a18909d58f8442e145c9e7ea6f -> trunk/41f6acef83d280a18909d58f8442e145c9e7ea6f 2025-07-17T07:01:09.4352496Z * [new tag] trunk/42015db6a9602f40250f9afc18a3fbad4ca4ef39 -> trunk/42015db6a9602f40250f9afc18a3fbad4ca4ef39 2025-07-17T07:01:09.4353439Z * [new tag] trunk/4237ee3c33b0edb01db96d8c1ecf8f5d2cf184bc -> trunk/4237ee3c33b0edb01db96d8c1ecf8f5d2cf184bc 2025-07-17T07:01:09.4354310Z * [new tag] trunk/4283d96bcdf9aaa4289985267186d74ba6534ee5 -> trunk/4283d96bcdf9aaa4289985267186d74ba6534ee5 2025-07-17T07:01:09.4355188Z * [new tag] trunk/42b48ee67229286127390000f103a11dfc8901f5 -> trunk/42b48ee67229286127390000f103a11dfc8901f5 2025-07-17T07:01:09.4356616Z * [new tag] trunk/42ff6a4a5c4e0d77bd18fcc5426622f1b8f20add -> trunk/42ff6a4a5c4e0d77bd18fcc5426622f1b8f20add 2025-07-17T07:01:09.4357432Z * [new tag] trunk/430cc1c636380a7d50652df646274f7008a76747 -> trunk/430cc1c636380a7d50652df646274f7008a76747 2025-07-17T07:01:09.4358343Z * [new tag] trunk/4311aea5e7568c9956a9f0d694f1980c387b6a37 -> trunk/4311aea5e7568c9956a9f0d694f1980c387b6a37 2025-07-17T07:01:09.4359206Z * [new tag] trunk/433a2471023f77a4e62e880ef59f22caf939c227 -> trunk/433a2471023f77a4e62e880ef59f22caf939c227 2025-07-17T07:01:09.4360250Z * [new tag] trunk/43523bf1682c2926a84a1f65f00fabd3d34db4f2 -> trunk/43523bf1682c2926a84a1f65f00fabd3d34db4f2 2025-07-17T07:01:09.4360999Z * [new tag] trunk/43a09189c68fe02bd9d8433c4a144ffc9bbf895c -> trunk/43a09189c68fe02bd9d8433c4a144ffc9bbf895c 2025-07-17T07:01:09.4361916Z * [new tag] trunk/43f72163275ce1503b1de1480642c61d20e6158d -> trunk/43f72163275ce1503b1de1480642c61d20e6158d 2025-07-17T07:01:09.4362882Z * [new tag] trunk/442aca44d603ae6c2b7d2aa2190cc91f970c4202 -> trunk/442aca44d603ae6c2b7d2aa2190cc91f970c4202 2025-07-17T07:01:09.4363826Z * [new tag] trunk/44303caabfa0bdc5688d693d491ba7c3fdb40f3a -> trunk/44303caabfa0bdc5688d693d491ba7c3fdb40f3a 2025-07-17T07:01:09.4364851Z * [new tag] trunk/443b5b43c3d40b89bbb5db70f3f05a44b2a4ec66 -> trunk/443b5b43c3d40b89bbb5db70f3f05a44b2a4ec66 2025-07-17T07:01:09.4365790Z * [new tag] trunk/4486a6dbfd65ef490cfe73e0630929e85f61ee16 -> trunk/4486a6dbfd65ef490cfe73e0630929e85f61ee16 2025-07-17T07:01:09.4366642Z * [new tag] trunk/4491326fb0c0e67eca1598ae33c41cdfced2cd33 -> trunk/4491326fb0c0e67eca1598ae33c41cdfced2cd33 2025-07-17T07:01:09.4367589Z * [new tag] trunk/44a5f93462bd4aa4f36ae2573685ed7ba458c4c9 -> trunk/44a5f93462bd4aa4f36ae2573685ed7ba458c4c9 2025-07-17T07:01:09.4368502Z * [new tag] trunk/44d0800d60e78fef8ab332e307c3134e3c276ba4 -> trunk/44d0800d60e78fef8ab332e307c3134e3c276ba4 2025-07-17T07:01:09.4369404Z * [new tag] trunk/44df7cf28dd37a4d900eb6b2f78dabf72b209d9b -> trunk/44df7cf28dd37a4d900eb6b2f78dabf72b209d9b 2025-07-17T07:01:09.4370490Z * [new tag] trunk/44f5b9312290866584088e2e42228c484f669faf -> trunk/44f5b9312290866584088e2e42228c484f669faf 2025-07-17T07:01:09.4371427Z * [new tag] trunk/4500a4aa50141ed30e093ef8491b30d1d1287348 -> trunk/4500a4aa50141ed30e093ef8491b30d1d1287348 2025-07-17T07:01:09.4372355Z * [new tag] trunk/451b525bf0cb8840adbde1b6280c7b199f733ced -> trunk/451b525bf0cb8840adbde1b6280c7b199f733ced 2025-07-17T07:01:09.4373298Z * [new tag] trunk/45382b284d03015f3e6eb83a959f0e54a3ebd688 -> trunk/45382b284d03015f3e6eb83a959f0e54a3ebd688 2025-07-17T07:01:09.4374264Z * [new tag] trunk/453bc9fbdfb97fef925477cbbf4948e93fd22756 -> trunk/453bc9fbdfb97fef925477cbbf4948e93fd22756 2025-07-17T07:01:09.4375160Z * [new tag] trunk/45596ec58f5bc5489911ee932c2a55a7ff40d0a0 -> trunk/45596ec58f5bc5489911ee932c2a55a7ff40d0a0 2025-07-17T07:01:09.4376009Z * [new tag] trunk/455dfd258980294f0745bd90aee12a323e37224d -> trunk/455dfd258980294f0745bd90aee12a323e37224d 2025-07-17T07:01:09.4377118Z * [new tag] trunk/456b7451c78096fd512c60e26cc618386a251bc7 -> trunk/456b7451c78096fd512c60e26cc618386a251bc7 2025-07-17T07:01:09.4377939Z * [new tag] trunk/456f40cb09c6e5e0cd268d1601b89fc5ac1987ea -> trunk/456f40cb09c6e5e0cd268d1601b89fc5ac1987ea 2025-07-17T07:01:09.4378867Z * [new tag] trunk/4574b39aa45f0250cba04aa3cb053a686c4888b2 -> trunk/4574b39aa45f0250cba04aa3cb053a686c4888b2 2025-07-17T07:01:09.4379789Z * [new tag] trunk/457dd79927db6ae7f1c53f36768b7ac93b61e507 -> trunk/457dd79927db6ae7f1c53f36768b7ac93b61e507 2025-07-17T07:01:09.4380668Z * [new tag] trunk/4585c33e74079af8e9067bf39970b93c3f13629f -> trunk/4585c33e74079af8e9067bf39970b93c3f13629f 2025-07-17T07:01:09.4381613Z * [new tag] trunk/458cc7213baf01ab742a2250c7a31f7796fcb1ef -> trunk/458cc7213baf01ab742a2250c7a31f7796fcb1ef 2025-07-17T07:01:09.4382547Z * [new tag] trunk/45c5a232373cac1b1524259f20758bfb56dde5f2 -> trunk/45c5a232373cac1b1524259f20758bfb56dde5f2 2025-07-17T07:01:09.4383506Z * [new tag] trunk/4609699bfd440d1fe603c5ad9a942e45410094c1 -> trunk/4609699bfd440d1fe603c5ad9a942e45410094c1 2025-07-17T07:01:09.4384467Z * [new tag] trunk/4628f1b7a9313df98346d582d9a789661a823e27 -> trunk/4628f1b7a9313df98346d582d9a789661a823e27 2025-07-17T07:01:09.4385369Z * [new tag] trunk/463fe36532bc165b46c12cef4948f039434e0924 -> trunk/463fe36532bc165b46c12cef4948f039434e0924 2025-07-17T07:01:09.4386327Z * [new tag] trunk/4657a84bc55b6ce12f21706de2b90e1d43784f57 -> trunk/4657a84bc55b6ce12f21706de2b90e1d43784f57 2025-07-17T07:01:09.4387240Z * [new tag] trunk/46915b13614dbac90724d0f1802b8e0db037c9e4 -> trunk/46915b13614dbac90724d0f1802b8e0db037c9e4 2025-07-17T07:01:09.4388166Z * [new tag] trunk/473208cb18d543e8f968918a6b3c9defa8a4ae10 -> trunk/473208cb18d543e8f968918a6b3c9defa8a4ae10 2025-07-17T07:01:09.4389058Z * [new tag] trunk/476874b37fff42a46d25dfac720ef4c71ec74fe0 -> trunk/476874b37fff42a46d25dfac720ef4c71ec74fe0 2025-07-17T07:01:09.4390378Z * [new tag] trunk/4781b0ee6057fdf2a82d2f9ed30299f219267a71 -> trunk/4781b0ee6057fdf2a82d2f9ed30299f219267a71 2025-07-17T07:01:09.4391257Z * [new tag] trunk/4781d72faa6b72bf96fde9bedfca06a5285eebfb -> trunk/4781d72faa6b72bf96fde9bedfca06a5285eebfb 2025-07-17T07:01:09.4392238Z * [new tag] trunk/47c8810b5275179833d6b33ca3d70922f485272c -> trunk/47c8810b5275179833d6b33ca3d70922f485272c 2025-07-17T07:01:09.4394321Z * [new tag] trunk/47f10d0ad0dda281c886ff08ac2f938207027316 -> trunk/47f10d0ad0dda281c886ff08ac2f938207027316 2025-07-17T07:01:09.4395119Z * [new tag] trunk/4805a6ead6f1e7f32351056e2602be4e908f69b7 -> trunk/4805a6ead6f1e7f32351056e2602be4e908f69b7 2025-07-17T07:01:09.4396025Z * [new tag] trunk/48315181c75e43cab5957197d42e053d66b3fe1c -> trunk/48315181c75e43cab5957197d42e053d66b3fe1c 2025-07-17T07:01:09.4397196Z * [new tag] trunk/4851863e3f98e1ffba1d5801f3533031ef4f905d -> trunk/4851863e3f98e1ffba1d5801f3533031ef4f905d 2025-07-17T07:01:09.4398067Z * [new tag] trunk/48560eef80e97e855cbb8e2814acefe8f5cc6fbd -> trunk/48560eef80e97e855cbb8e2814acefe8f5cc6fbd 2025-07-17T07:01:09.4398921Z * [new tag] trunk/4886ba64dceb24b8a0444e574abb907a18fdeee9 -> trunk/4886ba64dceb24b8a0444e574abb907a18fdeee9 2025-07-17T07:01:09.4399840Z * [new tag] trunk/48921721d8ed32a2c7f80605b434f9fcb2f948b4 -> trunk/48921721d8ed32a2c7f80605b434f9fcb2f948b4 2025-07-17T07:01:09.4400801Z * [new tag] trunk/48de3da2539cecaee14af8e3841c133c9c0c0f1c -> trunk/48de3da2539cecaee14af8e3841c133c9c0c0f1c 2025-07-17T07:01:09.4401612Z * [new tag] trunk/48e7b62d3abda4a3eac2f538c9f35e56093c4ece -> trunk/48e7b62d3abda4a3eac2f538c9f35e56093c4ece 2025-07-17T07:01:09.4402571Z * [new tag] trunk/4918502d2e685270cea9f1fd733a3414ac1ca5d7 -> trunk/4918502d2e685270cea9f1fd733a3414ac1ca5d7 2025-07-17T07:01:09.4403497Z * [new tag] trunk/493bd625e252dea02e871346beaa49745b4b2663 -> trunk/493bd625e252dea02e871346beaa49745b4b2663 2025-07-17T07:01:09.4404441Z * [new tag] trunk/493f42a5417a8ac33d1070478d1869ea4f207b5b -> trunk/493f42a5417a8ac33d1070478d1869ea4f207b5b 2025-07-17T07:01:09.4405428Z * [new tag] trunk/495c317005ad656dee752b6ad7bd5541b04e388e -> trunk/495c317005ad656dee752b6ad7bd5541b04e388e 2025-07-17T07:01:09.4406377Z * [new tag] trunk/49888e6be0dcc00ba546746425893bb17c287248 -> trunk/49888e6be0dcc00ba546746425893bb17c287248 2025-07-17T07:01:09.4407199Z * [new tag] trunk/49ee1e7106db00778345efd7c70cc12d2ca6a91a -> trunk/49ee1e7106db00778345efd7c70cc12d2ca6a91a 2025-07-17T07:01:09.4407999Z * [new tag] trunk/4a26bb8a12ba5cb437ed5b7f035b5b533e07549e -> trunk/4a26bb8a12ba5cb437ed5b7f035b5b533e07549e 2025-07-17T07:01:09.4408966Z * [new tag] trunk/4a4cac0cefea3661cc69cfdafdba64832ee0841a -> trunk/4a4cac0cefea3661cc69cfdafdba64832ee0841a 2025-07-17T07:01:09.4409915Z * [new tag] trunk/4a80ddfbe70bf6b75acc3177e5d2095b285da841 -> trunk/4a80ddfbe70bf6b75acc3177e5d2095b285da841 2025-07-17T07:01:09.4410818Z * [new tag] trunk/4a8f5e752beb5a6809ba866c83f32dd464a47bfd -> trunk/4a8f5e752beb5a6809ba866c83f32dd464a47bfd 2025-07-17T07:01:09.4411749Z * [new tag] trunk/4a954fc1857ff41be604e8cae68908d41124b419 -> trunk/4a954fc1857ff41be604e8cae68908d41124b419 2025-07-17T07:01:09.4412631Z * [new tag] trunk/4ab4d29cbee1f90daf14444d5ca3a53653c7784d -> trunk/4ab4d29cbee1f90daf14444d5ca3a53653c7784d 2025-07-17T07:01:09.4413560Z * [new tag] trunk/4b11428cb5b3d97f3068a2dc4c55cee6ddd41979 -> trunk/4b11428cb5b3d97f3068a2dc4c55cee6ddd41979 2025-07-17T07:01:09.4414680Z * [new tag] trunk/4b4c2a7b1dfd88313801878c5b4e3855fe5232df -> trunk/4b4c2a7b1dfd88313801878c5b4e3855fe5232df 2025-07-17T07:01:09.4415451Z * [new tag] trunk/4b55871e06d6bad54eac45e45a9af615d758a39f -> trunk/4b55871e06d6bad54eac45e45a9af615d758a39f 2025-07-17T07:01:09.4416300Z * [new tag] trunk/4b6cbf528b8f7b95e02e3a0233945e0bb8b00f44 -> trunk/4b6cbf528b8f7b95e02e3a0233945e0bb8b00f44 2025-07-17T07:01:09.4417892Z * [new tag] trunk/4b9a6f7211123511e856ac8c8524bc332a741241 -> trunk/4b9a6f7211123511e856ac8c8524bc332a741241 2025-07-17T07:01:09.4418760Z * [new tag] trunk/4bb936d8b77c959efbff0bdb68f63e5a5faf60a9 -> trunk/4bb936d8b77c959efbff0bdb68f63e5a5faf60a9 2025-07-17T07:01:09.4419667Z * [new tag] trunk/4bc3e4b497948af0a48d08b427339efc8960fedb -> trunk/4bc3e4b497948af0a48d08b427339efc8960fedb 2025-07-17T07:01:09.4420569Z * [new tag] trunk/4bd18e31e5a38d0e84ce915b1fa124058c6373fa -> trunk/4bd18e31e5a38d0e84ce915b1fa124058c6373fa 2025-07-17T07:01:09.4421677Z * [new tag] trunk/4c0091fda65b714fa73671a15e379f814af153e0 -> trunk/4c0091fda65b714fa73671a15e379f814af153e0 2025-07-17T07:01:09.4422588Z * [new tag] trunk/4c0aa37dda605e7cf3372c71940d7e3a93ecef8d -> trunk/4c0aa37dda605e7cf3372c71940d7e3a93ecef8d 2025-07-17T07:01:09.4423518Z * [new tag] trunk/4c3da611c2a80fa5073b164974d7edc0577b9ca7 -> trunk/4c3da611c2a80fa5073b164974d7edc0577b9ca7 2025-07-17T07:01:09.4424451Z * [new tag] trunk/4c59edf0c5838087cbe09c67c6e0e776467a5f2d -> trunk/4c59edf0c5838087cbe09c67c6e0e776467a5f2d 2025-07-17T07:01:09.4425259Z * [new tag] trunk/4c8eb65efb147cd263fc02f5588683f530363a0f -> trunk/4c8eb65efb147cd263fc02f5588683f530363a0f 2025-07-17T07:01:09.4426182Z * [new tag] trunk/4cbbc8b4583e9dac4af7e8d1d8535546de21178c -> trunk/4cbbc8b4583e9dac4af7e8d1d8535546de21178c 2025-07-17T07:01:09.4427118Z * [new tag] trunk/4cc13c4af6dbd5aa36545ef577d0bee517cf8c57 -> trunk/4cc13c4af6dbd5aa36545ef577d0bee517cf8c57 2025-07-17T07:01:09.4427898Z * [new tag] trunk/4cd6e96bf0d13f168772f6ad44267b1ac7632a97 -> trunk/4cd6e96bf0d13f168772f6ad44267b1ac7632a97 2025-07-17T07:01:09.4428805Z * [new tag] trunk/4cdbdcdbcf2b7f7a52a5c61cb35064f7b4aa2e44 -> trunk/4cdbdcdbcf2b7f7a52a5c61cb35064f7b4aa2e44 2025-07-17T07:01:09.4429720Z * [new tag] trunk/4ce6e6ec8890a3f6ee604c9efb3ff153825ce575 -> trunk/4ce6e6ec8890a3f6ee604c9efb3ff153825ce575 2025-07-17T07:01:09.4430632Z * [new tag] trunk/4cfc0a320897b6ec75b85cfc07bc29009a824177 -> trunk/4cfc0a320897b6ec75b85cfc07bc29009a824177 2025-07-17T07:01:09.4431536Z * [new tag] trunk/4d055982e38f59fdb2a4c9d8855e58548bc42c12 -> trunk/4d055982e38f59fdb2a4c9d8855e58548bc42c12 2025-07-17T07:01:09.4432793Z * [new tag] trunk/4d3ecefda5a41df678fd68b020c521db95e9fbde -> trunk/4d3ecefda5a41df678fd68b020c521db95e9fbde 2025-07-17T07:01:09.4433563Z * [new tag] trunk/4d5d627e5ff3310318f9df80348ee419324228df -> trunk/4d5d627e5ff3310318f9df80348ee419324228df 2025-07-17T07:01:09.4434397Z * [new tag] trunk/4d9d884c3f5adc89b59d25d5a080498b76f9bb39 -> trunk/4d9d884c3f5adc89b59d25d5a080498b76f9bb39 2025-07-17T07:01:09.4435789Z * [new tag] trunk/4da98351b9e231bbbe83b5c590cf7d2ea382333a -> trunk/4da98351b9e231bbbe83b5c590cf7d2ea382333a 2025-07-17T07:01:09.4436717Z * [new tag] trunk/4dce5b71a0751aa4287c3a80adf07afc773ec4db -> trunk/4dce5b71a0751aa4287c3a80adf07afc773ec4db 2025-07-17T07:01:09.4437594Z * [new tag] trunk/4e13eca713c60ca63c1116823b99d2461a7422ef -> trunk/4e13eca713c60ca63c1116823b99d2461a7422ef 2025-07-17T07:01:09.4440929Z * [new tag] trunk/4e19477196547eb2e8157d6d132689373ffcf0fa -> trunk/4e19477196547eb2e8157d6d132689373ffcf0fa 2025-07-17T07:01:09.4441691Z * [new tag] trunk/4e8dd11be17a974e0ee5503b3061d4d47467844f -> trunk/4e8dd11be17a974e0ee5503b3061d4d47467844f 2025-07-17T07:01:09.4442460Z * [new tag] trunk/4ebd2690654ffe487c43941ebaea41b99914d8b7 -> trunk/4ebd2690654ffe487c43941ebaea41b99914d8b7 2025-07-17T07:01:09.4443099Z * [new tag] trunk/4ed1b03f7275075b1783d1deab946ced4ceba4d6 -> trunk/4ed1b03f7275075b1783d1deab946ced4ceba4d6 2025-07-17T07:01:09.4443779Z * [new tag] trunk/4ee4863232b9e07728d85254768bcba3aadc9b9a -> trunk/4ee4863232b9e07728d85254768bcba3aadc9b9a 2025-07-17T07:01:09.4444574Z * [new tag] trunk/4f36743f5eef2d9c40357eb5d8d8b1aeeacfbb2a -> trunk/4f36743f5eef2d9c40357eb5d8d8b1aeeacfbb2a 2025-07-17T07:01:09.4445389Z * [new tag] trunk/4f5b34427b57e8b876d12e6ce551f04a7c31cacf -> trunk/4f5b34427b57e8b876d12e6ce551f04a7c31cacf 2025-07-17T07:01:09.4446059Z * [new tag] trunk/4f5be5661240427fbbfbe1d137dce53ca32846b5 -> trunk/4f5be5661240427fbbfbe1d137dce53ca32846b5 2025-07-17T07:01:09.4446643Z * [new tag] trunk/4f70fbbd16d1f0d62af082246a95e56cffccc860 -> trunk/4f70fbbd16d1f0d62af082246a95e56cffccc860 2025-07-17T07:01:09.4447394Z * [new tag] trunk/4ff0e033c16aae064f05ee9300053cd304891673 -> trunk/4ff0e033c16aae064f05ee9300053cd304891673 2025-07-17T07:01:09.4448136Z * [new tag] trunk/4ff9b7fa3116b1c429e577830ac6e816734ad029 -> trunk/4ff9b7fa3116b1c429e577830ac6e816734ad029 2025-07-17T07:01:09.4449120Z * [new tag] trunk/502486d9466e81cda76c91d33eb869235480bee9 -> trunk/502486d9466e81cda76c91d33eb869235480bee9 2025-07-17T07:01:09.4449860Z * [new tag] trunk/503362d019b3782581492af7767945dbd75ca1c9 -> trunk/503362d019b3782581492af7767945dbd75ca1c9 2025-07-17T07:01:09.4450656Z * [new tag] trunk/508cdc4fc9f7a91b5fd3f20de38d673daebf1af3 -> trunk/508cdc4fc9f7a91b5fd3f20de38d673daebf1af3 2025-07-17T07:01:09.4451644Z * [new tag] trunk/50940270ae179134cd4f9072f04ffdd55daf808e -> trunk/50940270ae179134cd4f9072f04ffdd55daf808e 2025-07-17T07:01:09.4452511Z * [new tag] trunk/50b2069b61942e923528c94ccbbc8ab5e92c381e -> trunk/50b2069b61942e923528c94ccbbc8ab5e92c381e 2025-07-17T07:01:09.4453457Z * [new tag] trunk/50d8168c8b62990fda86398c9dee1dc8cbd6908d -> trunk/50d8168c8b62990fda86398c9dee1dc8cbd6908d 2025-07-17T07:01:09.4454470Z * [new tag] trunk/510c398a4f1dff9217938159d605290149358332 -> trunk/510c398a4f1dff9217938159d605290149358332 2025-07-17T07:01:09.4455462Z * [new tag] trunk/5116293f7eb587ada6076f3c3ea1711a0ec7ab4a -> trunk/5116293f7eb587ada6076f3c3ea1711a0ec7ab4a 2025-07-17T07:01:09.4456561Z * [new tag] trunk/5118a8f8a5a7906e26bcbd35370de3416b5cdab0 -> trunk/5118a8f8a5a7906e26bcbd35370de3416b5cdab0 2025-07-17T07:01:09.4457544Z * [new tag] trunk/51560797ce70aea353585d8381ee88c2e6c81075 -> trunk/51560797ce70aea353585d8381ee88c2e6c81075 2025-07-17T07:01:09.4458566Z * [new tag] trunk/517d2995e09603017f07f065c1ae5b8d25962cd2 -> trunk/517d2995e09603017f07f065c1ae5b8d25962cd2 2025-07-17T07:01:09.4459517Z * [new tag] trunk/51853b358e698f6a42c1eef045ab8fa766129ee1 -> trunk/51853b358e698f6a42c1eef045ab8fa766129ee1 2025-07-17T07:01:09.4460286Z * [new tag] trunk/51a708ffc679b13f99e4c7cf19bc00082a3266a6 -> trunk/51a708ffc679b13f99e4c7cf19bc00082a3266a6 2025-07-17T07:01:09.4461298Z * [new tag] trunk/51eb8e8f84bb9aa901cff17dd649e18b17a8908c -> trunk/51eb8e8f84bb9aa901cff17dd649e18b17a8908c 2025-07-17T07:01:09.4462552Z * [new tag] trunk/52214485747ceb0ea47ce5a09babb0b82b3282b8 -> trunk/52214485747ceb0ea47ce5a09babb0b82b3282b8 2025-07-17T07:01:09.4463534Z * [new tag] trunk/522a18bd6c094c766c0de9ef539682d1a3f04a15 -> trunk/522a18bd6c094c766c0de9ef539682d1a3f04a15 2025-07-17T07:01:09.4464376Z * [new tag] trunk/523b637cbeb69665072a2cf489ec1c5313b57670 -> trunk/523b637cbeb69665072a2cf489ec1c5313b57670 2025-07-17T07:01:09.4465347Z * [new tag] trunk/524e8270955788c53473497fd2cc16c5aa0e4c67 -> trunk/524e8270955788c53473497fd2cc16c5aa0e4c67 2025-07-17T07:01:09.4467486Z * [new tag] trunk/5264f8cd8d08272003298cdefe6bd60b1b8c80b4 -> trunk/5264f8cd8d08272003298cdefe6bd60b1b8c80b4 2025-07-17T07:01:09.4468285Z * [new tag] trunk/52772765e034622d1a86476e4bb19c28e3945f74 -> trunk/52772765e034622d1a86476e4bb19c28e3945f74 2025-07-17T07:01:09.4469280Z * [new tag] trunk/5285d1024376396a00fe750fe3d628c65dc26254 -> trunk/5285d1024376396a00fe750fe3d628c65dc26254 2025-07-17T07:01:09.4470278Z * [new tag] trunk/529e0357c6c4e74f8cd32c29198c5f1c9f6e329d -> trunk/529e0357c6c4e74f8cd32c29198c5f1c9f6e329d 2025-07-17T07:01:09.4471181Z * [new tag] trunk/52e4e41cbc36a5cf44395ff84ca2d069263560de -> trunk/52e4e41cbc36a5cf44395ff84ca2d069263560de 2025-07-17T07:01:09.4472113Z * [new tag] trunk/52edfb2cbcdded865645cc82bb1bb501fdcbdb52 -> trunk/52edfb2cbcdded865645cc82bb1bb501fdcbdb52 2025-07-17T07:01:09.4473044Z * [new tag] trunk/52f873adc23e7069ce95933d97ee514022cfbf7d -> trunk/52f873adc23e7069ce95933d97ee514022cfbf7d 2025-07-17T07:01:09.4473940Z * [new tag] trunk/53057fc16af2d381a61fe891b52ac8731ee9dfae -> trunk/53057fc16af2d381a61fe891b52ac8731ee9dfae 2025-07-17T07:01:09.4474827Z * [new tag] trunk/534c454e77ac0eefd52d63c60d42911e7f9617ea -> trunk/534c454e77ac0eefd52d63c60d42911e7f9617ea 2025-07-17T07:01:09.4475774Z * [new tag] trunk/53ab73090eb66d96e45ec134e41cf67266208954 -> trunk/53ab73090eb66d96e45ec134e41cf67266208954 2025-07-17T07:01:09.4476745Z * [new tag] trunk/53cd18f6b31bc2ea62985fda87e96aa17cd11bc1 -> trunk/53cd18f6b31bc2ea62985fda87e96aa17cd11bc1 2025-07-17T07:01:09.4477611Z * [new tag] trunk/53d06e18d9b165cb8aa0a5a3cbb6837ac3000c59 -> trunk/53d06e18d9b165cb8aa0a5a3cbb6837ac3000c59 2025-07-17T07:01:09.4478760Z * [new tag] trunk/53e0b9c3936176521ed8d71c00abd5b7499057c2 -> trunk/53e0b9c3936176521ed8d71c00abd5b7499057c2 2025-07-17T07:01:09.4480079Z * [new tag] trunk/541297daae63f74a90bac52c5db3540bf84bc971 -> trunk/541297daae63f74a90bac52c5db3540bf84bc971 2025-07-17T07:01:09.4481040Z * [new tag] trunk/5430990bd7d050f249b1cdf1f7d1016c4b17488d -> trunk/5430990bd7d050f249b1cdf1f7d1016c4b17488d 2025-07-17T07:01:09.4481916Z * [new tag] trunk/5435e7539930be7bd038683ce096038b30c5bb5f -> trunk/5435e7539930be7bd038683ce096038b30c5bb5f 2025-07-17T07:01:09.4482961Z * [new tag] trunk/545fbd58dc8b4f688f6b259cb671b3ec16a46810 -> trunk/545fbd58dc8b4f688f6b259cb671b3ec16a46810 2025-07-17T07:01:09.4483808Z * [new tag] trunk/54701a0c943245402fceeab0e55d7aa394303c20 -> trunk/54701a0c943245402fceeab0e55d7aa394303c20 2025-07-17T07:01:09.4484669Z * [new tag] trunk/5484890539823d9867c74209588abe095c9232a1 -> trunk/5484890539823d9867c74209588abe095c9232a1 2025-07-17T07:01:09.4485703Z * [new tag] trunk/548c9d8281d9b3d6d12e90c40b3387faf0e24c61 -> trunk/548c9d8281d9b3d6d12e90c40b3387faf0e24c61 2025-07-17T07:01:09.4486698Z * [new tag] trunk/54976bca103fcf2b5037cc0cd1b37c4639fcf779 -> trunk/54976bca103fcf2b5037cc0cd1b37c4639fcf779 2025-07-17T07:01:09.4487697Z * [new tag] trunk/54998c2daaf5b8919cf82367492dd3c5177ab935 -> trunk/54998c2daaf5b8919cf82367492dd3c5177ab935 2025-07-17T07:01:09.4488619Z * [new tag] trunk/54a4d34d100f4ebe45f486451967daba896e839c -> trunk/54a4d34d100f4ebe45f486451967daba896e839c 2025-07-17T07:01:09.4489495Z * [new tag] trunk/54a7e5b5983d237b324b50703bcb0919a6c4c296 -> trunk/54a7e5b5983d237b324b50703bcb0919a6c4c296 2025-07-17T07:01:09.4490552Z * [new tag] trunk/54b8087f638de57c1c93c4624d03f2f2c512b90e -> trunk/54b8087f638de57c1c93c4624d03f2f2c512b90e 2025-07-17T07:01:09.4491592Z * [new tag] trunk/55108074c0795be3b617d3b13b06794f63e1f8ca -> trunk/55108074c0795be3b617d3b13b06794f63e1f8ca 2025-07-17T07:01:09.4492429Z * [new tag] trunk/554b5680405e6197a985040ffe88157beb637450 -> trunk/554b5680405e6197a985040ffe88157beb637450 2025-07-17T07:01:09.4493441Z * [new tag] trunk/555f3562541992b66a550eca8e8740884b1247f8 -> trunk/555f3562541992b66a550eca8e8740884b1247f8 2025-07-17T07:01:09.4494347Z * [new tag] trunk/5596cefba623fcc0739f1e9568131a85973cf1f9 -> trunk/5596cefba623fcc0739f1e9568131a85973cf1f9 2025-07-17T07:01:09.4495537Z * [new tag] trunk/55d888a616be3c94d8e4073b4d1580541692997d -> trunk/55d888a616be3c94d8e4073b4d1580541692997d 2025-07-17T07:01:09.4496387Z * [new tag] trunk/55dae0bf7a4b501be91d0e022e675337dfe288ff -> trunk/55dae0bf7a4b501be91d0e022e675337dfe288ff 2025-07-17T07:01:09.4497300Z * [new tag] trunk/55ef7b15e0b2de903bfc26adfb0788ecfbcb4ed4 -> trunk/55ef7b15e0b2de903bfc26adfb0788ecfbcb4ed4 2025-07-17T07:01:09.4498236Z * [new tag] trunk/5606c516fd87e5c3594177e4ca64c3cac7fdafd5 -> trunk/5606c516fd87e5c3594177e4ca64c3cac7fdafd5 2025-07-17T07:01:09.4499010Z * [new tag] trunk/5633283574c458bd6a3cbb6a0a890f0cb9c8b2b5 -> trunk/5633283574c458bd6a3cbb6a0a890f0cb9c8b2b5 2025-07-17T07:01:09.4499966Z * [new tag] trunk/563fd95563c5edd732ae260b3bd3d0c38822ab57 -> trunk/563fd95563c5edd732ae260b3bd3d0c38822ab57 2025-07-17T07:01:09.4500876Z * [new tag] trunk/565fd079099d33a81c11d7b36581f09441ba6efa -> trunk/565fd079099d33a81c11d7b36581f09441ba6efa 2025-07-17T07:01:09.4501668Z * [new tag] trunk/568ca89bac9a80a66d664593a26ae69ac604796e -> trunk/568ca89bac9a80a66d664593a26ae69ac604796e 2025-07-17T07:01:09.4502570Z * [new tag] trunk/5692cbb818f1af9fcce9234e202d232afa5f3fa3 -> trunk/5692cbb818f1af9fcce9234e202d232afa5f3fa3 2025-07-17T07:01:09.4503490Z * [new tag] trunk/56b03df6ac5b4185a2b7b92f253565500a5b51ca -> trunk/56b03df6ac5b4185a2b7b92f253565500a5b51ca 2025-07-17T07:01:09.4504403Z * [new tag] trunk/56b3bf0c74f5837fd4fa6293bc515d353cb10295 -> trunk/56b3bf0c74f5837fd4fa6293bc515d353cb10295 2025-07-17T07:01:09.4505331Z * [new tag] trunk/56c69bedcc7e2211e5a3d6249e51b1674be5d10e -> trunk/56c69bedcc7e2211e5a3d6249e51b1674be5d10e 2025-07-17T07:01:09.4506213Z * [new tag] trunk/5763ec5f8d11df5eea962bedc74563394c0e273f -> trunk/5763ec5f8d11df5eea962bedc74563394c0e273f 2025-07-17T07:01:09.4507182Z * [new tag] trunk/577baa411675ed241c7d5cf79f25c13e29dac583 -> trunk/577baa411675ed241c7d5cf79f25c13e29dac583 2025-07-17T07:01:09.4508099Z * [new tag] trunk/57e4d7b5ccb8e35b434b62cc1f9aafb7d4d82b55 -> trunk/57e4d7b5ccb8e35b434b62cc1f9aafb7d4d82b55 2025-07-17T07:01:09.4508986Z * [new tag] trunk/584a0510b30b2472e54197d6b67b6f5f5e8ac807 -> trunk/584a0510b30b2472e54197d6b67b6f5f5e8ac807 2025-07-17T07:01:09.4509911Z * [new tag] trunk/588b5fb94bc6d2195ba5a4287b7feebe736da7db -> trunk/588b5fb94bc6d2195ba5a4287b7feebe736da7db 2025-07-17T07:01:09.4510834Z * [new tag] trunk/58e5d20c57e6baafd82b3b49c0e52931f5ae5d51 -> trunk/58e5d20c57e6baafd82b3b49c0e52931f5ae5d51 2025-07-17T07:01:09.4511726Z * [new tag] trunk/590607c5992d200b86361c5b68d53c93d8099193 -> trunk/590607c5992d200b86361c5b68d53c93d8099193 2025-07-17T07:01:09.4512761Z * [new tag] trunk/590fe4d2d7565f2045ef1ad4f4aad1f3b3de7aa3 -> trunk/590fe4d2d7565f2045ef1ad4f4aad1f3b3de7aa3 2025-07-17T07:01:09.4513761Z * [new tag] trunk/5951fcd50acc51bb91beae8488758f35219da849 -> trunk/5951fcd50acc51bb91beae8488758f35219da849 2025-07-17T07:01:09.4514580Z * [new tag] trunk/596b418391aa5d520e69310250c1f86c6c0a1107 -> trunk/596b418391aa5d520e69310250c1f86c6c0a1107 2025-07-17T07:01:09.4515488Z * [new tag] trunk/59c3cac4547aafd2f718b7c64053098cc5886878 -> trunk/59c3cac4547aafd2f718b7c64053098cc5886878 2025-07-17T07:01:09.4516637Z * [new tag] trunk/59eb61b2d1e4b64debbefa036acd0d8c7d55f0a3 -> trunk/59eb61b2d1e4b64debbefa036acd0d8c7d55f0a3 2025-07-17T07:01:09.4517562Z * [new tag] trunk/59f9b25f3cfc635053843372ea29ff4bf754da3f -> trunk/59f9b25f3cfc635053843372ea29ff4bf754da3f 2025-07-17T07:01:09.4518671Z * [new tag] trunk/5a2db5152d23f76dbb45d20008d9af68e761e8d1 -> trunk/5a2db5152d23f76dbb45d20008d9af68e761e8d1 2025-07-17T07:01:09.4519613Z * [new tag] trunk/5a533f74a160f6a570c2b9770ffdd89874ba59e2 -> trunk/5a533f74a160f6a570c2b9770ffdd89874ba59e2 2025-07-17T07:01:09.4520534Z * [new tag] trunk/5a54db14e3843cfa87fd8d27487dbf2f2dfb6c47 -> trunk/5a54db14e3843cfa87fd8d27487dbf2f2dfb6c47 2025-07-17T07:01:09.4521524Z * [new tag] trunk/5a5a05a6a3be376130848e235df73b752eef0230 -> trunk/5a5a05a6a3be376130848e235df73b752eef0230 2025-07-17T07:01:09.4522436Z * [new tag] trunk/5ab257c74c8e3ffe99380790de2134ba8013555e -> trunk/5ab257c74c8e3ffe99380790de2134ba8013555e 2025-07-17T07:01:09.4523403Z * [new tag] trunk/5ab6a3fb6fd37c542060c606edd4b95c7e3cae82 -> trunk/5ab6a3fb6fd37c542060c606edd4b95c7e3cae82 2025-07-17T07:01:09.4524258Z * [new tag] trunk/5ad2bee2c8a7defd2580bb138145a49c37146fcc -> trunk/5ad2bee2c8a7defd2580bb138145a49c37146fcc 2025-07-17T07:01:09.4525378Z * [new tag] trunk/5aee022d8b2bc9d31ddaf877315ffb8ad9d62985 -> trunk/5aee022d8b2bc9d31ddaf877315ffb8ad9d62985 2025-07-17T07:01:09.4526143Z * [new tag] trunk/5b10b0a96f9abf8c2751db324f0773aa433ec783 -> trunk/5b10b0a96f9abf8c2751db324f0773aa433ec783 2025-07-17T07:01:09.4527169Z * [new tag] trunk/5b4e0255d7ed756c312fb74ffcf17fe62c903bd7 -> trunk/5b4e0255d7ed756c312fb74ffcf17fe62c903bd7 2025-07-17T07:01:09.4528074Z * [new tag] trunk/5b656289064311e8bb08e1148db7d9b41f9d7ac8 -> trunk/5b656289064311e8bb08e1148db7d9b41f9d7ac8 2025-07-17T07:01:09.4530552Z * [new tag] trunk/5b9db4335e61c1c903cb0769282cbea588e49036 -> trunk/5b9db4335e61c1c903cb0769282cbea588e49036 2025-07-17T07:01:09.4531316Z * [new tag] trunk/5bd7804be2186f1756fba75ecc900d3b19016ad5 -> trunk/5bd7804be2186f1756fba75ecc900d3b19016ad5 2025-07-17T07:01:09.4532296Z * [new tag] trunk/5c79a55e7e58c6382c7ce02da1cd07d358239d94 -> trunk/5c79a55e7e58c6382c7ce02da1cd07d358239d94 2025-07-17T07:01:09.4533274Z * [new tag] trunk/5c7e1d39ab81647300d60e7cc22b24acf2641457 -> trunk/5c7e1d39ab81647300d60e7cc22b24acf2641457 2025-07-17T07:01:09.4534307Z * [new tag] trunk/5cc4e856fda4accb2e9291527693a91dc2a18d89 -> trunk/5cc4e856fda4accb2e9291527693a91dc2a18d89 2025-07-17T07:01:09.4535361Z * [new tag] trunk/5cfe4377d6f3b5845ba1f67122e5fbda8d642ecd -> trunk/5cfe4377d6f3b5845ba1f67122e5fbda8d642ecd 2025-07-17T07:01:09.4536317Z * [new tag] trunk/5d5a5b3501dfb0759ed36d0a88b65cdcd87c1e27 -> trunk/5d5a5b3501dfb0759ed36d0a88b65cdcd87c1e27 2025-07-17T07:01:09.4537269Z * [new tag] trunk/5d8d126249f83a9581f6b086f0891753bbb7175e -> trunk/5d8d126249f83a9581f6b086f0891753bbb7175e 2025-07-17T07:01:09.4538906Z * [new tag] trunk/5db9a2b54ae69917753be5b2eef0e15ad3cfd19b -> trunk/5db9a2b54ae69917753be5b2eef0e15ad3cfd19b 2025-07-17T07:01:09.4539793Z * [new tag] trunk/5dc75f72d4ede12067ddca459e02c8ee8a95e02c -> trunk/5dc75f72d4ede12067ddca459e02c8ee8a95e02c 2025-07-17T07:01:09.4540701Z * [new tag] trunk/5dd07c70e53a86b73f49711b8186d86dc4f1b32a -> trunk/5dd07c70e53a86b73f49711b8186d86dc4f1b32a 2025-07-17T07:01:09.4541566Z * [new tag] trunk/5dd9652389ed7959a842323e4ce063f553710e47 -> trunk/5dd9652389ed7959a842323e4ce063f553710e47 2025-07-17T07:01:09.4542919Z * [new tag] trunk/5df3bf13ec4e436abefe9d3822230727c04c2ab7 -> trunk/5df3bf13ec4e436abefe9d3822230727c04c2ab7 2025-07-17T07:01:09.4543872Z * [new tag] trunk/5dfd8a9c7a464bb42e81b8594eefd2fa865e5423 -> trunk/5dfd8a9c7a464bb42e81b8594eefd2fa865e5423 2025-07-17T07:01:09.4544908Z * [new tag] trunk/5dfe1787b5ed372fe1e9f0d73fab4e53a61bd17a -> trunk/5dfe1787b5ed372fe1e9f0d73fab4e53a61bd17a 2025-07-17T07:01:09.4545677Z * [new tag] trunk/5e18bc333144473f1f10bc8a5ba05dba7950fb8a -> trunk/5e18bc333144473f1f10bc8a5ba05dba7950fb8a 2025-07-17T07:01:09.4546659Z * [new tag] trunk/5e636d664ae0ccfdc1f0c5b060eb50fabf56e91b -> trunk/5e636d664ae0ccfdc1f0c5b060eb50fabf56e91b 2025-07-17T07:01:09.4547607Z * [new tag] trunk/5e93abe3c0106cf6fc694a38433909f20ee6a92c -> trunk/5e93abe3c0106cf6fc694a38433909f20ee6a92c 2025-07-17T07:01:09.4548462Z * [new tag] trunk/5eb5c3700bf51015e6a46f9f20c0e0e20cf55ab6 -> trunk/5eb5c3700bf51015e6a46f9f20c0e0e20cf55ab6 2025-07-17T07:01:09.4549457Z * [new tag] trunk/5f1225ef487a4c3954499a8ae5b5a55751e3ef2b -> trunk/5f1225ef487a4c3954499a8ae5b5a55751e3ef2b 2025-07-17T07:01:09.4550285Z * [new tag] trunk/5fb07acbc32874a932cd26087cf752b2f4cc72df -> trunk/5fb07acbc32874a932cd26087cf752b2f4cc72df 2025-07-17T07:01:09.4551971Z * [new tag] trunk/5fbaa041e75af11c7ff892e544707820232bd750 -> trunk/5fbaa041e75af11c7ff892e544707820232bd750 2025-07-17T07:01:09.4552723Z * [new tag] trunk/602044068359a3be08b2030a1bb1efb4dc107767 -> trunk/602044068359a3be08b2030a1bb1efb4dc107767 2025-07-17T07:01:09.4553719Z * [new tag] trunk/603a54a9b33e1aabe1407721d7935b881a160968 -> trunk/603a54a9b33e1aabe1407721d7935b881a160968 2025-07-17T07:01:09.4554722Z * [new tag] trunk/606d73bde495b055984206986fb7dd8918570e89 -> trunk/606d73bde495b055984206986fb7dd8918570e89 2025-07-17T07:01:09.4555660Z * [new tag] trunk/6098209bfffa453ec2cea08b0c9991b3b7e2bfeb -> trunk/6098209bfffa453ec2cea08b0c9991b3b7e2bfeb 2025-07-17T07:01:09.4556517Z * [new tag] trunk/60abb0d3273749cb2a7d583c7c2863bd2819e87e -> trunk/60abb0d3273749cb2a7d583c7c2863bd2819e87e 2025-07-17T07:01:09.4557423Z * [new tag] trunk/60b41de0ca0e5240eccf15c26a2b55b4a34d6f47 -> trunk/60b41de0ca0e5240eccf15c26a2b55b4a34d6f47 2025-07-17T07:01:09.4558414Z * [new tag] trunk/60e66d11ab3d62273cafa7f6b104db7e20f75dfd -> trunk/60e66d11ab3d62273cafa7f6b104db7e20f75dfd 2025-07-17T07:01:09.4559319Z * [new tag] trunk/61712e6f2ba58cce354a742d918934ec7293ee43 -> trunk/61712e6f2ba58cce354a742d918934ec7293ee43 2025-07-17T07:01:09.4560316Z * [new tag] trunk/617e3f69f8479197be57a28cc31e001c3feec407 -> trunk/617e3f69f8479197be57a28cc31e001c3feec407 2025-07-17T07:01:09.4561179Z * [new tag] trunk/61a7b09ef39907b6c4b47445f965c4c77cc6c2ed -> trunk/61a7b09ef39907b6c4b47445f965c4c77cc6c2ed 2025-07-17T07:01:09.4562163Z * [new tag] trunk/61b271e0f3f93209325dea9dccb1e97e7bc16b41 -> trunk/61b271e0f3f93209325dea9dccb1e97e7bc16b41 2025-07-17T07:01:09.4563027Z * [new tag] trunk/61e13782ddddf9e957c984ef11d7bb7643b871e7 -> trunk/61e13782ddddf9e957c984ef11d7bb7643b871e7 2025-07-17T07:01:09.4564062Z * [new tag] trunk/61eaaa21a42398941ea3fb01585a0926e9544831 -> trunk/61eaaa21a42398941ea3fb01585a0926e9544831 2025-07-17T07:01:09.4564958Z * [new tag] trunk/61f6aa36b9f9a168bd3c710c449f0a78c0301972 -> trunk/61f6aa36b9f9a168bd3c710c449f0a78c0301972 2025-07-17T07:01:09.4565979Z * [new tag] trunk/6200584193b770411b7f91880bbff6f746acfcb0 -> trunk/6200584193b770411b7f91880bbff6f746acfcb0 2025-07-17T07:01:09.4566919Z * [new tag] trunk/620415e018cd67e45d5c0a87964aff8751c9bf71 -> trunk/620415e018cd67e45d5c0a87964aff8751c9bf71 2025-07-17T07:01:09.4567860Z * [new tag] trunk/6215e90b7b9af8275c5dbfaa5fd58d7ec08b6764 -> trunk/6215e90b7b9af8275c5dbfaa5fd58d7ec08b6764 2025-07-17T07:01:09.4568718Z * [new tag] trunk/62272d5b24e7f505a02175de3c56ecc287557d2a -> trunk/62272d5b24e7f505a02175de3c56ecc287557d2a 2025-07-17T07:01:09.4569632Z * [new tag] trunk/627ba411366bcc15019c49756d3f22fd3914bd50 -> trunk/627ba411366bcc15019c49756d3f22fd3914bd50 2025-07-17T07:01:09.4570686Z * [new tag] trunk/62fa3f5aebfe763f5de27e687e4c81df7c7080e3 -> trunk/62fa3f5aebfe763f5de27e687e4c81df7c7080e3 2025-07-17T07:01:09.4571764Z * [new tag] trunk/6303cc41b71c02af9c855f3cc85b1146a97fc7a8 -> trunk/6303cc41b71c02af9c855f3cc85b1146a97fc7a8 2025-07-17T07:01:09.4572878Z * [new tag] trunk/63360e64da814de8ce271f1e4b6e2380a03b585e -> trunk/63360e64da814de8ce271f1e4b6e2380a03b585e 2025-07-17T07:01:09.4573642Z * [new tag] trunk/63a96eaeb84f5af6e83c7360c09f5540a44d19ca -> trunk/63a96eaeb84f5af6e83c7360c09f5540a44d19ca 2025-07-17T07:01:09.4574637Z * [new tag] trunk/63e87d6d05dc05ed7cc642c0cf8fd1cd2e3b93a1 -> trunk/63e87d6d05dc05ed7cc642c0cf8fd1cd2e3b93a1 2025-07-17T07:01:09.4575501Z * [new tag] trunk/6401d1d53d13cb2d564d48a30a8cf4f952ff773d -> trunk/6401d1d53d13cb2d564d48a30a8cf4f952ff773d 2025-07-17T07:01:09.4576454Z * [new tag] trunk/640703d95f210876f20f8f16c868442dad17b477 -> trunk/640703d95f210876f20f8f16c868442dad17b477 2025-07-17T07:01:09.4577392Z * [new tag] trunk/640f5a70905b01405f1ce397d25308d3e6a1d421 -> trunk/640f5a70905b01405f1ce397d25308d3e6a1d421 2025-07-17T07:01:09.4578289Z * [new tag] trunk/6442ae9256a6936bc8efe31fc5326d5c1c1f660b -> trunk/6442ae9256a6936bc8efe31fc5326d5c1c1f660b 2025-07-17T07:01:09.4579225Z * [new tag] trunk/64436c38c956b252d8c9f6f68e94fb46c34efdac -> trunk/64436c38c956b252d8c9f6f68e94fb46c34efdac 2025-07-17T07:01:09.4579995Z * [new tag] trunk/644cc58dfffe1b5bd15688495551b49462c163f6 -> trunk/644cc58dfffe1b5bd15688495551b49462c163f6 2025-07-17T07:01:09.4580892Z * [new tag] trunk/64bb6317a57d14c37339d86cded7c6b860c7d638 -> trunk/64bb6317a57d14c37339d86cded7c6b860c7d638 2025-07-17T07:01:09.4581853Z * [new tag] trunk/64f2ec77f869a7d495694519fb482e9ecaaa6da1 -> trunk/64f2ec77f869a7d495694519fb482e9ecaaa6da1 2025-07-17T07:01:09.4582883Z * [new tag] trunk/651b4a68f2a60d55d266e40776709247ef347d68 -> trunk/651b4a68f2a60d55d266e40776709247ef347d68 2025-07-17T07:01:09.4583763Z * [new tag] trunk/653c52fe52254e6783d75a73c3a8abbfd9cd2b3c -> trunk/653c52fe52254e6783d75a73c3a8abbfd9cd2b3c 2025-07-17T07:01:09.4584669Z * [new tag] trunk/655b3b14ffba4ae73e26a63b4289329e8d160a6f -> trunk/655b3b14ffba4ae73e26a63b4289329e8d160a6f 2025-07-17T07:01:09.4585574Z * [new tag] trunk/65b9c13cce43a7a8666ca1ef12b554a5dcfd2492 -> trunk/65b9c13cce43a7a8666ca1ef12b554a5dcfd2492 2025-07-17T07:01:09.4586370Z * [new tag] trunk/65fcca4f8c97de82d35d51ad9b790d10433e9b91 -> trunk/65fcca4f8c97de82d35d51ad9b790d10433e9b91 2025-07-17T07:01:09.4587287Z * [new tag] trunk/660695f11dd73efbe2694be0ed5826e4624f22e4 -> trunk/660695f11dd73efbe2694be0ed5826e4624f22e4 2025-07-17T07:01:09.4588232Z * [new tag] trunk/660dbea909b98f19dc0239a7ae565f8a52cfe846 -> trunk/660dbea909b98f19dc0239a7ae565f8a52cfe846 2025-07-17T07:01:09.4589165Z * [new tag] trunk/6629eaf0c658b523eed47a98c0a3e6b44fd89c6b -> trunk/6629eaf0c658b523eed47a98c0a3e6b44fd89c6b 2025-07-17T07:01:09.4590043Z * [new tag] trunk/662c1cfed2bf3262709f1150fcb11e96bc29e142 -> trunk/662c1cfed2bf3262709f1150fcb11e96bc29e142 2025-07-17T07:01:09.4590955Z * [new tag] trunk/670dab6c630552b32189911f22896ec453e55ab7 -> trunk/670dab6c630552b32189911f22896ec453e55ab7 2025-07-17T07:01:09.4591825Z * [new tag] trunk/671a9d175b7e15b4947c97f50b931dba1cc35a63 -> trunk/671a9d175b7e15b4947c97f50b931dba1cc35a63 2025-07-17T07:01:09.4592763Z * [new tag] trunk/672ac2ec86d8ffe080399363df96597437e51115 -> trunk/672ac2ec86d8ffe080399363df96597437e51115 2025-07-17T07:01:09.4593679Z * [new tag] trunk/67ee0c6725e8dd2d0372ff902775b7040631aaf7 -> trunk/67ee0c6725e8dd2d0372ff902775b7040631aaf7 2025-07-17T07:01:09.4594602Z * [new tag] trunk/67f8270516ef877aec85801e4a8d0b533687e938 -> trunk/67f8270516ef877aec85801e4a8d0b533687e938 2025-07-17T07:01:09.4595409Z * [new tag] trunk/6835ba1b3409d9764c6e704cdc0311d53ea0841a -> trunk/6835ba1b3409d9764c6e704cdc0311d53ea0841a 2025-07-17T07:01:09.4596468Z * [new tag] trunk/68996dc18306ac0320ac5e6979f1a7a7a226b3cc -> trunk/68996dc18306ac0320ac5e6979f1a7a7a226b3cc 2025-07-17T07:01:09.4597305Z * [new tag] trunk/68f36683f0c0dfe7befeba2b65dee30faf88f7cc -> trunk/68f36683f0c0dfe7befeba2b65dee30faf88f7cc 2025-07-17T07:01:09.4598050Z * [new tag] trunk/6918758f554790e1155fe9f3ee4120692347680a -> trunk/6918758f554790e1155fe9f3ee4120692347680a 2025-07-17T07:01:09.4599054Z * [new tag] trunk/693116f765ede6632d3dd8ef3ffe01cc40b960b9 -> trunk/693116f765ede6632d3dd8ef3ffe01cc40b960b9 2025-07-17T07:01:09.4599903Z * [new tag] trunk/694028f50269c9f34721db813e9ee1a8221c99b2 -> trunk/694028f50269c9f34721db813e9ee1a8221c99b2 2025-07-17T07:01:09.4601007Z * [new tag] trunk/6959b5febe090375e261e678902681533d2e2528 -> trunk/6959b5febe090375e261e678902681533d2e2528 2025-07-17T07:01:09.4601941Z * [new tag] trunk/69f2e09cc241176d6128a8f92f9490422c5b81b3 -> trunk/69f2e09cc241176d6128a8f92f9490422c5b81b3 2025-07-17T07:01:09.4603267Z * [new tag] trunk/6a3d00aa3b1e54feeb040891bfe2c59c36b9443c -> trunk/6a3d00aa3b1e54feeb040891bfe2c59c36b9443c 2025-07-17T07:01:09.4604209Z * [new tag] trunk/6abe450a6fda580714a276ed2dd695ab99074b93 -> trunk/6abe450a6fda580714a276ed2dd695ab99074b93 2025-07-17T07:01:09.4605124Z * [new tag] trunk/6b05842e4785f52ab89a8fa2a88f9e6f2316cbbd -> trunk/6b05842e4785f52ab89a8fa2a88f9e6f2316cbbd 2025-07-17T07:01:09.4606139Z * [new tag] trunk/6b1211df294e57d59c1e1717b1fedc671ec5bd5a -> trunk/6b1211df294e57d59c1e1717b1fedc671ec5bd5a 2025-07-17T07:01:09.4607068Z * [new tag] trunk/6b2bef10afae4acb18f230a496392b673c954ce7 -> trunk/6b2bef10afae4acb18f230a496392b673c954ce7 2025-07-17T07:01:09.4607957Z * [new tag] trunk/6b3eef6d316ce33ef0f0416c2f3f6a827ac4fe30 -> trunk/6b3eef6d316ce33ef0f0416c2f3f6a827ac4fe30 2025-07-17T07:01:09.4608860Z * [new tag] trunk/6b45af38a5991134f45d9750b79c767688ba3761 -> trunk/6b45af38a5991134f45d9750b79c767688ba3761 2025-07-17T07:01:09.4609836Z * [new tag] trunk/6b7767fc8d759017b5fc2a7002051cf5c05615a9 -> trunk/6b7767fc8d759017b5fc2a7002051cf5c05615a9 2025-07-17T07:01:09.4610737Z * [new tag] trunk/6b84cb29f97957032c5aa91b4e2a6bfa166db04d -> trunk/6b84cb29f97957032c5aa91b4e2a6bfa166db04d 2025-07-17T07:01:09.4611701Z * [new tag] trunk/6bc263809de610e2fcdf594c122a0f99c6c7d96f -> trunk/6bc263809de610e2fcdf594c122a0f99c6c7d96f 2025-07-17T07:01:09.4612564Z * [new tag] trunk/6c008e2fb5a94342c5c4047d034c61bb067fa2b7 -> trunk/6c008e2fb5a94342c5c4047d034c61bb067fa2b7 2025-07-17T07:01:09.4613496Z * [new tag] trunk/6c05f2fca049344fbbb55eed7a6c866f34c8a477 -> trunk/6c05f2fca049344fbbb55eed7a6c866f34c8a477 2025-07-17T07:01:09.4614397Z * [new tag] trunk/6c0b42fd2f2c070f4c7ef9a3914698726f61ef3a -> trunk/6c0b42fd2f2c070f4c7ef9a3914698726f61ef3a 2025-07-17T07:01:09.4615341Z * [new tag] trunk/6c24c6633a00608d8c20805a77fae55f6b8fe9a6 -> trunk/6c24c6633a00608d8c20805a77fae55f6b8fe9a6 2025-07-17T07:01:09.4616391Z * [new tag] trunk/6c42afe1964496e1b02be1442470f254e35eb199 -> trunk/6c42afe1964496e1b02be1442470f254e35eb199 2025-07-17T07:01:09.4617267Z * [new tag] trunk/6c5227ba00a2904365af566c24b4681cd01a041c -> trunk/6c5227ba00a2904365af566c24b4681cd01a041c 2025-07-17T07:01:09.4618757Z * [new tag] trunk/6c795306378c47341d58109da03371bba2bec46e -> trunk/6c795306378c47341d58109da03371bba2bec46e 2025-07-17T07:01:09.4619712Z * [new tag] trunk/6cc490d40b16b3be7ecc8943fe1bc594246caab3 -> trunk/6cc490d40b16b3be7ecc8943fe1bc594246caab3 2025-07-17T07:01:09.4620640Z * [new tag] trunk/6d02321472ee0761092166dd273eb3ec386cf0c0 -> trunk/6d02321472ee0761092166dd273eb3ec386cf0c0 2025-07-17T07:01:09.4621556Z * [new tag] trunk/6d2155db498375317e2101068a220439dba80939 -> trunk/6d2155db498375317e2101068a220439dba80939 2025-07-17T07:01:09.4622461Z * [new tag] trunk/6d3a4356f61b28a14abd95f641e2615deb186365 -> trunk/6d3a4356f61b28a14abd95f641e2615deb186365 2025-07-17T07:01:09.4623261Z * [new tag] trunk/6d5c789ad5f5d162426a5a10c84813ec923dd8ee -> trunk/6d5c789ad5f5d162426a5a10c84813ec923dd8ee 2025-07-17T07:01:09.4624258Z * [new tag] trunk/6dc2b22269f82a1feec06b5e3e79b184704cc0ba -> trunk/6dc2b22269f82a1feec06b5e3e79b184704cc0ba 2025-07-17T07:01:09.4625165Z * [new tag] trunk/6de41ce0f899604c3f8b33e1f8d37eb89b3a963e -> trunk/6de41ce0f899604c3f8b33e1f8d37eb89b3a963e 2025-07-17T07:01:09.4626105Z * [new tag] trunk/6defd5084e3fd330561095252c30ea50efa8e0ca -> trunk/6defd5084e3fd330561095252c30ea50efa8e0ca 2025-07-17T07:01:09.4627053Z * [new tag] trunk/6dfada220e4f46c28df3a6bdf57260ca0717c4bd -> trunk/6dfada220e4f46c28df3a6bdf57260ca0717c4bd 2025-07-17T07:01:09.4628025Z * [new tag] trunk/6e17315cd33892919dc6deb6a9ecb568dda6195e -> trunk/6e17315cd33892919dc6deb6a9ecb568dda6195e 2025-07-17T07:01:09.4629101Z * [new tag] trunk/6e185c53124e1b5a0fe391959060c1249178bcb6 -> trunk/6e185c53124e1b5a0fe391959060c1249178bcb6 2025-07-17T07:01:09.4630113Z * [new tag] trunk/6e2992a9984f2c3f6469564008c7e45869b84678 -> trunk/6e2992a9984f2c3f6469564008c7e45869b84678 2025-07-17T07:01:09.4631013Z * [new tag] trunk/6ea91f067256447cda6fae533f806c1f8baafbe2 -> trunk/6ea91f067256447cda6fae533f806c1f8baafbe2 2025-07-17T07:01:09.4631813Z * [new tag] trunk/6eb6f198e1a28e904ce00a132c43aa2536419664 -> trunk/6eb6f198e1a28e904ce00a132c43aa2536419664 2025-07-17T07:01:09.4632773Z * [new tag] trunk/6ebe9a4f47e9cd1c9ccd467bcdfdea9445fd98d6 -> trunk/6ebe9a4f47e9cd1c9ccd467bcdfdea9445fd98d6 2025-07-17T07:01:09.4633659Z * [new tag] trunk/6ed85bfe6a1704a87a492a3381414186eb439f5e -> trunk/6ed85bfe6a1704a87a492a3381414186eb439f5e 2025-07-17T07:01:09.4634614Z * [new tag] trunk/6ef70edd9a9acee76a607bdd22bac400c8e29434 -> trunk/6ef70edd9a9acee76a607bdd22bac400c8e29434 2025-07-17T07:01:09.4635546Z * [new tag] trunk/6f05d58f2b0bc4779fbed9db5b0f80af1c686dcd -> trunk/6f05d58f2b0bc4779fbed9db5b0f80af1c686dcd 2025-07-17T07:01:09.4636414Z * [new tag] trunk/6f23f53599629a47d6e097b2a027048658a142d4 -> trunk/6f23f53599629a47d6e097b2a027048658a142d4 2025-07-17T07:01:09.4637355Z * [new tag] trunk/6f60cfe9b1445271f8b83f58b4c4f12578d837d3 -> trunk/6f60cfe9b1445271f8b83f58b4c4f12578d837d3 2025-07-17T07:01:09.4638370Z * [new tag] trunk/6fb62931593fc10252e4994cd1a0595ebf8e990f -> trunk/6fb62931593fc10252e4994cd1a0595ebf8e990f 2025-07-17T07:01:09.4639282Z * [new tag] trunk/6fe7456aa1a2d025d1d06e15ba3896e6adba94b8 -> trunk/6fe7456aa1a2d025d1d06e15ba3896e6adba94b8 2025-07-17T07:01:09.4640265Z * [new tag] trunk/6ffa03ef9e18299f41da076f421abbd32e51e175 -> trunk/6ffa03ef9e18299f41da076f421abbd32e51e175 2025-07-17T07:01:09.4641420Z * [new tag] trunk/702a304b0785d2dfe3d9bd4eed535c38e969818d -> trunk/702a304b0785d2dfe3d9bd4eed535c38e969818d 2025-07-17T07:01:09.4642223Z * [new tag] trunk/706bc41c4c3caa2654a926382c2ef0ef4d0bc55e -> trunk/706bc41c4c3caa2654a926382c2ef0ef4d0bc55e 2025-07-17T07:01:09.4643072Z * [new tag] trunk/706e236b080cadd5b8a016e4bf972cdb0886d57b -> trunk/706e236b080cadd5b8a016e4bf972cdb0886d57b 2025-07-17T07:01:09.4644003Z * [new tag] trunk/7070ab318061d44f195a83b6dc11ef9299603dfe -> trunk/7070ab318061d44f195a83b6dc11ef9299603dfe 2025-07-17T07:01:09.4644963Z * [new tag] trunk/7081b8233a64c350c64e9f00c9b9d00e52020241 -> trunk/7081b8233a64c350c64e9f00c9b9d00e52020241 2025-07-17T07:01:09.4645973Z * [new tag] trunk/70b68caf58815419924ddeda231cbf6535181c53 -> trunk/70b68caf58815419924ddeda231cbf6535181c53 2025-07-17T07:01:09.4647083Z * [new tag] trunk/70bb34929aabc9c11d9ec9bbb53a4f9fc32e5e19 -> trunk/70bb34929aabc9c11d9ec9bbb53a4f9fc32e5e19 2025-07-17T07:01:09.4647896Z * [new tag] trunk/710b92cf3b577036d551708b351b4043817233f5 -> trunk/710b92cf3b577036d551708b351b4043817233f5 2025-07-17T07:01:09.4649027Z * [new tag] trunk/717a099d427d97a62c26fee58f9da9a0893d4233 -> trunk/717a099d427d97a62c26fee58f9da9a0893d4233 2025-07-17T07:01:09.4649992Z * [new tag] trunk/71a650ad565fe75ca752acbc8b40fb9ce677f40f -> trunk/71a650ad565fe75ca752acbc8b40fb9ce677f40f 2025-07-17T07:01:09.4650782Z * [new tag] trunk/720c2c46b181ad446bf970d70a27fd0ce149114d -> trunk/720c2c46b181ad446bf970d70a27fd0ce149114d 2025-07-17T07:01:09.4651746Z * [new tag] trunk/721d2580dbf9a4922adc1c7d1cc8237126d3cdd6 -> trunk/721d2580dbf9a4922adc1c7d1cc8237126d3cdd6 2025-07-17T07:01:09.4652632Z * [new tag] trunk/72453a66769294e93a183dfb5bdefa23de873d89 -> trunk/72453a66769294e93a183dfb5bdefa23de873d89 2025-07-17T07:01:09.4653594Z * [new tag] trunk/725c3272848c408d0fa2cba4de76affe90f793b5 -> trunk/725c3272848c408d0fa2cba4de76affe90f793b5 2025-07-17T07:01:09.4654527Z * [new tag] trunk/7275f280454f790414b24147a2ba7f94d0eabcf6 -> trunk/7275f280454f790414b24147a2ba7f94d0eabcf6 2025-07-17T07:01:09.4655417Z * [new tag] trunk/728cf6721e2996490922d0eacb23081953e45fc7 -> trunk/728cf6721e2996490922d0eacb23081953e45fc7 2025-07-17T07:01:09.4656395Z * [new tag] trunk/72c8751b61e0b2c7b88003a41ed737a65768063c -> trunk/72c8751b61e0b2c7b88003a41ed737a65768063c 2025-07-17T07:01:09.4657334Z * [new tag] trunk/731351bb4ac572fb47d46c70b7425c209c81570a -> trunk/731351bb4ac572fb47d46c70b7425c209c81570a 2025-07-17T07:01:09.4658217Z * [new tag] trunk/73220d52fd67b5f4f5b15e0e0433e09733c93f31 -> trunk/73220d52fd67b5f4f5b15e0e0433e09733c93f31 2025-07-17T07:01:09.4659205Z * [new tag] trunk/73772919d2db560c9cc8ed617c94c77450542a94 -> trunk/73772919d2db560c9cc8ed617c94c77450542a94 2025-07-17T07:01:09.4660030Z * [new tag] trunk/7381c777245a836f88e9622005c6ea16009a3a0d -> trunk/7381c777245a836f88e9622005c6ea16009a3a0d 2025-07-17T07:01:09.4661151Z * [new tag] trunk/7392470da4386e654f303eb526dfba7e7777b06b -> trunk/7392470da4386e654f303eb526dfba7e7777b06b 2025-07-17T07:01:09.4662114Z * [new tag] trunk/7444debaca7de16b2cf71d0cd82dc8998c3a73c4 -> trunk/7444debaca7de16b2cf71d0cd82dc8998c3a73c4 2025-07-17T07:01:09.4663029Z * [new tag] trunk/7485ef078f182af981b5f17d06602de68816492c -> trunk/7485ef078f182af981b5f17d06602de68816492c 2025-07-17T07:01:09.4664512Z * [new tag] trunk/749757ac1b66485459e751b0e58b5a7c64d5f561 -> trunk/749757ac1b66485459e751b0e58b5a7c64d5f561 2025-07-17T07:01:09.4665341Z * [new tag] trunk/74ebd8d14e0d612ed35557ab254a90facf73b029 -> trunk/74ebd8d14e0d612ed35557ab254a90facf73b029 2025-07-17T07:01:09.4666308Z * [new tag] trunk/7521cd91118c1c1a55b8f7146d7e22bf60fe06bf -> trunk/7521cd91118c1c1a55b8f7146d7e22bf60fe06bf 2025-07-17T07:01:09.4667203Z * [new tag] trunk/752f202ef3445d2e28e2abeb6feed56eee9da5a9 -> trunk/752f202ef3445d2e28e2abeb6feed56eee9da5a9 2025-07-17T07:01:09.4668054Z * [new tag] trunk/7531bd64911774fc2656f290601834d5d02d3925 -> trunk/7531bd64911774fc2656f290601834d5d02d3925 2025-07-17T07:01:09.4669000Z * [new tag] trunk/754699610b0abec2fe3f5a73269b1dd09a330445 -> trunk/754699610b0abec2fe3f5a73269b1dd09a330445 2025-07-17T07:01:09.4669916Z * [new tag] trunk/754c04aa062d8f3c0449aec4bbcaab00bfca4bf2 -> trunk/754c04aa062d8f3c0449aec4bbcaab00bfca4bf2 2025-07-17T07:01:09.4670968Z * [new tag] trunk/75824035d392595de3bd0b8588e63c2fc6d09139 -> trunk/75824035d392595de3bd0b8588e63c2fc6d09139 2025-07-17T07:01:09.4675202Z * [new tag] trunk/7597988f1b5a41c0b91d379e0ce51111fd7cc95a -> trunk/7597988f1b5a41c0b91d379e0ce51111fd7cc95a 2025-07-17T07:01:09.4676315Z * [new tag] trunk/7599bebead35dd21bad3d3e85f62f400ad2c3139 -> trunk/7599bebead35dd21bad3d3e85f62f400ad2c3139 2025-07-17T07:01:09.4677196Z * [new tag] trunk/75a7d9e86842b57f9001a0fa6fd716927614dbf9 -> trunk/75a7d9e86842b57f9001a0fa6fd716927614dbf9 2025-07-17T07:01:09.4678040Z * [new tag] trunk/75f258dd1feeb90b8084849155e049fb57ba3521 -> trunk/75f258dd1feeb90b8084849155e049fb57ba3521 2025-07-17T07:01:09.4678942Z * [new tag] trunk/75f3e5a88df60caef27fd9c9df3fd51161378fcc -> trunk/75f3e5a88df60caef27fd9c9df3fd51161378fcc 2025-07-17T07:01:09.4679895Z * [new tag] trunk/75f489d37f048ec8a9106163ca16201156f05499 -> trunk/75f489d37f048ec8a9106163ca16201156f05499 2025-07-17T07:01:09.4680843Z * [new tag] trunk/764c02b78b935ba61c46277cb7409e6419460058 -> trunk/764c02b78b935ba61c46277cb7409e6419460058 2025-07-17T07:01:09.4681738Z * [new tag] trunk/76644c9ff58285c95764ffd27d629df219aab140 -> trunk/76644c9ff58285c95764ffd27d629df219aab140 2025-07-17T07:01:09.4682750Z * [new tag] trunk/769d754ab2469813a3b790ec58c25c466099dd3d -> trunk/769d754ab2469813a3b790ec58c25c466099dd3d 2025-07-17T07:01:09.4683962Z * [new tag] trunk/76ca23c41c7edcf7b4c60ff6162eedcdf06ef359 -> trunk/76ca23c41c7edcf7b4c60ff6162eedcdf06ef359 2025-07-17T07:01:09.4684852Z * [new tag] trunk/76d07e919f66c24a55746bbc060c14b3df02ffa8 -> trunk/76d07e919f66c24a55746bbc060c14b3df02ffa8 2025-07-17T07:01:09.4685794Z * [new tag] trunk/76fe88fa56c8aac7377127fb5553de94e16e9070 -> trunk/76fe88fa56c8aac7377127fb5553de94e16e9070 2025-07-17T07:01:09.4686769Z * [new tag] trunk/770285522805745959221b902f23776a13d56df8 -> trunk/770285522805745959221b902f23776a13d56df8 2025-07-17T07:01:09.4687733Z * [new tag] trunk/7709ff55123dbdcaaa44004738fb767324f05dbd -> trunk/7709ff55123dbdcaaa44004738fb767324f05dbd 2025-07-17T07:01:09.4688681Z * [new tag] trunk/771be857043bf794cd219a9b925e308e31f12314 -> trunk/771be857043bf794cd219a9b925e308e31f12314 2025-07-17T07:01:09.4690553Z * [new tag] trunk/772d5904152abc9702bf49037e46ab6203b83f55 -> trunk/772d5904152abc9702bf49037e46ab6203b83f55 2025-07-17T07:01:09.4691297Z * [new tag] trunk/77518d1a13cc105637814bc157387478384dc897 -> trunk/77518d1a13cc105637814bc157387478384dc897 2025-07-17T07:01:09.4692294Z * [new tag] trunk/77676753ecabf6a6645bdd3abfe01939e5751e76 -> trunk/77676753ecabf6a6645bdd3abfe01939e5751e76 2025-07-17T07:01:09.4693319Z * [new tag] trunk/777eca9f16aeecd7c362a235cf25e6b8e6eda57f -> trunk/777eca9f16aeecd7c362a235cf25e6b8e6eda57f 2025-07-17T07:01:09.4694285Z * [new tag] trunk/77ac3a096532ee08211dae38c2a9336c970d1785 -> trunk/77ac3a096532ee08211dae38c2a9336c970d1785 2025-07-17T07:01:09.4695178Z * [new tag] trunk/77f884c2ec62df9df930ae86e9b8437364900346 -> trunk/77f884c2ec62df9df930ae86e9b8437364900346 2025-07-17T07:01:09.4696064Z * [new tag] trunk/783a4c1f5002bf1749833821c450360a417d40c7 -> trunk/783a4c1f5002bf1749833821c450360a417d40c7 2025-07-17T07:01:09.4696927Z * [new tag] trunk/78684e27ace1ebd51ccc93d4b6b8a6a3ec3b4c14 -> trunk/78684e27ace1ebd51ccc93d4b6b8a6a3ec3b4c14 2025-07-17T07:01:09.4697870Z * [new tag] trunk/78ee2ee90eed957aec3dc80423b108b16938a8ae -> trunk/78ee2ee90eed957aec3dc80423b108b16938a8ae 2025-07-17T07:01:09.4698779Z * [new tag] trunk/7918978653ff4f21c284b34809acf88784deb0de -> trunk/7918978653ff4f21c284b34809acf88784deb0de 2025-07-17T07:01:09.4699710Z * [new tag] trunk/794b95d54bb2c49d704169ddb777acfd8da8cfad -> trunk/794b95d54bb2c49d704169ddb777acfd8da8cfad 2025-07-17T07:01:09.4700669Z * [new tag] trunk/794ef6c9b8f173a0cbab5288efb2d68aef9c90b9 -> trunk/794ef6c9b8f173a0cbab5288efb2d68aef9c90b9 2025-07-17T07:01:09.4701538Z * [new tag] trunk/795a6a0affd349adfb4e3df298b604b74f27b44e -> trunk/795a6a0affd349adfb4e3df298b604b74f27b44e 2025-07-17T07:01:09.4702377Z * [new tag] trunk/7982b8c703e24a36c0e0a01b8cf22cd272369b28 -> trunk/7982b8c703e24a36c0e0a01b8cf22cd272369b28 2025-07-17T07:01:09.4703174Z * [new tag] trunk/7986c0dba6e1044d90b7f607f9cca15922339bb4 -> trunk/7986c0dba6e1044d90b7f607f9cca15922339bb4 2025-07-17T07:01:09.4704068Z * [new tag] trunk/799443605bffbd0d80fb3f2edbfe5517e0e2b4a3 -> trunk/799443605bffbd0d80fb3f2edbfe5517e0e2b4a3 2025-07-17T07:01:09.4705003Z * [new tag] trunk/7999735d23aeca844d4a7b23de6ac2370767099a -> trunk/7999735d23aeca844d4a7b23de6ac2370767099a 2025-07-17T07:01:09.4705954Z * [new tag] trunk/79ab84e9b8fe561a55931b2108af45993a670276 -> trunk/79ab84e9b8fe561a55931b2108af45993a670276 2025-07-17T07:01:09.4706912Z * [new tag] trunk/79aef141695f2daea4a9aeb0f385726c5794a242 -> trunk/79aef141695f2daea4a9aeb0f385726c5794a242 2025-07-17T07:01:09.4707828Z * [new tag] trunk/79bdafe5b61f6f073dcd276e135076ff3277a951 -> trunk/79bdafe5b61f6f073dcd276e135076ff3277a951 2025-07-17T07:01:09.4708861Z * [new tag] trunk/79d7c754ab8ae0e5c3a614521632d2cfbfa0fdba -> trunk/79d7c754ab8ae0e5c3a614521632d2cfbfa0fdba 2025-07-17T07:01:09.4709838Z * [new tag] trunk/7a03b0d2ca3946b770bc817571fc36bd5c608b38 -> trunk/7a03b0d2ca3946b770bc817571fc36bd5c608b38 2025-07-17T07:01:09.4710699Z * [new tag] trunk/7a08755c5f3630150c50d09e16c0abf9501dea1e -> trunk/7a08755c5f3630150c50d09e16c0abf9501dea1e 2025-07-17T07:01:09.4711924Z * [new tag] trunk/7a41f207943cc6c88160d7a531fc57bdbe149253 -> trunk/7a41f207943cc6c88160d7a531fc57bdbe149253 2025-07-17T07:01:09.4712848Z * [new tag] trunk/7a48cc699006879a6ec185ac5bd4eaad0c0b7e36 -> trunk/7a48cc699006879a6ec185ac5bd4eaad0c0b7e36 2025-07-17T07:01:09.4713870Z * [new tag] trunk/7a92b5119654c07d15f5c0818e6ae804b01e836c -> trunk/7a92b5119654c07d15f5c0818e6ae804b01e836c 2025-07-17T07:01:09.4714727Z * [new tag] trunk/7ae7c1414354ad225c4a36b3228e30a2baf94923 -> trunk/7ae7c1414354ad225c4a36b3228e30a2baf94923 2025-07-17T07:01:09.4715769Z * [new tag] trunk/7afb834f939eccbb3262e646f0922eed070074a7 -> trunk/7afb834f939eccbb3262e646f0922eed070074a7 2025-07-17T07:01:09.4716671Z * [new tag] trunk/7b0118884e0855e4918af53d44c3fbfc185a1ee9 -> trunk/7b0118884e0855e4918af53d44c3fbfc185a1ee9 2025-07-17T07:01:09.4717650Z * [new tag] trunk/7b392bac13a8007d1e0c6c789aa9bc515119faba -> trunk/7b392bac13a8007d1e0c6c789aa9bc515119faba 2025-07-17T07:01:09.4718718Z * [new tag] trunk/7b7cd56f5e2a965ae8a48c69441dd4f58bf68ceb -> trunk/7b7cd56f5e2a965ae8a48c69441dd4f58bf68ceb 2025-07-17T07:01:09.4719640Z * [new tag] trunk/7be862ab8f2b9040b34c58e1b77ce74c2512f062 -> trunk/7be862ab8f2b9040b34c58e1b77ce74c2512f062 2025-07-17T07:01:09.4720675Z * [new tag] trunk/7c1f62782875a4ac70b96aed0e6c9525b6e4eaf3 -> trunk/7c1f62782875a4ac70b96aed0e6c9525b6e4eaf3 2025-07-17T07:01:09.4721523Z * [new tag] trunk/7c51619e7fbd346e2299255c468cc43bd69425d7 -> trunk/7c51619e7fbd346e2299255c468cc43bd69425d7 2025-07-17T07:01:09.4722486Z * [new tag] trunk/7caf6c801ddfaf556a3ca191173b50002c4261f4 -> trunk/7caf6c801ddfaf556a3ca191173b50002c4261f4 2025-07-17T07:01:09.4723440Z * [new tag] trunk/7cda4017ddda554752e89069ae205be5e8388f59 -> trunk/7cda4017ddda554752e89069ae205be5e8388f59 2025-07-17T07:01:09.4724522Z * [new tag] trunk/7cf31b4a426f3791af30159cea420687f347cd7a -> trunk/7cf31b4a426f3791af30159cea420687f347cd7a 2025-07-17T07:01:09.4725559Z * [new tag] trunk/7cf38d2a0521c5ca292a720bce00617be749a0e7 -> trunk/7cf38d2a0521c5ca292a720bce00617be749a0e7 2025-07-17T07:01:09.4726617Z * [new tag] trunk/7cfd054075b0713642fab8dc4313fc1e5d992599 -> trunk/7cfd054075b0713642fab8dc4313fc1e5d992599 2025-07-17T07:01:09.4727681Z * [new tag] trunk/7d1b3f599d6968a3efe70b7401310e3127949f13 -> trunk/7d1b3f599d6968a3efe70b7401310e3127949f13 2025-07-17T07:01:09.4728694Z * [new tag] trunk/7d4228dbfd13d1ac8fac2c78c042dbb8314f042d -> trunk/7d4228dbfd13d1ac8fac2c78c042dbb8314f042d 2025-07-17T07:01:09.4730205Z * [new tag] trunk/7dcc77e422dcf97ce35991a138ab635a5cb88731 -> trunk/7dcc77e422dcf97ce35991a138ab635a5cb88731 2025-07-17T07:01:09.4730977Z * [new tag] trunk/7e433d5f423248914c5e9838d3ea145db7964923 -> trunk/7e433d5f423248914c5e9838d3ea145db7964923 2025-07-17T07:01:09.4731970Z * [new tag] trunk/7e4c097b0752ae79a8b5dd1de21a51aaafba2ef9 -> trunk/7e4c097b0752ae79a8b5dd1de21a51aaafba2ef9 2025-07-17T07:01:09.4732840Z * [new tag] trunk/7e54c02a35b905e758497b856a1953eb009ba836 -> trunk/7e54c02a35b905e758497b856a1953eb009ba836 2025-07-17T07:01:09.4734995Z * [new tag] trunk/7e83d5084588bdb51151f869b53c92c07bc9f544 -> trunk/7e83d5084588bdb51151f869b53c92c07bc9f544 2025-07-17T07:01:09.4735848Z * [new tag] trunk/7f0cddfb55d426b414cf7b4482c6a371618b349c -> trunk/7f0cddfb55d426b414cf7b4482c6a371618b349c 2025-07-17T07:01:09.4736689Z * [new tag] trunk/7f14b42adf70196d82340c59a9981ffcadf0c53c -> trunk/7f14b42adf70196d82340c59a9981ffcadf0c53c 2025-07-17T07:01:09.4737585Z * [new tag] trunk/7f6e7103a3aefd2d96b3cc6702be931a66b44977 -> trunk/7f6e7103a3aefd2d96b3cc6702be931a66b44977 2025-07-17T07:01:09.4738514Z * [new tag] trunk/7f9fc7e67ce9853a1bb4b16c901c708f78c1c5cd -> trunk/7f9fc7e67ce9853a1bb4b16c901c708f78c1c5cd 2025-07-17T07:01:09.4739486Z * [new tag] trunk/7fcad0231cb0ae9ba6a0004098b5ffd82c62858f -> trunk/7fcad0231cb0ae9ba6a0004098b5ffd82c62858f 2025-07-17T07:01:09.4740321Z * [new tag] trunk/805297981ae4e2aa08d133161477a477f5da274f -> trunk/805297981ae4e2aa08d133161477a477f5da274f 2025-07-17T07:01:09.4741264Z * [new tag] trunk/8088958793841191eba1faf98849904ee769bbfd -> trunk/8088958793841191eba1faf98849904ee769bbfd 2025-07-17T07:01:09.4742316Z * [new tag] trunk/80bcaa4195944d0f00f16abcbb702bde4d582d14 -> trunk/80bcaa4195944d0f00f16abcbb702bde4d582d14 2025-07-17T07:01:09.4743356Z * [new tag] trunk/80d89974c173c9d7a2c59fe9dfce2fe1301e2833 -> trunk/80d89974c173c9d7a2c59fe9dfce2fe1301e2833 2025-07-17T07:01:09.4744293Z * [new tag] trunk/8134684d44f3f9d09e775f3adc513bdef72245c9 -> trunk/8134684d44f3f9d09e775f3adc513bdef72245c9 2025-07-17T07:01:09.4745187Z * [new tag] trunk/8142a0286016e63a0e91b5667e1fb1a5e868ffd7 -> trunk/8142a0286016e63a0e91b5667e1fb1a5e868ffd7 2025-07-17T07:01:09.4746214Z * [new tag] trunk/8147c4a9044913e62ba3aab7f1eaaafead4f5930 -> trunk/8147c4a9044913e62ba3aab7f1eaaafead4f5930 2025-07-17T07:01:09.4747087Z * [new tag] trunk/8153340d1073c190ecf221e51abbd983286782a8 -> trunk/8153340d1073c190ecf221e51abbd983286782a8 2025-07-17T07:01:09.4748019Z * [new tag] trunk/815545f2dd6ade563cb1263f8bb7813f355edb2e -> trunk/815545f2dd6ade563cb1263f8bb7813f355edb2e 2025-07-17T07:01:09.4748955Z * [new tag] trunk/81759afed4fa4fa3a03f9ff671abe270679cc006 -> trunk/81759afed4fa4fa3a03f9ff671abe270679cc006 2025-07-17T07:01:09.4749874Z * [new tag] trunk/8186af5a26bc6a628f283c4791c8d68ef6fa1336 -> trunk/8186af5a26bc6a628f283c4791c8d68ef6fa1336 2025-07-17T07:01:09.4750809Z * [new tag] trunk/81b0b308cafae44339b8a123e8b1bec3bf9eb8ad -> trunk/81b0b308cafae44339b8a123e8b1bec3bf9eb8ad 2025-07-17T07:01:09.4751656Z * [new tag] trunk/81bf278537c081279a574157e1359ec7f0b65daf -> trunk/81bf278537c081279a574157e1359ec7f0b65daf 2025-07-17T07:01:09.4752531Z * [new tag] trunk/81c7445eb97f910ed89da9b11140d914651a1675 -> trunk/81c7445eb97f910ed89da9b11140d914651a1675 2025-07-17T07:01:09.4753535Z * [new tag] trunk/82672206b724a767dcb8c2541074449100de701b -> trunk/82672206b724a767dcb8c2541074449100de701b 2025-07-17T07:01:09.4754311Z * [new tag] trunk/826f12b829070e3d5bfd050f001b61aaf78e5447 -> trunk/826f12b829070e3d5bfd050f001b61aaf78e5447 2025-07-17T07:01:09.4755208Z * [new tag] trunk/82765dad16d7cda1ea382497dbf8c1ab2d07bfdd -> trunk/82765dad16d7cda1ea382497dbf8c1ab2d07bfdd 2025-07-17T07:01:09.4756185Z * [new tag] trunk/82a1ee1135b054d371d10081883b848ac7b7419f -> trunk/82a1ee1135b054d371d10081883b848ac7b7419f 2025-07-17T07:01:09.4757130Z * [new tag] trunk/82e6475d920991ef3be5d5637a72bf49313cc604 -> trunk/82e6475d920991ef3be5d5637a72bf49313cc604 2025-07-17T07:01:09.4757951Z * [new tag] trunk/82eefaedd98b63de8a87e34275af781f8eb177e1 -> trunk/82eefaedd98b63de8a87e34275af781f8eb177e1 2025-07-17T07:01:09.4758687Z * [new tag] trunk/82fb904140d258604a185154287b9c6fde047fc5 -> trunk/82fb904140d258604a185154287b9c6fde047fc5 2025-07-17T07:01:09.4759650Z * [new tag] trunk/830a335a7da5fec00395d440ba568749cb4e2e9e -> trunk/830a335a7da5fec00395d440ba568749cb4e2e9e 2025-07-17T07:01:09.4760513Z * [new tag] trunk/831c9010c7d7460fd78bc59b3fa28a65a0339e5d -> trunk/831c9010c7d7460fd78bc59b3fa28a65a0339e5d 2025-07-17T07:01:09.4761474Z * [new tag] trunk/8347268edcf3cc4f638474d860450bb0cd7a9908 -> trunk/8347268edcf3cc4f638474d860450bb0cd7a9908 2025-07-17T07:01:09.4762343Z * [new tag] trunk/836bb1941b593063f002394c1de3ec382c2ce50e -> trunk/836bb1941b593063f002394c1de3ec382c2ce50e 2025-07-17T07:01:09.4763235Z * [new tag] trunk/83700b448874cac8e89356ab06292e4289577269 -> trunk/83700b448874cac8e89356ab06292e4289577269 2025-07-17T07:01:09.4764172Z * [new tag] trunk/8372d0986a495d41f41c5d7684f1428ff847c699 -> trunk/8372d0986a495d41f41c5d7684f1428ff847c699 2025-07-17T07:01:09.4765478Z * [new tag] trunk/838798425731e6c90df4a885e90ec03f18eea10b -> trunk/838798425731e6c90df4a885e90ec03f18eea10b 2025-07-17T07:01:09.4766267Z * [new tag] trunk/83d22256f84232c5440b25a08459c649a32b9a4f -> trunk/83d22256f84232c5440b25a08459c649a32b9a4f 2025-07-17T07:01:09.4767255Z * [new tag] trunk/84085229765698166f07c9220d5544023ab80d47 -> trunk/84085229765698166f07c9220d5544023ab80d47 2025-07-17T07:01:09.4768203Z * [new tag] trunk/8485f1950710d383fd8d0d772fc978933c6fc175 -> trunk/8485f1950710d383fd8d0d772fc978933c6fc175 2025-07-17T07:01:09.4769071Z * [new tag] trunk/84b77ec1280a56bece8408a2e0e179b9eb95e1e2 -> trunk/84b77ec1280a56bece8408a2e0e179b9eb95e1e2 2025-07-17T07:01:09.4770081Z * [new tag] trunk/84c14361c28e1b553ea405ef5020cf0a90468850 -> trunk/84c14361c28e1b553ea405ef5020cf0a90468850 2025-07-17T07:01:09.4770970Z * [new tag] trunk/84c588e5eada9e7921608065edc444a15c22cb1c -> trunk/84c588e5eada9e7921608065edc444a15c22cb1c 2025-07-17T07:01:09.4771969Z * [new tag] trunk/84dec060b79078e68dcb6be1e7f308dad05d00e2 -> trunk/84dec060b79078e68dcb6be1e7f308dad05d00e2 2025-07-17T07:01:09.4772867Z * [new tag] trunk/85111cd165f108ffabb4a90083d59d7a867ebd9f -> trunk/85111cd165f108ffabb4a90083d59d7a867ebd9f 2025-07-17T07:01:09.4773789Z * [new tag] trunk/851a6fa82df251fbc368f0284d941ce78f68e7b1 -> trunk/851a6fa82df251fbc368f0284d941ce78f68e7b1 2025-07-17T07:01:09.4774655Z * [new tag] trunk/85320336799e38411d15c0e159b41248cda01218 -> trunk/85320336799e38411d15c0e159b41248cda01218 2025-07-17T07:01:09.4775843Z * [new tag] trunk/8554c8007ddaa8029e7e01bb1af12f358bf597c2 -> trunk/8554c8007ddaa8029e7e01bb1af12f358bf597c2 2025-07-17T07:01:09.4776828Z * [new tag] trunk/85857181ebca86e9c709e9922a9d9ef41a9c4ef9 -> trunk/85857181ebca86e9c709e9922a9d9ef41a9c4ef9 2025-07-17T07:01:09.4777856Z * [new tag] trunk/85df746892d9b0e87e7a5dfa78ef81a84aec6de0 -> trunk/85df746892d9b0e87e7a5dfa78ef81a84aec6de0 2025-07-17T07:01:09.4778642Z * [new tag] trunk/86251eff4069c468efebdb481dd18fe8d42856f0 -> trunk/86251eff4069c468efebdb481dd18fe8d42856f0 2025-07-17T07:01:09.4779542Z * [new tag] trunk/863327ae496471654344e1e04ccaa713a44a135d -> trunk/863327ae496471654344e1e04ccaa713a44a135d 2025-07-17T07:01:09.4780445Z * [new tag] trunk/86670b39fa3df63a652a9a06b59b73f92d70c392 -> trunk/86670b39fa3df63a652a9a06b59b73f92d70c392 2025-07-17T07:01:09.4781614Z * [new tag] trunk/86996c15dc4294c400c3a552d1a9e8e90aa6c7f6 -> trunk/86996c15dc4294c400c3a552d1a9e8e90aa6c7f6 2025-07-17T07:01:09.4782517Z * [new tag] trunk/86ced144534c2c78460a2d0f1d9ed2ba048f2514 -> trunk/86ced144534c2c78460a2d0f1d9ed2ba048f2514 2025-07-17T07:01:09.4783458Z * [new tag] trunk/86d8af6a6cc648134289de89d393d0dce5b3a5f4 -> trunk/86d8af6a6cc648134289de89d393d0dce5b3a5f4 2025-07-17T07:01:09.4784440Z * [new tag] trunk/86eaf452c330bd871262b7590ff8bd1bf432e2d7 -> trunk/86eaf452c330bd871262b7590ff8bd1bf432e2d7 2025-07-17T07:01:09.4785380Z * [new tag] trunk/87d615efab194482a00d241e4d9aebc513635cf5 -> trunk/87d615efab194482a00d241e4d9aebc513635cf5 2025-07-17T07:01:09.4786242Z * [new tag] trunk/8823138e47a3200c313f6bf2d21eb689d8150f39 -> trunk/8823138e47a3200c313f6bf2d21eb689d8150f39 2025-07-17T07:01:09.4787130Z * [new tag] trunk/8892b782a85b9de9f51334e65e009b3d59899b02 -> trunk/8892b782a85b9de9f51334e65e009b3d59899b02 2025-07-17T07:01:09.4788061Z * [new tag] trunk/88b9c285e0eb68134c5f834ceccdb99bc1d255d0 -> trunk/88b9c285e0eb68134c5f834ceccdb99bc1d255d0 2025-07-17T07:01:09.4788919Z * [new tag] trunk/88c6199db09372b6e2d55a5349ab545527842727 -> trunk/88c6199db09372b6e2d55a5349ab545527842727 2025-07-17T07:01:09.4789915Z * [new tag] trunk/88cd9f34b00c22e4edefa223490fcdd6c4ff272a -> trunk/88cd9f34b00c22e4edefa223490fcdd6c4ff272a 2025-07-17T07:01:09.4791180Z * [new tag] trunk/898179331e82e5ee1ff64737f508fd6a6da711f9 -> trunk/898179331e82e5ee1ff64737f508fd6a6da711f9 2025-07-17T07:01:09.4792467Z * [new tag] trunk/899d3d3e9eec4756a2e759f0203334dbe08f664e -> trunk/899d3d3e9eec4756a2e759f0203334dbe08f664e 2025-07-17T07:01:09.4793383Z * [new tag] trunk/8a2255130025abc80e03adaeb0b90d6463f2f916 -> trunk/8a2255130025abc80e03adaeb0b90d6463f2f916 2025-07-17T07:01:09.4794257Z * [new tag] trunk/8a396c56350ade97c18a6e13b3d97939f1eea075 -> trunk/8a396c56350ade97c18a6e13b3d97939f1eea075 2025-07-17T07:01:09.4795100Z * [new tag] trunk/8a47f9d03be0e0118a43443ff5f60db7be85102b -> trunk/8a47f9d03be0e0118a43443ff5f60db7be85102b 2025-07-17T07:01:09.4796040Z * [new tag] trunk/8a88c6e85abe345d95d970d424a0295cbc89b69c -> trunk/8a88c6e85abe345d95d970d424a0295cbc89b69c 2025-07-17T07:01:09.4796954Z * [new tag] trunk/8a8fac11318778aa5e4479b369b37fdb9e10ec17 -> trunk/8a8fac11318778aa5e4479b369b37fdb9e10ec17 2025-07-17T07:01:09.4797951Z * [new tag] trunk/8ad6197b466e91eb5fbbde2c76688d40fa472ac3 -> trunk/8ad6197b466e91eb5fbbde2c76688d40fa472ac3 2025-07-17T07:01:09.4798868Z * [new tag] trunk/8b0e0e4f2301f4aeb9fccf52cd2c6d8ac13da131 -> trunk/8b0e0e4f2301f4aeb9fccf52cd2c6d8ac13da131 2025-07-17T07:01:09.4799718Z * [new tag] trunk/8b68e5b1bb4a0014a64eab25c54b716968e109a9 -> trunk/8b68e5b1bb4a0014a64eab25c54b716968e109a9 2025-07-17T07:01:09.4800651Z * [new tag] trunk/8b8684466a11ae6ac27c85dbc6a02091dadac749 -> trunk/8b8684466a11ae6ac27c85dbc6a02091dadac749 2025-07-17T07:01:09.4801532Z * [new tag] trunk/8b97e4dd8cbe23101801043fe343d7350e527540 -> trunk/8b97e4dd8cbe23101801043fe343d7350e527540 2025-07-17T07:01:09.4802588Z * [new tag] trunk/8bda95228fbefa6ce204bf4da8b632d1516431bb -> trunk/8bda95228fbefa6ce204bf4da8b632d1516431bb 2025-07-17T07:01:09.4803569Z * [new tag] trunk/8c0df6fe1769c813f57da766528ff3cc4e56943e -> trunk/8c0df6fe1769c813f57da766528ff3cc4e56943e 2025-07-17T07:01:09.4804478Z * [new tag] trunk/8c2e45008282cf5202b72a0ecb0c2951438abeea -> trunk/8c2e45008282cf5202b72a0ecb0c2951438abeea 2025-07-17T07:01:09.4805536Z * [new tag] trunk/8c3f206457a1b9d75bc95a6c30a101135fcee329 -> trunk/8c3f206457a1b9d75bc95a6c30a101135fcee329 2025-07-17T07:01:09.4806641Z * [new tag] trunk/8c5b070d1f7cf4a9b58b09a28a0aeb5fdca28679 -> trunk/8c5b070d1f7cf4a9b58b09a28a0aeb5fdca28679 2025-07-17T07:01:09.4807552Z * [new tag] trunk/8c928372b3560bb512e2cf98c94efd923caf5fa7 -> trunk/8c928372b3560bb512e2cf98c94efd923caf5fa7 2025-07-17T07:01:09.4808563Z * [new tag] trunk/8cb0c4a4da0e017834d63f3d7dc2ab29e0ad6424 -> trunk/8cb0c4a4da0e017834d63f3d7dc2ab29e0ad6424 2025-07-17T07:01:09.4809402Z * [new tag] trunk/8d070187e34d5474ae88cefe56754f729138756b -> trunk/8d070187e34d5474ae88cefe56754f729138756b 2025-07-17T07:01:09.4810294Z * [new tag] trunk/8d7ee0f4fb7e41e8a49a5a24b6686b2324c493ba -> trunk/8d7ee0f4fb7e41e8a49a5a24b6686b2324c493ba 2025-07-17T07:01:09.4811190Z * [new tag] trunk/8da774d81feace041ff39de4ba2ddd43086370d3 -> trunk/8da774d81feace041ff39de4ba2ddd43086370d3 2025-07-17T07:01:09.4812046Z * [new tag] trunk/8dff457f42c9a20f9936d22773239df33cb48c9d -> trunk/8dff457f42c9a20f9936d22773239df33cb48c9d 2025-07-17T07:01:09.4812987Z * [new tag] trunk/8e02cd9c5ab151faad80e18e648c82a204fc3735 -> trunk/8e02cd9c5ab151faad80e18e648c82a204fc3735 2025-07-17T07:01:09.4813920Z * [new tag] trunk/8e8bbfc80340f0bf0a31a03d61b9b4dd72a40469 -> trunk/8e8bbfc80340f0bf0a31a03d61b9b4dd72a40469 2025-07-17T07:01:09.4814680Z * [new tag] trunk/8e8d4b13b0f6358e249a1e6fea9831b91b41b6d0 -> trunk/8e8d4b13b0f6358e249a1e6fea9831b91b41b6d0 2025-07-17T07:01:09.4815735Z * [new tag] trunk/8eaa9f2701277f328d9d6aea1bfe7cba20792f7c -> trunk/8eaa9f2701277f328d9d6aea1bfe7cba20792f7c 2025-07-17T07:01:09.4816663Z * [new tag] trunk/8eb3c5b7a18205974fff0353b97e599ea3d0e2a4 -> trunk/8eb3c5b7a18205974fff0353b97e599ea3d0e2a4 2025-07-17T07:01:09.4817622Z * [new tag] trunk/8f02161d1012143263fdbca47ee62983448e2c7e -> trunk/8f02161d1012143263fdbca47ee62983448e2c7e 2025-07-17T07:01:09.4818555Z * [new tag] trunk/8f0998aafe5e9594ade50cd263d5c63a5aad9333 -> trunk/8f0998aafe5e9594ade50cd263d5c63a5aad9333 2025-07-17T07:01:09.4819481Z * [new tag] trunk/8f5f01bf19e01f4b74add7f3d558966152a398c7 -> trunk/8f5f01bf19e01f4b74add7f3d558966152a398c7 2025-07-17T07:01:09.4820402Z * [new tag] trunk/8f9a191db6efcf44510db87c8f6f6e96c67e9b11 -> trunk/8f9a191db6efcf44510db87c8f6f6e96c67e9b11 2025-07-17T07:01:09.4821308Z * [new tag] trunk/8fcda2c60d974e4970ce939bc828bece9903c304 -> trunk/8fcda2c60d974e4970ce939bc828bece9903c304 2025-07-17T07:01:09.4822112Z * [new tag] trunk/900fba4c073b121b6c9ce581ea27e25c13a354e5 -> trunk/900fba4c073b121b6c9ce581ea27e25c13a354e5 2025-07-17T07:01:09.4823027Z * [new tag] trunk/9056279f8159b052599a31b591a78da1acc4224c -> trunk/9056279f8159b052599a31b591a78da1acc4224c 2025-07-17T07:01:09.4824026Z * [new tag] trunk/905b0846903a0193ee651a44762e72c881f83950 -> trunk/905b0846903a0193ee651a44762e72c881f83950 2025-07-17T07:01:09.4825079Z * [new tag] trunk/905b194a2e3d1d1c9ec136dfc1b6be7e62ff4b2c -> trunk/905b194a2e3d1d1c9ec136dfc1b6be7e62ff4b2c 2025-07-17T07:01:09.4825924Z * [new tag] trunk/90618581e971d28ac6950305d72521af05ed3a42 -> trunk/90618581e971d28ac6950305d72521af05ed3a42 2025-07-17T07:01:09.4826796Z * [new tag] trunk/907aea032d2f709f26dec78b762481c4604cc186 -> trunk/907aea032d2f709f26dec78b762481c4604cc186 2025-07-17T07:01:09.4827799Z * [new tag] trunk/907d0931cc8868164c2890b0452eda5d4da49278 -> trunk/907d0931cc8868164c2890b0452eda5d4da49278 2025-07-17T07:01:09.4828814Z * [new tag] trunk/90b973a2e228f2a5e2c158e5f5cf8f59d9118fc8 -> trunk/90b973a2e228f2a5e2c158e5f5cf8f59d9118fc8 2025-07-17T07:01:09.4829719Z * [new tag] trunk/91ee9ee82d40bcc36afbe9fed8dfc2f8c19c7316 -> trunk/91ee9ee82d40bcc36afbe9fed8dfc2f8c19c7316 2025-07-17T07:01:09.4830637Z * [new tag] trunk/9222552572890fd7ff1d75884cc6a99a55ab90bc -> trunk/9222552572890fd7ff1d75884cc6a99a55ab90bc 2025-07-17T07:01:09.4831572Z * [new tag] trunk/92388bb2ab14dae7b63c2088de4d6add413d1c27 -> trunk/92388bb2ab14dae7b63c2088de4d6add413d1c27 2025-07-17T07:01:09.4832668Z * [new tag] trunk/92409b6c89fbfbd3caa79c81b1e3d9e7917d3bc7 -> trunk/92409b6c89fbfbd3caa79c81b1e3d9e7917d3bc7 2025-07-17T07:01:09.4833548Z * [new tag] trunk/924fc52e1842de756a7632e7b2777aeed77d60e5 -> trunk/924fc52e1842de756a7632e7b2777aeed77d60e5 2025-07-17T07:01:09.4834508Z * [new tag] trunk/925fbfca27580f2ec8d5f9bfd549b1fe2e665617 -> trunk/925fbfca27580f2ec8d5f9bfd549b1fe2e665617 2025-07-17T07:01:09.4835379Z * [new tag] trunk/92b7ed6d07fcd6af31cddc7b4276e626b023bd0b -> trunk/92b7ed6d07fcd6af31cddc7b4276e626b023bd0b 2025-07-17T07:01:09.4836558Z * [new tag] trunk/92c79f36dbbdb01e0aab6efb8f52df828e1046d5 -> trunk/92c79f36dbbdb01e0aab6efb8f52df828e1046d5 2025-07-17T07:01:09.4837318Z * [new tag] trunk/92ee5bd9f6bef38b3e3e81a37f4d5374395aeb40 -> trunk/92ee5bd9f6bef38b3e3e81a37f4d5374395aeb40 2025-07-17T07:01:09.4838315Z * [new tag] trunk/92f41ccc2651ab284118ec7087977ab455027eb0 -> trunk/92f41ccc2651ab284118ec7087977ab455027eb0 2025-07-17T07:01:09.4839221Z * [new tag] trunk/930b575389f9233efddf70ea7b7804ed06af80d5 -> trunk/930b575389f9233efddf70ea7b7804ed06af80d5 2025-07-17T07:01:09.4840217Z * [new tag] trunk/9328a7fb589f6372ea478e47cdae8d124030f383 -> trunk/9328a7fb589f6372ea478e47cdae8d124030f383 2025-07-17T07:01:09.4841149Z * [new tag] trunk/9338d85d4594f981c198bcbb7edfccf6b92643be -> trunk/9338d85d4594f981c198bcbb7edfccf6b92643be 2025-07-17T07:01:09.4841922Z * [new tag] trunk/9345279c6ebdbad95b7b53bc2cb6f63a4e57b2cc -> trunk/9345279c6ebdbad95b7b53bc2cb6f63a4e57b2cc 2025-07-17T07:01:09.4842692Z * [new tag] trunk/937529f0b31788726e53890f5601886c64dc9eec -> trunk/937529f0b31788726e53890f5601886c64dc9eec 2025-07-17T07:01:09.4843657Z * [new tag] trunk/938515fa75f4e9d28c62a2aaa3e0e5428c867c36 -> trunk/938515fa75f4e9d28c62a2aaa3e0e5428c867c36 2025-07-17T07:01:09.4844580Z * [new tag] trunk/93854e83b7bfde94090662e9b372d8bf44ccf5d4 -> trunk/93854e83b7bfde94090662e9b372d8bf44ccf5d4 2025-07-17T07:01:09.4845513Z * [new tag] trunk/944a140e90389eced1ec38e14cb4345811ed0b1a -> trunk/944a140e90389eced1ec38e14cb4345811ed0b1a 2025-07-17T07:01:09.4846458Z * [new tag] trunk/9462106b7e41d9a24308255e15613b464ab086ce -> trunk/9462106b7e41d9a24308255e15613b464ab086ce 2025-07-17T07:01:09.4847358Z * [new tag] trunk/94716db22214912896cf680dc3eb88574f611a42 -> trunk/94716db22214912896cf680dc3eb88574f611a42 2025-07-17T07:01:09.4848263Z * [new tag] trunk/94763f5ca75330206777f3c1b36ff124706bd9d9 -> trunk/94763f5ca75330206777f3c1b36ff124706bd9d9 2025-07-17T07:01:09.4849265Z * [new tag] trunk/94995eba07763890b86465d53c4647c089f48d0a -> trunk/94995eba07763890b86465d53c4647c089f48d0a 2025-07-17T07:01:09.4850171Z * [new tag] trunk/94ae61533719defecb08d11f63c5d9fe9a826c00 -> trunk/94ae61533719defecb08d11f63c5d9fe9a826c00 2025-07-17T07:01:09.4851503Z * [new tag] trunk/94c746bb43484787a3f5bbdc2f72bd4fb02f2964 -> trunk/94c746bb43484787a3f5bbdc2f72bd4fb02f2964 2025-07-17T07:01:09.4852394Z * [new tag] trunk/94da4523ec4362dabbf9f08f9f2efce79ab70b73 -> trunk/94da4523ec4362dabbf9f08f9f2efce79ab70b73 2025-07-17T07:01:09.4853673Z * [new tag] trunk/94f8679019ea4b1272f1ad58ad7cad87147cf5a7 -> trunk/94f8679019ea4b1272f1ad58ad7cad87147cf5a7 2025-07-17T07:01:09.4854415Z * [new tag] trunk/9508d73307b4bc1fe453677526a096e5e10a7575 -> trunk/9508d73307b4bc1fe453677526a096e5e10a7575 2025-07-17T07:01:09.4855180Z * [new tag] trunk/9513b9d03fa8950ba5d2b59cc0b1a1aab3a41c06 -> trunk/9513b9d03fa8950ba5d2b59cc0b1a1aab3a41c06 2025-07-17T07:01:09.4856150Z * [new tag] trunk/95448b2ce61c3995ecdae0bfec655a5ef81a117d -> trunk/95448b2ce61c3995ecdae0bfec655a5ef81a117d 2025-07-17T07:01:09.4857108Z * [new tag] trunk/954ce949500746763a487a8ed9800035e7cd87d4 -> trunk/954ce949500746763a487a8ed9800035e7cd87d4 2025-07-17T07:01:09.4858124Z * [new tag] trunk/95a7d1912a86d857a9f4adb55b73b57518ce1e7b -> trunk/95a7d1912a86d857a9f4adb55b73b57518ce1e7b 2025-07-17T07:01:09.4859032Z * [new tag] trunk/95bc3da9f8555897d5d2b90f75385e3b2ff7bc43 -> trunk/95bc3da9f8555897d5d2b90f75385e3b2ff7bc43 2025-07-17T07:01:09.4859910Z * [new tag] trunk/95cb42c45d17f532222611e8028c9307622cc3c9 -> trunk/95cb42c45d17f532222611e8028c9307622cc3c9 2025-07-17T07:01:09.4860702Z * [new tag] trunk/9620994067b18e846a097d1e99af85ec2426ef0a -> trunk/9620994067b18e846a097d1e99af85ec2426ef0a 2025-07-17T07:01:09.4861652Z * [new tag] trunk/9636e2cfd3e995ef977f670ad47e8e895296d992 -> trunk/9636e2cfd3e995ef977f670ad47e8e895296d992 2025-07-17T07:01:09.4862518Z * [new tag] trunk/9642c7568967ab424c5d0e04ef2cd1e82a54b5f8 -> trunk/9642c7568967ab424c5d0e04ef2cd1e82a54b5f8 2025-07-17T07:01:09.4863448Z * [new tag] trunk/9656251bb1bee12c0e2f21828dc14a4c3c06afdd -> trunk/9656251bb1bee12c0e2f21828dc14a4c3c06afdd 2025-07-17T07:01:09.4864407Z * [new tag] trunk/9665702c64af633ab23499228d552a49660a9fa2 -> trunk/9665702c64af633ab23499228d552a49660a9fa2 2025-07-17T07:01:09.4865322Z * [new tag] trunk/96897e721b76f3b72aa406696165711d74f8d260 -> trunk/96897e721b76f3b72aa406696165711d74f8d260 2025-07-17T07:01:09.4866354Z * [new tag] trunk/968f90ce7344223c788eeba59200cc22b9f94dcd -> trunk/968f90ce7344223c788eeba59200cc22b9f94dcd 2025-07-17T07:01:09.4867251Z * [new tag] trunk/96d082d06bda98addd4ad7903d315477404dc272 -> trunk/96d082d06bda98addd4ad7903d315477404dc272 2025-07-17T07:01:09.4868091Z * [new tag] trunk/96df86641048a282a4622ac93d19e4c7b6c38b8e -> trunk/96df86641048a282a4622ac93d19e4c7b6c38b8e 2025-07-17T07:01:09.4869062Z * [new tag] trunk/96e4c95cd8d03037765ffd4b8fcdaa06c4b2c51c -> trunk/96e4c95cd8d03037765ffd4b8fcdaa06c4b2c51c 2025-07-17T07:01:09.4869928Z * [new tag] trunk/9768d393fa62df8a508136f5b6634bf955d8365d -> trunk/9768d393fa62df8a508136f5b6634bf955d8365d 2025-07-17T07:01:09.4871088Z * [new tag] trunk/977abe786d907c1ff76528a550e3d53c9f3b1044 -> trunk/977abe786d907c1ff76528a550e3d53c9f3b1044 2025-07-17T07:01:09.4872019Z * [new tag] trunk/981c99fdffd9a4f510e4b89245d16aa427ee0978 -> trunk/981c99fdffd9a4f510e4b89245d16aa427ee0978 2025-07-17T07:01:09.4872914Z * [new tag] trunk/987314aa96fdf8aa051e3643b26f4209b7fe166d -> trunk/987314aa96fdf8aa051e3643b26f4209b7fe166d 2025-07-17T07:01:09.4873829Z * [new tag] trunk/98a34e8d4b4d73504afbf49f70284221e6303314 -> trunk/98a34e8d4b4d73504afbf49f70284221e6303314 2025-07-17T07:01:09.4874692Z * [new tag] trunk/98bb0c0e7888a84de1d22c4952de69a5d5b1a0b3 -> trunk/98bb0c0e7888a84de1d22c4952de69a5d5b1a0b3 2025-07-17T07:01:09.4875670Z * [new tag] trunk/9944cd0949e96d656746de6df0cb3a5a954597e4 -> trunk/9944cd0949e96d656746de6df0cb3a5a954597e4 2025-07-17T07:01:09.4876595Z * [new tag] trunk/996206e66fcafff25d0af5177497e8f792000869 -> trunk/996206e66fcafff25d0af5177497e8f792000869 2025-07-17T07:01:09.4877595Z * [new tag] trunk/9963845a4e55a3e8d35ea49deb8f8c1f6c53cb74 -> trunk/9963845a4e55a3e8d35ea49deb8f8c1f6c53cb74 2025-07-17T07:01:09.4878467Z * [new tag] trunk/9968c854b6a38857d05fb1da7bea797fbf23c880 -> trunk/9968c854b6a38857d05fb1da7bea797fbf23c880 2025-07-17T07:01:09.4879245Z * [new tag] trunk/9968edd00256fdb47e2e0129df918c5b23c06419 -> trunk/9968edd00256fdb47e2e0129df918c5b23c06419 2025-07-17T07:01:09.4880199Z * [new tag] trunk/99c1a6bdd98ecb1f9b2fb8310bcd891c8c6adf57 -> trunk/99c1a6bdd98ecb1f9b2fb8310bcd891c8c6adf57 2025-07-17T07:01:09.4881174Z * [new tag] trunk/99e99d5bfe57eddfce23f7dc9ede016cb1393c52 -> trunk/99e99d5bfe57eddfce23f7dc9ede016cb1393c52 2025-07-17T07:01:09.4882232Z * [new tag] trunk/9a2c669425379eb264f896390b8fcd8d3f2ce959 -> trunk/9a2c669425379eb264f896390b8fcd8d3f2ce959 2025-07-17T07:01:09.4883149Z * [new tag] trunk/9a42f01586267b52fe303c0c1b7a71d50cc4178e -> trunk/9a42f01586267b52fe303c0c1b7a71d50cc4178e 2025-07-17T07:01:09.4884182Z * [new tag] trunk/9a4c08ddfc9b43c07cd16355277d359dfcef50d6 -> trunk/9a4c08ddfc9b43c07cd16355277d359dfcef50d6 2025-07-17T07:01:09.4885101Z * [new tag] trunk/9a5278225fc5e7b46d54a65ae1a3f049ee49824f -> trunk/9a5278225fc5e7b46d54a65ae1a3f049ee49824f 2025-07-17T07:01:09.4885976Z * [new tag] trunk/9a5c59368d46d3793e09b72a2782ef4d12e74392 -> trunk/9a5c59368d46d3793e09b72a2782ef4d12e74392 2025-07-17T07:01:09.4886905Z * [new tag] trunk/9aaa184105b2f436b5834187c4c004c02e438491 -> trunk/9aaa184105b2f436b5834187c4c004c02e438491 2025-07-17T07:01:09.4887844Z * [new tag] trunk/9afee0fa969fd4ebab86a2cbad3217c8bade156e -> trunk/9afee0fa969fd4ebab86a2cbad3217c8bade156e 2025-07-17T07:01:09.4888725Z * [new tag] trunk/9b0013c6bb98d7161e921d03be76c81bbc0eebef -> trunk/9b0013c6bb98d7161e921d03be76c81bbc0eebef 2025-07-17T07:01:09.4889791Z * [new tag] trunk/9b122aab5dcd419b96d4a1137c45e99bde94f14e -> trunk/9b122aab5dcd419b96d4a1137c45e99bde94f14e 2025-07-17T07:01:09.4890707Z * [new tag] trunk/9b498d3bb28b8e3411ce464dd2755c5b96d92c8f -> trunk/9b498d3bb28b8e3411ce464dd2755c5b96d92c8f 2025-07-17T07:01:09.4891596Z * [new tag] trunk/9b4a748e29a720d0fade7e1298a68cc36cfd5f5e -> trunk/9b4a748e29a720d0fade7e1298a68cc36cfd5f5e 2025-07-17T07:01:09.4892496Z * [new tag] trunk/9b4db093cb63555654c868ba9e3ab68ef4c722e5 -> trunk/9b4db093cb63555654c868ba9e3ab68ef4c722e5 2025-07-17T07:01:09.4893496Z * [new tag] trunk/9bae2fcf990cd51891218895ac1b3cfe70ffc2c3 -> trunk/9bae2fcf990cd51891218895ac1b3cfe70ffc2c3 2025-07-17T07:01:09.4894287Z * [new tag] trunk/9bd0830ed8d3e753afc3e9fff2553f4c5871f6f9 -> trunk/9bd0830ed8d3e753afc3e9fff2553f4c5871f6f9 2025-07-17T07:01:09.4895190Z * [new tag] trunk/9bd42c15707a4b410ee005d5916e882a7db432bb -> trunk/9bd42c15707a4b410ee005d5916e882a7db432bb 2025-07-17T07:01:09.4896446Z * [new tag] trunk/9bdf87e8918b9a3f78d7bcb8a770c19f7c82ac15 -> trunk/9bdf87e8918b9a3f78d7bcb8a770c19f7c82ac15 2025-07-17T07:01:09.4897357Z * [new tag] trunk/9be5860bc34b643abd02ac5b5a89d820efcdfbc9 -> trunk/9be5860bc34b643abd02ac5b5a89d820efcdfbc9 2025-07-17T07:01:09.4898723Z * [new tag] trunk/9bf41633d76f7816fdcc0b7ae22a42dc91821004 -> trunk/9bf41633d76f7816fdcc0b7ae22a42dc91821004 2025-07-17T07:01:09.4899635Z * [new tag] trunk/9bf6593e96b711641606e6008a4936173fd3b458 -> trunk/9bf6593e96b711641606e6008a4936173fd3b458 2025-07-17T07:01:09.4900520Z * [new tag] trunk/9bfefda296d2df31ce9bb90410d91d8f18127545 -> trunk/9bfefda296d2df31ce9bb90410d91d8f18127545 2025-07-17T07:01:09.4901449Z * [new tag] trunk/9c189ed29a2cfa08ff357cb5042ff8c34f07d668 -> trunk/9c189ed29a2cfa08ff357cb5042ff8c34f07d668 2025-07-17T07:01:09.4902318Z * [new tag] trunk/9c39bc24807a5843f8affdf56bd71836760dc554 -> trunk/9c39bc24807a5843f8affdf56bd71836760dc554 2025-07-17T07:01:09.4903402Z * [new tag] trunk/9ca080db87f66becb2bb2c61598c0beabae73d5f -> trunk/9ca080db87f66becb2bb2c61598c0beabae73d5f 2025-07-17T07:01:09.4904251Z * [new tag] trunk/9cced33c7c9cdfc68e9ed85c4b45bdfd05dac92d -> trunk/9cced33c7c9cdfc68e9ed85c4b45bdfd05dac92d 2025-07-17T07:01:09.4905134Z * [new tag] trunk/9cd521de4dad5fc6bca94e253a9334b9a521acb0 -> trunk/9cd521de4dad5fc6bca94e253a9334b9a521acb0 2025-07-17T07:01:09.4906006Z * [new tag] trunk/9d175bc7e615b062d8ea57df6ca17edb8a6b951f -> trunk/9d175bc7e615b062d8ea57df6ca17edb8a6b951f 2025-07-17T07:01:09.4906972Z * [new tag] trunk/9d184bda2f190a3ba72a4a0d95e1fde26d6bfc08 -> trunk/9d184bda2f190a3ba72a4a0d95e1fde26d6bfc08 2025-07-17T07:01:09.4907911Z * [new tag] trunk/9d2d2270037c5a014767cdfa531863da8062bf9d -> trunk/9d2d2270037c5a014767cdfa531863da8062bf9d 2025-07-17T07:01:09.4908980Z * [new tag] trunk/9d59b516e9b3026948918e3ff8c2ef55a33d13ad -> trunk/9d59b516e9b3026948918e3ff8c2ef55a33d13ad 2025-07-17T07:01:09.4909859Z * [new tag] trunk/9d677389cb5eb75d423860c55519b522961a9195 -> trunk/9d677389cb5eb75d423860c55519b522961a9195 2025-07-17T07:01:09.4910833Z * [new tag] trunk/9de23d0c29dfac8dc0f6f234bdbcd85a6375fa81 -> trunk/9de23d0c29dfac8dc0f6f234bdbcd85a6375fa81 2025-07-17T07:01:09.4912083Z * [new tag] trunk/9df0176408518b30ac172837bd697c9d19b19a98 -> trunk/9df0176408518b30ac172837bd697c9d19b19a98 2025-07-17T07:01:09.4913062Z * [new tag] trunk/9df2e8020f190bdad02258aff2b2f88f7db3dcab -> trunk/9df2e8020f190bdad02258aff2b2f88f7db3dcab 2025-07-17T07:01:09.4914002Z * [new tag] trunk/9e132b770e06c2399f827d3d1963fe036e9744e6 -> trunk/9e132b770e06c2399f827d3d1963fe036e9744e6 2025-07-17T07:01:09.4914780Z * [new tag] trunk/9e5f4a844c0aebf964a435094005c92713fbe99a -> trunk/9e5f4a844c0aebf964a435094005c92713fbe99a 2025-07-17T07:01:09.4915681Z * [new tag] trunk/9e88d6c857fd2b276427f4527130e2ecb7ed731e -> trunk/9e88d6c857fd2b276427f4527130e2ecb7ed731e 2025-07-17T07:01:09.4916783Z * [new tag] trunk/9e9484d022f8d65e2066b5683b75c84ba0f36332 -> trunk/9e9484d022f8d65e2066b5683b75c84ba0f36332 2025-07-17T07:01:09.4917808Z * [new tag] trunk/9ed0060225a7b78c60c42f29be94444b537edd4a -> trunk/9ed0060225a7b78c60c42f29be94444b537edd4a 2025-07-17T07:01:09.4918819Z * [new tag] trunk/9f18482d41227df3cf2248dfa54bd6601e61e1ca -> trunk/9f18482d41227df3cf2248dfa54bd6601e61e1ca 2025-07-17T07:01:09.4919712Z * [new tag] trunk/9f37cce69334bccebf4b21503f0047d0c0bb320c -> trunk/9f37cce69334bccebf4b21503f0047d0c0bb320c 2025-07-17T07:01:09.4920674Z * [new tag] trunk/9f5153b1a495b3b2b7ad9f22a064fe4074d742aa -> trunk/9f5153b1a495b3b2b7ad9f22a064fe4074d742aa 2025-07-17T07:01:09.4921590Z * [new tag] trunk/9f5276dc07c788533af8945b1605df47a33313e7 -> trunk/9f5276dc07c788533af8945b1605df47a33313e7 2025-07-17T07:01:09.4922514Z * [new tag] trunk/9fe2d156a9f81d67e248c0edaf7feee1a8d6c4d5 -> trunk/9fe2d156a9f81d67e248c0edaf7feee1a8d6c4d5 2025-07-17T07:01:09.4923388Z * [new tag] trunk/9fed2addedb42da86b657165fe14eadc911232cf -> trunk/9fed2addedb42da86b657165fe14eadc911232cf 2025-07-17T07:01:09.4924203Z * [new tag] trunk/a00a697c1748937b0c6d13508ff76b8af4957d8a -> trunk/a00a697c1748937b0c6d13508ff76b8af4957d8a 2025-07-17T07:01:09.4925116Z * [new tag] trunk/a0308edb6cdfd8983e80a499890d9f320556e844 -> trunk/a0308edb6cdfd8983e80a499890d9f320556e844 2025-07-17T07:01:09.4926098Z * [new tag] trunk/a04a13c44908fe0ace4f76a228d045dbf5c015bc -> trunk/a04a13c44908fe0ace4f76a228d045dbf5c015bc 2025-07-17T07:01:09.4927231Z * [new tag] trunk/a0e0abd0379ed403adc926d3cc5459fa35aff0a0 -> trunk/a0e0abd0379ed403adc926d3cc5459fa35aff0a0 2025-07-17T07:01:09.4928269Z * [new tag] trunk/a10024d7dea47c52469059a47efe376eb20adca0 -> trunk/a10024d7dea47c52469059a47efe376eb20adca0 2025-07-17T07:01:09.4929167Z * [new tag] trunk/a1057cda31fe890d237fe9a2e6b3314cd4be3439 -> trunk/a1057cda31fe890d237fe9a2e6b3314cd4be3439 2025-07-17T07:01:09.4930084Z * [new tag] trunk/a1257446f8eaf81eb758e89b4e784bed47b9c733 -> trunk/a1257446f8eaf81eb758e89b4e784bed47b9c733 2025-07-17T07:01:09.4931095Z * [new tag] trunk/a1282b18239204b0344884ebd232b33b2d8b748f -> trunk/a1282b18239204b0344884ebd232b33b2d8b748f 2025-07-17T07:01:09.4932037Z * [new tag] trunk/a14f427db68e54500ef4cd9ed34cb9537263bb74 -> trunk/a14f427db68e54500ef4cd9ed34cb9537263bb74 2025-07-17T07:01:09.4932900Z * [new tag] trunk/a1dad2f2d2c082e2a3784c3d585ef0204b7ccf75 -> trunk/a1dad2f2d2c082e2a3784c3d585ef0204b7ccf75 2025-07-17T07:01:09.4933791Z * [new tag] trunk/a1e4f1f98a0b9596fe52aaf2f85b0778498d5f49 -> trunk/a1e4f1f98a0b9596fe52aaf2f85b0778498d5f49 2025-07-17T07:01:09.4934741Z * [new tag] trunk/a205e8fd7357cf5c2b95eb4bec7c8ff7b5c41651 -> trunk/a205e8fd7357cf5c2b95eb4bec7c8ff7b5c41651 2025-07-17T07:01:09.4935675Z * [new tag] trunk/a21806f0386c2671fc11ae37fe2fe96c4aeb37d9 -> trunk/a21806f0386c2671fc11ae37fe2fe96c4aeb37d9 2025-07-17T07:01:09.4936579Z * [new tag] trunk/a23f4471b952d8cd630b860639e0aaa9be957d60 -> trunk/a23f4471b952d8cd630b860639e0aaa9be957d60 2025-07-17T07:01:09.4937421Z * [new tag] trunk/a24afbff3f44399ac9513addce6bd50cacab22d2 -> trunk/a24afbff3f44399ac9513addce6bd50cacab22d2 2025-07-17T07:01:09.4938244Z * [new tag] trunk/a24ce67deedab025531660ddb44c148bb066edf8 -> trunk/a24ce67deedab025531660ddb44c148bb066edf8 2025-07-17T07:01:09.4939013Z * [new tag] trunk/a25d1443fae79a9984eaa44e973b2f5645c85da8 -> trunk/a25d1443fae79a9984eaa44e973b2f5645c85da8 2025-07-17T07:01:09.4940000Z * [new tag] trunk/a26bf3892778ca7cc457c772a1f5194c11b6f33c -> trunk/a26bf3892778ca7cc457c772a1f5194c11b6f33c 2025-07-17T07:01:09.4940930Z * [new tag] trunk/a28e6ae38f1e1de33ecf48b679ff1eda71fc2efc -> trunk/a28e6ae38f1e1de33ecf48b679ff1eda71fc2efc 2025-07-17T07:01:09.4941824Z * [new tag] trunk/a2a75be0f8d680cf1dc36c50f34f225b0c7c4d6a -> trunk/a2a75be0f8d680cf1dc36c50f34f225b0c7c4d6a 2025-07-17T07:01:09.4942700Z * [new tag] trunk/a2ad16be72bf989c01b96c4c56b1c108a71c087f -> trunk/a2ad16be72bf989c01b96c4c56b1c108a71c087f 2025-07-17T07:01:09.4943738Z * [new tag] trunk/a2b0b2698d5b953861b2e4f3cdee11136f07bd3b -> trunk/a2b0b2698d5b953861b2e4f3cdee11136f07bd3b 2025-07-17T07:01:09.4944696Z * [new tag] trunk/a3098a74d494020dbb906c05ef047013e1921662 -> trunk/a3098a74d494020dbb906c05ef047013e1921662 2025-07-17T07:01:09.4945592Z * [new tag] trunk/a317c63d1b70a7989a4cab09394691fb7a3d8323 -> trunk/a317c63d1b70a7989a4cab09394691fb7a3d8323 2025-07-17T07:01:09.4946428Z * [new tag] trunk/a355158fcba807fda1e47e5ee42babdbcf447947 -> trunk/a355158fcba807fda1e47e5ee42babdbcf447947 2025-07-17T07:01:09.4947306Z * [new tag] trunk/a35b3a9b95bbe0703de33802162a83cb7970ddc0 -> trunk/a35b3a9b95bbe0703de33802162a83cb7970ddc0 2025-07-17T07:01:09.4948217Z * [new tag] trunk/a369350065493109d1abfbb994695777ab11bcf4 -> trunk/a369350065493109d1abfbb994695777ab11bcf4 2025-07-17T07:01:09.4949328Z * [new tag] trunk/a38f433be2e94a64b095a44ba39879d02d0c2316 -> trunk/a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:01:09.4950259Z * [new tag] trunk/a3ec6d64b24fdbd61164240f3bcd8530434812b5 -> trunk/a3ec6d64b24fdbd61164240f3bcd8530434812b5 2025-07-17T07:01:09.4951181Z * [new tag] trunk/a46ea8a364e528828c4369d58d53802291f0b49b -> trunk/a46ea8a364e528828c4369d58d53802291f0b49b 2025-07-17T07:01:09.4952176Z * [new tag] trunk/a47ca4fc746a663c0e97d55a87815d0965d0a7e9 -> trunk/a47ca4fc746a663c0e97d55a87815d0965d0a7e9 2025-07-17T07:01:09.4953075Z * [new tag] trunk/a4b59498c5222a02a706fa1e1308a6035d65feab -> trunk/a4b59498c5222a02a706fa1e1308a6035d65feab 2025-07-17T07:01:09.4954091Z * [new tag] trunk/a4c7e7f98373ad8f309e419c6f98b0134933dcda -> trunk/a4c7e7f98373ad8f309e419c6f98b0134933dcda 2025-07-17T07:01:09.4955034Z * [new tag] trunk/a4d753295ee5662056bdfd1b00fa242071ac7125 -> trunk/a4d753295ee5662056bdfd1b00fa242071ac7125 2025-07-17T07:01:09.4956021Z * [new tag] trunk/a4ea242edc8626250e54a62aa073cba0e5322af2 -> trunk/a4ea242edc8626250e54a62aa073cba0e5322af2 2025-07-17T07:01:09.4957084Z * [new tag] trunk/a529a5daf5d348f4f8dac4fcd85521153b6a3d4d -> trunk/a529a5daf5d348f4f8dac4fcd85521153b6a3d4d 2025-07-17T07:01:09.4957991Z * [new tag] trunk/a5938ff431202864c92fec7d9042574348b1c15b -> trunk/a5938ff431202864c92fec7d9042574348b1c15b 2025-07-17T07:01:09.4958989Z * [new tag] trunk/a5b4463d60e5beaec546843b24876ce573890784 -> trunk/a5b4463d60e5beaec546843b24876ce573890784 2025-07-17T07:01:09.4959799Z * [new tag] trunk/a5c61eb78dda6b7b4c4beb8bc616f9545ea4807b -> trunk/a5c61eb78dda6b7b4c4beb8bc616f9545ea4807b 2025-07-17T07:01:09.4960752Z * [new tag] trunk/a5cbb2bcb3c005909a3c10042605e861e6390927 -> trunk/a5cbb2bcb3c005909a3c10042605e861e6390927 2025-07-17T07:01:09.4961698Z * [new tag] trunk/a5df6ffbc2cf8d61fc98bca1c10f22ff64b2318e -> trunk/a5df6ffbc2cf8d61fc98bca1c10f22ff64b2318e 2025-07-17T07:01:09.4962656Z * [new tag] trunk/a5e68814d556cf67c6511876410970dd08c3dd6d -> trunk/a5e68814d556cf67c6511876410970dd08c3dd6d 2025-07-17T07:01:09.4963664Z * [new tag] trunk/a5f59cc2eab3a5201712c52fe48c268357ba4f3c -> trunk/a5f59cc2eab3a5201712c52fe48c268357ba4f3c 2025-07-17T07:01:09.4964654Z * [new tag] trunk/a6084b71edb8d2856356724b5e71c4e2a861867f -> trunk/a6084b71edb8d2856356724b5e71c4e2a861867f 2025-07-17T07:01:09.4965644Z * [new tag] trunk/a6210fd07b8fe1924f24229bb30562608af4f41a -> trunk/a6210fd07b8fe1924f24229bb30562608af4f41a 2025-07-17T07:01:09.4966564Z * [new tag] trunk/a666cf3b38f5e7739f94b175f152b127a6d51344 -> trunk/a666cf3b38f5e7739f94b175f152b127a6d51344 2025-07-17T07:01:09.4967494Z * [new tag] trunk/a67eb1a0d627d59d95a99722d37cab3bf054261f -> trunk/a67eb1a0d627d59d95a99722d37cab3bf054261f 2025-07-17T07:01:09.4968492Z * [new tag] trunk/a69e27ca5ad4287add73972ef1b34b469e3c7d23 -> trunk/a69e27ca5ad4287add73972ef1b34b469e3c7d23 2025-07-17T07:01:09.4969441Z * [new tag] trunk/a6a3a441442a96f38d0771c985f753223cea2ba0 -> trunk/a6a3a441442a96f38d0771c985f753223cea2ba0 2025-07-17T07:01:09.4970750Z * [new tag] trunk/a6a8641c8aee5797324c3d41749bcae62b4e5de8 -> trunk/a6a8641c8aee5797324c3d41749bcae62b4e5de8 2025-07-17T07:01:09.4971670Z * [new tag] trunk/a6fab82b16011213cb010c8c50461b9a680748a2 -> trunk/a6fab82b16011213cb010c8c50461b9a680748a2 2025-07-17T07:01:09.4973191Z * [new tag] trunk/a73d9e0aec9319e56ba0c9b0ccc25db69c739faf -> trunk/a73d9e0aec9319e56ba0c9b0ccc25db69c739faf 2025-07-17T07:01:09.4973975Z * [new tag] trunk/a767e50adca9e08dd638be60c9e5604de15b9f15 -> trunk/a767e50adca9e08dd638be60c9e5604de15b9f15 2025-07-17T07:01:09.4974779Z * [new tag] trunk/a7b29c88b1f55bac02f38bf1faba68b6c4be4c9c -> trunk/a7b29c88b1f55bac02f38bf1faba68b6c4be4c9c 2025-07-17T07:01:09.4975698Z * [new tag] trunk/a7eb153bba0534daaa1b652d44bb9fb5bd1ac7c7 -> trunk/a7eb153bba0534daaa1b652d44bb9fb5bd1ac7c7 2025-07-17T07:01:09.4976629Z * [new tag] trunk/a82c171bb26949dda5f5932051a905a9bab38761 -> trunk/a82c171bb26949dda5f5932051a905a9bab38761 2025-07-17T07:01:09.4977545Z * [new tag] trunk/a85ad5552532926b78d489d1b60671f74bf6dc8e -> trunk/a85ad5552532926b78d489d1b60671f74bf6dc8e 2025-07-17T07:01:09.4978611Z * [new tag] trunk/a87dfc7480bc98d33dab274d7e95723aa9cf7840 -> trunk/a87dfc7480bc98d33dab274d7e95723aa9cf7840 2025-07-17T07:01:09.4979479Z * [new tag] trunk/a8b973673798ca79dfe616c9080415d09f9e990d -> trunk/a8b973673798ca79dfe616c9080415d09f9e990d 2025-07-17T07:01:09.4980385Z * [new tag] trunk/a8ec7babcf27584cf068c3a5a04bb3ea0102ab99 -> trunk/a8ec7babcf27584cf068c3a5a04bb3ea0102ab99 2025-07-17T07:01:09.4981396Z * [new tag] trunk/a8fe982993221048ee1665ce28add1b02888784d -> trunk/a8fe982993221048ee1665ce28add1b02888784d 2025-07-17T07:01:09.4982318Z * [new tag] trunk/a92b24cd839aa6807f3c9ea8b8787da99c4490c0 -> trunk/a92b24cd839aa6807f3c9ea8b8787da99c4490c0 2025-07-17T07:01:09.4983315Z * [new tag] trunk/a9352bd25e9f070e8f846b8fdbcd7c90ad5c66b3 -> trunk/a9352bd25e9f070e8f846b8fdbcd7c90ad5c66b3 2025-07-17T07:01:09.4984401Z * [new tag] trunk/a952956d05dd617355007ae31d8e936474a35f14 -> trunk/a952956d05dd617355007ae31d8e936474a35f14 2025-07-17T07:01:09.4985375Z * [new tag] trunk/a9537b626c91ce617139ade60b9107a2805a4248 -> trunk/a9537b626c91ce617139ade60b9107a2805a4248 2025-07-17T07:01:09.4986430Z * [new tag] trunk/a95504b10fff38b5308660e0b535961beed6c9f1 -> trunk/a95504b10fff38b5308660e0b535961beed6c9f1 2025-07-17T07:01:09.4987571Z * [new tag] trunk/a9a0501ec40d8fab07b0f8d2fcbf8eb7147c1ae8 -> trunk/a9a0501ec40d8fab07b0f8d2fcbf8eb7147c1ae8 2025-07-17T07:01:09.4988621Z * [new tag] trunk/a9ac9f2635a9be28eaf267ed41070081a4ce05d8 -> trunk/a9ac9f2635a9be28eaf267ed41070081a4ce05d8 2025-07-17T07:01:09.4989395Z * [new tag] trunk/a9d5157e2596e1d830158e83fab618aab1d4ee39 -> trunk/a9d5157e2596e1d830158e83fab618aab1d4ee39 2025-07-17T07:01:09.4990189Z * [new tag] trunk/a9ee4250d55c6342b80e2d57a8ad9a1992ddcdce -> trunk/a9ee4250d55c6342b80e2d57a8ad9a1992ddcdce 2025-07-17T07:01:09.4991133Z * [new tag] trunk/a9ef7c4d044d386993a6e82b5ad37b7db759b502 -> trunk/a9ef7c4d044d386993a6e82b5ad37b7db759b502 2025-07-17T07:01:09.4992066Z * [new tag] trunk/a9f902add02383ca1b0386eb865767641975fede -> trunk/a9f902add02383ca1b0386eb865767641975fede 2025-07-17T07:01:09.4993003Z * [new tag] trunk/aa116285768ba6a8cd34bf8d245e38d04c88810a -> trunk/aa116285768ba6a8cd34bf8d245e38d04c88810a 2025-07-17T07:01:09.4993953Z * [new tag] trunk/aa280ea19fb20923d048909fa98af092e18ca2fb -> trunk/aa280ea19fb20923d048909fa98af092e18ca2fb 2025-07-17T07:01:09.4994916Z * [new tag] trunk/aa2d54148d476383986855af3fe53862da861dda -> trunk/aa2d54148d476383986855af3fe53862da861dda 2025-07-17T07:01:09.4995841Z * [new tag] trunk/aab949aa96a6b197b75ffa25608fa84049ff68ad -> trunk/aab949aa96a6b197b75ffa25608fa84049ff68ad 2025-07-17T07:01:09.4996753Z * [new tag] trunk/aac0e8f0e998a9381f0eb5dd303a853515109eb0 -> trunk/aac0e8f0e998a9381f0eb5dd303a853515109eb0 2025-07-17T07:01:09.4997681Z * [new tag] trunk/aacb9440791f4e9567e2123f19bb062e75c2d242 -> trunk/aacb9440791f4e9567e2123f19bb062e75c2d242 2025-07-17T07:01:09.4998721Z * [new tag] trunk/ab2294d8289a7757a2fc321cdefac88e2b378edf -> trunk/ab2294d8289a7757a2fc321cdefac88e2b378edf 2025-07-17T07:01:09.4999620Z * [new tag] trunk/ab3393e923514438c9bdfc1afcd0b2aac8be8de9 -> trunk/ab3393e923514438c9bdfc1afcd0b2aac8be8de9 2025-07-17T07:01:09.5000707Z * [new tag] trunk/ab51a937371e61f91cacae7d9fb4b1fe61f24f03 -> trunk/ab51a937371e61f91cacae7d9fb4b1fe61f24f03 2025-07-17T07:01:09.5001670Z * [new tag] trunk/ab56e5add9c36f611a4d9af2f43213926b65d7b4 -> trunk/ab56e5add9c36f611a4d9af2f43213926b65d7b4 2025-07-17T07:01:09.5002587Z * [new tag] trunk/ab655816b8f76f511fb2262d45276d8d1b13d59c -> trunk/ab655816b8f76f511fb2262d45276d8d1b13d59c 2025-07-17T07:01:09.5003606Z * [new tag] trunk/ab6cb34480a14f3cf2446519189ee5f0c5e7278d -> trunk/ab6cb34480a14f3cf2446519189ee5f0c5e7278d 2025-07-17T07:01:09.5004478Z * [new tag] trunk/ab81fb846cd0e52bbc6a2eb366706350639e209f -> trunk/ab81fb846cd0e52bbc6a2eb366706350639e209f 2025-07-17T07:01:09.5005536Z * [new tag] trunk/ab8874bd26894a8ab956408ceee2e89c9ad7f450 -> trunk/ab8874bd26894a8ab956408ceee2e89c9ad7f450 2025-07-17T07:01:09.5006475Z * [new tag] trunk/abbdf9f3632af505b3265b4258a6c185b257edde -> trunk/abbdf9f3632af505b3265b4258a6c185b257edde 2025-07-17T07:01:09.5007584Z * [new tag] trunk/abeae997a35b1920a45be9c26eff7474f2c6c5dd -> trunk/abeae997a35b1920a45be9c26eff7474f2c6c5dd 2025-07-17T07:01:09.5008777Z * [new tag] trunk/abf4da0d242274ba7ab4c0859d105cae74a2dbc5 -> trunk/abf4da0d242274ba7ab4c0859d105cae74a2dbc5 2025-07-17T07:01:09.5009728Z * [new tag] trunk/ac706bfc7f942b8a97401486a840dd8f6452f5cb -> trunk/ac706bfc7f942b8a97401486a840dd8f6452f5cb 2025-07-17T07:01:09.5010620Z * [new tag] trunk/ac86ec0e60370c037e018137f2048cafd47c5c28 -> trunk/ac86ec0e60370c037e018137f2048cafd47c5c28 2025-07-17T07:01:09.5011551Z * [new tag] trunk/acaf6ba3c6d0bdec88ab3f6c2ef82650050558d2 -> trunk/acaf6ba3c6d0bdec88ab3f6c2ef82650050558d2 2025-07-17T07:01:09.5012482Z * [new tag] trunk/ad86c05b78d343f3346d07a07e17639e421d2cf4 -> trunk/ad86c05b78d343f3346d07a07e17639e421d2cf4 2025-07-17T07:01:09.5013477Z * [new tag] trunk/ada44e5ba78be9377814678d1986556af2d6e570 -> trunk/ada44e5ba78be9377814678d1986556af2d6e570 2025-07-17T07:01:09.5014446Z * [new tag] trunk/add0b450bd9907ba9d089c79ca4af96c0590d8ff -> trunk/add0b450bd9907ba9d089c79ca4af96c0590d8ff 2025-07-17T07:01:09.5015469Z * [new tag] trunk/adf6dd1e44c1b006ea6078576b64d5616cecfa5a -> trunk/adf6dd1e44c1b006ea6078576b64d5616cecfa5a 2025-07-17T07:01:09.5016461Z * [new tag] trunk/adf9644440e0d007853e7fdfd67b6a59248f4fbb -> trunk/adf9644440e0d007853e7fdfd67b6a59248f4fbb 2025-07-17T07:01:09.5017399Z * [new tag] trunk/ae0f1f89847564b04bdc43395e664e48f08aaca2 -> trunk/ae0f1f89847564b04bdc43395e664e48f08aaca2 2025-07-17T07:01:09.5018475Z * [new tag] trunk/ae1094b72b7db368f292ed6033de5b495dcdc878 -> trunk/ae1094b72b7db368f292ed6033de5b495dcdc878 2025-07-17T07:01:09.5019538Z * [new tag] trunk/ae86e8f6c829a3cfa9204949156fce2d048c919b -> trunk/ae86e8f6c829a3cfa9204949156fce2d048c919b 2025-07-17T07:01:09.5020509Z * [new tag] trunk/aec569da2325c09487ab659a0f28c3b51e60d779 -> trunk/aec569da2325c09487ab659a0f28c3b51e60d779 2025-07-17T07:01:09.5021415Z * [new tag] trunk/aee2bfc5bae2974f5a3023d51dfa8e3e641144cc -> trunk/aee2bfc5bae2974f5a3023d51dfa8e3e641144cc 2025-07-17T07:01:09.5022299Z * [new tag] trunk/aeffb68d3466635e4e95c50bffd7dfebaba94da2 -> trunk/aeffb68d3466635e4e95c50bffd7dfebaba94da2 2025-07-17T07:01:09.5023218Z * [new tag] trunk/af284b45d5cbfd19d168bf1d118b3a40cd8b3a92 -> trunk/af284b45d5cbfd19d168bf1d118b3a40cd8b3a92 2025-07-17T07:01:09.5024105Z * [new tag] trunk/af3d06909400413801b726a96f3ff52b5ee9ebb5 -> trunk/af3d06909400413801b726a96f3ff52b5ee9ebb5 2025-07-17T07:01:09.5024990Z * [new tag] trunk/af9c92b4cb9f406129dfd8c64c082c0aaf7c723f -> trunk/af9c92b4cb9f406129dfd8c64c082c0aaf7c723f 2025-07-17T07:01:09.5025896Z * [new tag] trunk/aff9c1eec599b8fa97240d192534b0f650c16b1b -> trunk/aff9c1eec599b8fa97240d192534b0f650c16b1b 2025-07-17T07:01:09.5026882Z * [new tag] trunk/b00b641ff1fbfa8f4f6152ffc631e0d24145a7a8 -> trunk/b00b641ff1fbfa8f4f6152ffc631e0d24145a7a8 2025-07-17T07:01:09.5027702Z * [new tag] trunk/b020971e7806bba39aecf636e59e743911831ad8 -> trunk/b020971e7806bba39aecf636e59e743911831ad8 2025-07-17T07:01:09.5028561Z * [new tag] trunk/b0556110e58e3bcf2c872b933e4fd4a0d34398ad -> trunk/b0556110e58e3bcf2c872b933e4fd4a0d34398ad 2025-07-17T07:01:09.5029549Z * [new tag] trunk/b07725a9516028a485153c4b5356b3e33b990f81 -> trunk/b07725a9516028a485153c4b5356b3e33b990f81 2025-07-17T07:01:09.5030358Z * [new tag] trunk/b096341963c4af3b2b0d7f598eba1cdc1c74fb6e -> trunk/b096341963c4af3b2b0d7f598eba1cdc1c74fb6e 2025-07-17T07:01:09.5031231Z * [new tag] trunk/b09bd414a6ccba158c09f586a278051588d90936 -> trunk/b09bd414a6ccba158c09f586a278051588d90936 2025-07-17T07:01:09.5032226Z * [new tag] trunk/b0fbbef1361ccaab8a5aec8e7cd62150e7b361de -> trunk/b0fbbef1361ccaab8a5aec8e7cd62150e7b361de 2025-07-17T07:01:09.5033109Z * [new tag] trunk/b146ca74f01df3cf711fd0f855e05805e490156c -> trunk/b146ca74f01df3cf711fd0f855e05805e490156c 2025-07-17T07:01:09.5034416Z * [new tag] trunk/b146e1a264960e5fb79cf4621ebe4b1345db3e64 -> trunk/b146e1a264960e5fb79cf4621ebe4b1345db3e64 2025-07-17T07:01:09.5035284Z * [new tag] trunk/b147b6c0e31d43a405416743fde1b0b606aa3839 -> trunk/b147b6c0e31d43a405416743fde1b0b606aa3839 2025-07-17T07:01:09.5036197Z * [new tag] trunk/b1713c665516d8355f5491d10b31f98c74ce27f1 -> trunk/b1713c665516d8355f5491d10b31f98c74ce27f1 2025-07-17T07:01:09.5037071Z * [new tag] trunk/b1a54fab9bcb0cc167773f9a885d4170447e1c68 -> trunk/b1a54fab9bcb0cc167773f9a885d4170447e1c68 2025-07-17T07:01:09.5037944Z * [new tag] trunk/b1b8e57cda03bd016594a4fc4944fa5e7f9dd961 -> trunk/b1b8e57cda03bd016594a4fc4944fa5e7f9dd961 2025-07-17T07:01:09.5038936Z * [new tag] trunk/b1d62febd03ac421197d5516596f98d3c46e9b44 -> trunk/b1d62febd03ac421197d5516596f98d3c46e9b44 2025-07-17T07:01:09.5039880Z * [new tag] trunk/b221be9140689d180ec339db05c5e235a95949d3 -> trunk/b221be9140689d180ec339db05c5e235a95949d3 2025-07-17T07:01:09.5040926Z * [new tag] trunk/b22b93a6babf86e823e979528bc0aab88fb7a012 -> trunk/b22b93a6babf86e823e979528bc0aab88fb7a012 2025-07-17T07:01:09.5041853Z * [new tag] trunk/b26da7741be37693ab1cd21115f3fca15b1cdb6b -> trunk/b26da7741be37693ab1cd21115f3fca15b1cdb6b 2025-07-17T07:01:09.5042820Z * [new tag] trunk/b2d473c8f8a6d0677940c174b38511f5ab3c3b65 -> trunk/b2d473c8f8a6d0677940c174b38511f5ab3c3b65 2025-07-17T07:01:09.5043798Z * [new tag] trunk/b2fc9cfea16c8eb52c1ce79b2032793dd1a545fb -> trunk/b2fc9cfea16c8eb52c1ce79b2032793dd1a545fb 2025-07-17T07:01:09.5044660Z * [new tag] trunk/b30e04b3c8a83e19dc9123f2f0229d80e208fb50 -> trunk/b30e04b3c8a83e19dc9123f2f0229d80e208fb50 2025-07-17T07:01:09.5045765Z * [new tag] trunk/b354328ecd6a313eab905ab6f74aed5ea2d3a2ce -> trunk/b354328ecd6a313eab905ab6f74aed5ea2d3a2ce 2025-07-17T07:01:09.5046696Z * [new tag] trunk/b359571c6043b40c4ae4fbb07135fd0f04902e21 -> trunk/b359571c6043b40c4ae4fbb07135fd0f04902e21 2025-07-17T07:01:09.5047660Z * [new tag] trunk/b3b4d28f4cf149cb7448c556d359ca852d815ab1 -> trunk/b3b4d28f4cf149cb7448c556d359ca852d815ab1 2025-07-17T07:01:09.5048651Z * [new tag] trunk/b40981c63078d99bb07afbdcfec1ce8f7519f26b -> trunk/b40981c63078d99bb07afbdcfec1ce8f7519f26b 2025-07-17T07:01:09.5049603Z * [new tag] trunk/b40c0b61eb5f5b6104cb732e709819e84518faa7 -> trunk/b40c0b61eb5f5b6104cb732e709819e84518faa7 2025-07-17T07:01:09.5050476Z * [new tag] trunk/b4228a94d11b1ba6599f443267824d2d918644f2 -> trunk/b4228a94d11b1ba6599f443267824d2d918644f2 2025-07-17T07:01:09.5051614Z * [new tag] trunk/b44306d3681d5b248e6b439d293ea0d5a8903a61 -> trunk/b44306d3681d5b248e6b439d293ea0d5a8903a61 2025-07-17T07:01:09.5052492Z * [new tag] trunk/b4442f42a93390760bb923cbe13b80993f5e8e78 -> trunk/b4442f42a93390760bb923cbe13b80993f5e8e78 2025-07-17T07:01:09.5053320Z * [new tag] trunk/b4476ca378be50034bd5cdc1eaa95104337c998a -> trunk/b4476ca378be50034bd5cdc1eaa95104337c998a 2025-07-17T07:01:09.5054329Z * [new tag] trunk/b487003182b7f2d6697064f184515369bf6c8cce -> trunk/b487003182b7f2d6697064f184515369bf6c8cce 2025-07-17T07:01:09.5055118Z * [new tag] trunk/b49edc0d6c72f744d744a026b0ce0d689e34b83b -> trunk/b49edc0d6c72f744d744a026b0ce0d689e34b83b 2025-07-17T07:01:09.5056166Z * [new tag] trunk/b4e3c9ea34cb607324639cd0bb0129740c300721 -> trunk/b4e3c9ea34cb607324639cd0bb0129740c300721 2025-07-17T07:01:09.5057053Z * [new tag] trunk/b4fc42ca807efc1a1b78f52d5481711a4e8bbea3 -> trunk/b4fc42ca807efc1a1b78f52d5481711a4e8bbea3 2025-07-17T07:01:09.5057981Z * [new tag] trunk/b50075343aeb519d135e00c44ff3577eaa25c61b -> trunk/b50075343aeb519d135e00c44ff3577eaa25c61b 2025-07-17T07:01:09.5059044Z * [new tag] trunk/b54eac2a5ed31106393bbc338de8637817809a1f -> trunk/b54eac2a5ed31106393bbc338de8637817809a1f 2025-07-17T07:01:09.5059983Z * [new tag] trunk/b5bfbba1841da810305262c7f47ee2dae54f335e -> trunk/b5bfbba1841da810305262c7f47ee2dae54f335e 2025-07-17T07:01:09.5060915Z * [new tag] trunk/b5c8b8d09f006b1b2911858882a56dfe6e325f36 -> trunk/b5c8b8d09f006b1b2911858882a56dfe6e325f36 2025-07-17T07:01:09.5061788Z * [new tag] trunk/b5ce77c1f5964293299eb1366f341872a4e47fa6 -> trunk/b5ce77c1f5964293299eb1366f341872a4e47fa6 2025-07-17T07:01:09.5062721Z * [new tag] trunk/b60569ed946ddcc267150a675916d68d7cac9085 -> trunk/b60569ed946ddcc267150a675916d68d7cac9085 2025-07-17T07:01:09.5063640Z * [new tag] trunk/b6188174795956f959feae0cbc33cbdb7901c4b6 -> trunk/b6188174795956f959feae0cbc33cbdb7901c4b6 2025-07-17T07:01:09.5064583Z * [new tag] trunk/b642a5c118baf4cd47dd7fe0190b83e04cee960f -> trunk/b642a5c118baf4cd47dd7fe0190b83e04cee960f 2025-07-17T07:01:09.5065464Z * [new tag] trunk/b6454a9058f2e50be9a3c26c128fec843b09c154 -> trunk/b6454a9058f2e50be9a3c26c128fec843b09c154 2025-07-17T07:01:09.5066564Z * [new tag] trunk/b6add8c8ba927a9f1687134ec2734b02a6ccb3c0 -> trunk/b6add8c8ba927a9f1687134ec2734b02a6ccb3c0 2025-07-17T07:01:09.5067633Z * [new tag] trunk/b6c00dfe249a7bfc1d61a322d5bc30f164353abf -> trunk/b6c00dfe249a7bfc1d61a322d5bc30f164353abf 2025-07-17T07:01:09.5068692Z * [new tag] trunk/b6e625e34f358c71b62409f96dc1e22e4791beef -> trunk/b6e625e34f358c71b62409f96dc1e22e4791beef 2025-07-17T07:01:09.5069651Z * [new tag] trunk/b6f84b3b0fef781653911420253dcff6767197dc -> trunk/b6f84b3b0fef781653911420253dcff6767197dc 2025-07-17T07:01:09.5070693Z * [new tag] trunk/b754b1fa43d20f5b31e17c396487ab56991912da -> trunk/b754b1fa43d20f5b31e17c396487ab56991912da 2025-07-17T07:01:09.5071859Z * [new tag] trunk/b7860c7863df9139bceabf5b0c186e6e4287aa4c -> trunk/b7860c7863df9139bceabf5b0c186e6e4287aa4c 2025-07-17T07:01:09.5072774Z * [new tag] trunk/b7a73a2cdbbe46e04aa145fb8c1615e608dcbde9 -> trunk/b7a73a2cdbbe46e04aa145fb8c1615e608dcbde9 2025-07-17T07:01:09.5073694Z * [new tag] trunk/b7b1109f49f5d0bd6145ae47c5c7d7d18c5659b0 -> trunk/b7b1109f49f5d0bd6145ae47c5c7d7d18c5659b0 2025-07-17T07:01:09.5074766Z * [new tag] trunk/b7def5ff1ca72fbb06350ffc75117efc68e149fb -> trunk/b7def5ff1ca72fbb06350ffc75117efc68e149fb 2025-07-17T07:01:09.5075643Z * [new tag] trunk/b83d8827bcd63501d7298267d94d103bf591c6c2 -> trunk/b83d8827bcd63501d7298267d94d103bf591c6c2 2025-07-17T07:01:09.5076610Z * [new tag] trunk/b85f10ea5006e8ae8fc769f48659ab7ad5eafb69 -> trunk/b85f10ea5006e8ae8fc769f48659ab7ad5eafb69 2025-07-17T07:01:09.5077487Z * [new tag] trunk/b86d5cef68d56f3924dc199424e65904a32d0743 -> trunk/b86d5cef68d56f3924dc199424e65904a32d0743 2025-07-17T07:01:09.5078532Z * [new tag] trunk/b878ca0c91bdccbdd907c15a01e5dcf249f0783c -> trunk/b878ca0c91bdccbdd907c15a01e5dcf249f0783c 2025-07-17T07:01:09.5079448Z * [new tag] trunk/b8ace6f95105751d0535cb0ce0d2c8f656c8b96c -> trunk/b8ace6f95105751d0535cb0ce0d2c8f656c8b96c 2025-07-17T07:01:09.5080629Z * [new tag] trunk/b8aee84fb9692f1a46c8c2a0ae6685df440f6e8f -> trunk/b8aee84fb9692f1a46c8c2a0ae6685df440f6e8f 2025-07-17T07:01:09.5081462Z * [new tag] trunk/b8bc2c2660e84034ff15232e2161e3ef9a6656d0 -> trunk/b8bc2c2660e84034ff15232e2161e3ef9a6656d0 2025-07-17T07:01:09.5082393Z * [new tag] trunk/b8c2d4c259b16f3dc044d049d964c44907ccecb6 -> trunk/b8c2d4c259b16f3dc044d049d964c44907ccecb6 2025-07-17T07:01:09.5083298Z * [new tag] trunk/b8d96c3f78a27e193f4fa9580f8d28298c8180e3 -> trunk/b8d96c3f78a27e193f4fa9580f8d28298c8180e3 2025-07-17T07:01:09.5084191Z * [new tag] trunk/b8fc5e0c0dda5da8315f9bc108a83a0f92252513 -> trunk/b8fc5e0c0dda5da8315f9bc108a83a0f92252513 2025-07-17T07:01:09.5085098Z * [new tag] trunk/b916d8a583cf4fb018c44eaf5efefa9ca76da366 -> trunk/b916d8a583cf4fb018c44eaf5efefa9ca76da366 2025-07-17T07:01:09.5086088Z * [new tag] trunk/b95dadd7170626273bb03b1264f04f3f051908da -> trunk/b95dadd7170626273bb03b1264f04f3f051908da 2025-07-17T07:01:09.5087072Z * [new tag] trunk/b981fb6744d034a0b2a0baf7e138cfb8dc83ca96 -> trunk/b981fb6744d034a0b2a0baf7e138cfb8dc83ca96 2025-07-17T07:01:09.5087935Z * [new tag] trunk/b9afdd9bcc738697c6eefc90899508ab783bf6ab -> trunk/b9afdd9bcc738697c6eefc90899508ab783bf6ab 2025-07-17T07:01:09.5088924Z * [new tag] trunk/b9b84d8011b08ac62cabf9100043c65863372fea -> trunk/b9b84d8011b08ac62cabf9100043c65863372fea 2025-07-17T07:01:09.5089901Z * [new tag] trunk/b9dc2fa4f7aa237a19248705abf82f5eae662182 -> trunk/b9dc2fa4f7aa237a19248705abf82f5eae662182 2025-07-17T07:01:09.5090932Z * [new tag] trunk/ba0d0de5e652650f8a59c85fc25a90f4ed9e2dc1 -> trunk/ba0d0de5e652650f8a59c85fc25a90f4ed9e2dc1 2025-07-17T07:01:09.5091858Z * [new tag] trunk/bb1f3d1a55e3f8eafb279995824c1ef87f24b341 -> trunk/bb1f3d1a55e3f8eafb279995824c1ef87f24b341 2025-07-17T07:01:09.5092820Z * [new tag] trunk/bb3c911c2d64ccad03349e50a0a220a2889ae85c -> trunk/bb3c911c2d64ccad03349e50a0a220a2889ae85c 2025-07-17T07:01:09.5093889Z * [new tag] trunk/bb462a6237c163774c99e01462703ebce55f4589 -> trunk/bb462a6237c163774c99e01462703ebce55f4589 2025-07-17T07:01:09.5094712Z * [new tag] trunk/bb476310a456b1fd418c79573ed34ad68b4871d4 -> trunk/bb476310a456b1fd418c79573ed34ad68b4871d4 2025-07-17T07:01:09.5096089Z * [new tag] trunk/bbb930aba2e769e3ed981f2a035133891de36dae -> trunk/bbb930aba2e769e3ed981f2a035133891de36dae 2025-07-17T07:01:09.5097022Z * [new tag] trunk/bbbced94a43cf764ddfe719e7d4c161a3992830c -> trunk/bbbced94a43cf764ddfe719e7d4c161a3992830c 2025-07-17T07:01:09.5097990Z * [new tag] trunk/bbe681ed510227ce05f99db2a36c1af5c2cc302b -> trunk/bbe681ed510227ce05f99db2a36c1af5c2cc302b 2025-07-17T07:01:09.5098907Z * [new tag] trunk/bbf1a6feac0e88772be103a1b159b871b5c00b4a -> trunk/bbf1a6feac0e88772be103a1b159b871b5c00b4a 2025-07-17T07:01:09.5099960Z * [new tag] trunk/bc3972b80a7abe85036f48b610532fce39ea5097 -> trunk/bc3972b80a7abe85036f48b610532fce39ea5097 2025-07-17T07:01:09.5100831Z * [new tag] trunk/bc5a11b58180d40157175f45c69d60a9b9961315 -> trunk/bc5a11b58180d40157175f45c69d60a9b9961315 2025-07-17T07:01:09.5101792Z * [new tag] trunk/bc65253369933160a2da3fc786d027a572faf6b7 -> trunk/bc65253369933160a2da3fc786d027a572faf6b7 2025-07-17T07:01:09.5102738Z * [new tag] trunk/bc6e0661a6ec7e536bee60b9c929f71643bb6c89 -> trunk/bc6e0661a6ec7e536bee60b9c929f71643bb6c89 2025-07-17T07:01:09.5103716Z * [new tag] trunk/bc9091a524a1ebe4de16af4dd8f442db7d1cb138 -> trunk/bc9091a524a1ebe4de16af4dd8f442db7d1cb138 2025-07-17T07:01:09.5104675Z * [new tag] trunk/bc9bd2a766ae8cf2aba8f3d0153cd8ecd05b4465 -> trunk/bc9bd2a766ae8cf2aba8f3d0153cd8ecd05b4465 2025-07-17T07:01:09.5105630Z * [new tag] trunk/bcad962550f2bfd850684250a3c881c9f38ad601 -> trunk/bcad962550f2bfd850684250a3c881c9f38ad601 2025-07-17T07:01:09.5106545Z * [new tag] trunk/bcc98bb2a4dd11ac696082731f8980b72deb6750 -> trunk/bcc98bb2a4dd11ac696082731f8980b72deb6750 2025-07-17T07:01:09.5107522Z * [new tag] trunk/bccb8473fed94dbc6f1392d0c5b4a51150ee4a9a -> trunk/bccb8473fed94dbc6f1392d0c5b4a51150ee4a9a 2025-07-17T07:01:09.5108435Z * [new tag] trunk/bcf50636ba1b93a833267c645d887888df06e9ea -> trunk/bcf50636ba1b93a833267c645d887888df06e9ea 2025-07-17T07:01:09.5109390Z * [new tag] trunk/bd364c901d5b20500ec5cbe275e93c955809d900 -> trunk/bd364c901d5b20500ec5cbe275e93c955809d900 2025-07-17T07:01:09.5110302Z * [new tag] trunk/bd3c32916cf5f85ddb9dd3c36e7311adfa8808af -> trunk/bd3c32916cf5f85ddb9dd3c36e7311adfa8808af 2025-07-17T07:01:09.5111344Z * [new tag] trunk/bd6b5fddbf5fb0b603ab8a7428079d9a86cf532a -> trunk/bd6b5fddbf5fb0b603ab8a7428079d9a86cf532a 2025-07-17T07:01:09.5112260Z * [new tag] trunk/bdacf08b8682b9fbe3a8656a53b1f8b1cb007fd8 -> trunk/bdacf08b8682b9fbe3a8656a53b1f8b1cb007fd8 2025-07-17T07:01:09.5113336Z * [new tag] trunk/bdb1553b77bb28df580ea41d726417ac91028ec6 -> trunk/bdb1553b77bb28df580ea41d726417ac91028ec6 2025-07-17T07:01:09.5114252Z * [new tag] trunk/bdb78191662c01ab1263108febac29a8560337d0 -> trunk/bdb78191662c01ab1263108febac29a8560337d0 2025-07-17T07:01:09.5115206Z * [new tag] trunk/bdbf2792a8f15907f6bbf231f73dab0e8efe1c50 -> trunk/bdbf2792a8f15907f6bbf231f73dab0e8efe1c50 2025-07-17T07:01:09.5116089Z * [new tag] trunk/be124a61a4933603795644d068d2c0e5f444e766 -> trunk/be124a61a4933603795644d068d2c0e5f444e766 2025-07-17T07:01:09.5117064Z * [new tag] trunk/be2ab96347a1e7206a57f69b58263c4455ff8f76 -> trunk/be2ab96347a1e7206a57f69b58263c4455ff8f76 2025-07-17T07:01:09.5118173Z * [new tag] trunk/be2ad70cfa1360da5c23a04ff6ca3480fa02f278 -> trunk/be2ad70cfa1360da5c23a04ff6ca3480fa02f278 2025-07-17T07:01:09.5119082Z * [new tag] trunk/be2e43264d0bce254efabcc60c368d1418bde57f -> trunk/be2e43264d0bce254efabcc60c368d1418bde57f 2025-07-17T07:01:09.5120117Z * [new tag] trunk/be56a8d7ac0dc72f6946354d7ac5be9ece0f1c35 -> trunk/be56a8d7ac0dc72f6946354d7ac5be9ece0f1c35 2025-07-17T07:01:09.5120984Z * [new tag] trunk/beb52f5c0ac8efddeafa862f274bc247db989695 -> trunk/beb52f5c0ac8efddeafa862f274bc247db989695 2025-07-17T07:01:09.5122009Z * [new tag] trunk/bee93f9f0d16f4f563812bb5c16e862de15724c1 -> trunk/bee93f9f0d16f4f563812bb5c16e862de15724c1 2025-07-17T07:01:09.5122841Z * [new tag] trunk/beed033b6e6ac57c0b4a1f47eb436e115a52e41b -> trunk/beed033b6e6ac57c0b4a1f47eb436e115a52e41b 2025-07-17T07:01:09.5123774Z * [new tag] trunk/bf06190e21fdf539c13e1ec01271653d0729733a -> trunk/bf06190e21fdf539c13e1ec01271653d0729733a 2025-07-17T07:01:09.5124717Z * [new tag] trunk/bf1ebe0531e1b0390ea09d66ac78500d3c6d3a15 -> trunk/bf1ebe0531e1b0390ea09d66ac78500d3c6d3a15 2025-07-17T07:01:09.5125695Z * [new tag] trunk/bf50d715539acedcb31a6d8f787149eff6213fdb -> trunk/bf50d715539acedcb31a6d8f787149eff6213fdb 2025-07-17T07:01:09.5126637Z * [new tag] trunk/bf798a2f016ca0001750436150e7a2bdb2676d1a -> trunk/bf798a2f016ca0001750436150e7a2bdb2676d1a 2025-07-17T07:01:09.5127491Z * [new tag] trunk/bf7e290854b7f0ab3fb89251d0100821f1b3a70e -> trunk/bf7e290854b7f0ab3fb89251d0100821f1b3a70e 2025-07-17T07:01:09.5128923Z * [new tag] trunk/bf897b4cea2b7481499a81afa30bfc69a8e685c4 -> trunk/bf897b4cea2b7481499a81afa30bfc69a8e685c4 2025-07-17T07:01:09.5129875Z * [new tag] trunk/bfcababbcb95ec42046737dbcf61f8e258075ace -> trunk/bfcababbcb95ec42046737dbcf61f8e258075ace 2025-07-17T07:01:09.5130873Z * [new tag] trunk/bfccfa0b31221d5df0b263de5a41fb9f7c84b97d -> trunk/bfccfa0b31221d5df0b263de5a41fb9f7c84b97d 2025-07-17T07:01:09.5131594Z * [new tag] trunk/c038719731abdcd415a5e82c5f3826f2358229fc -> trunk/c038719731abdcd415a5e82c5f3826f2358229fc 2025-07-17T07:01:09.5132451Z * [new tag] trunk/c04a4e709410936c12cdc9db5aaf47164f74a367 -> trunk/c04a4e709410936c12cdc9db5aaf47164f74a367 2025-07-17T07:01:09.5133531Z * [new tag] trunk/c062550a3598d27c2d6572db7c0f4ff90a84cc84 -> trunk/c062550a3598d27c2d6572db7c0f4ff90a84cc84 2025-07-17T07:01:09.5134543Z * [new tag] trunk/c06c2569ee53c169c96f42b45bdb64f390d2f23b -> trunk/c06c2569ee53c169c96f42b45bdb64f390d2f23b 2025-07-17T07:01:09.5135404Z * [new tag] trunk/c09b05487877a3f8b239523b3806f5dd9fc82051 -> trunk/c09b05487877a3f8b239523b3806f5dd9fc82051 2025-07-17T07:01:09.5136442Z * [new tag] trunk/c09cf29d7d010c0547f2f6771921a0ee2ec4904b -> trunk/c09cf29d7d010c0547f2f6771921a0ee2ec4904b 2025-07-17T07:01:09.5137349Z * [new tag] trunk/c09eba877f9c16908b3a925ef694604c1c761b85 -> trunk/c09eba877f9c16908b3a925ef694604c1c761b85 2025-07-17T07:01:09.5138320Z * [new tag] trunk/c0e155a8d230b04f186d1b7540b01213be2b9fc6 -> trunk/c0e155a8d230b04f186d1b7540b01213be2b9fc6 2025-07-17T07:01:09.5140174Z * [new tag] trunk/c0ee01c2fb54e2ae924270f7fd53069915a61a50 -> trunk/c0ee01c2fb54e2ae924270f7fd53069915a61a50 2025-07-17T07:01:09.5141021Z * [new tag] trunk/c10339559de1464c2c5aeb16649c382eefcfb572 -> trunk/c10339559de1464c2c5aeb16649c382eefcfb572 2025-07-17T07:01:09.5141742Z * [new tag] trunk/c11888e7a6557ff64e24ca06e22946c116a7c1e4 -> trunk/c11888e7a6557ff64e24ca06e22946c116a7c1e4 2025-07-17T07:01:09.5143028Z * [new tag] trunk/c13e725edd8dd21406c629bf625f2d6c59ceedd1 -> trunk/c13e725edd8dd21406c629bf625f2d6c59ceedd1 2025-07-17T07:01:09.5144650Z * [new tag] trunk/c14110056f1b6e989850f20ae56d47fbc775e890 -> trunk/c14110056f1b6e989850f20ae56d47fbc775e890 2025-07-17T07:01:09.5145071Z * [new tag] trunk/c1446e1e9d2f5a1bae5fb3d58e58f16c15bb15c3 -> trunk/c1446e1e9d2f5a1bae5fb3d58e58f16c15bb15c3 2025-07-17T07:01:09.5145930Z * [new tag] trunk/c165b36a31585d4e061a84e1977428afd931b82d -> trunk/c165b36a31585d4e061a84e1977428afd931b82d 2025-07-17T07:01:09.5146698Z * [new tag] trunk/c174f3a6a55864cedb8f6d9014e9b8cadf91186b -> trunk/c174f3a6a55864cedb8f6d9014e9b8cadf91186b 2025-07-17T07:01:09.5147655Z * [new tag] trunk/c177abd217ecef5cc096d50adbf5990525714dd3 -> trunk/c177abd217ecef5cc096d50adbf5990525714dd3 2025-07-17T07:01:09.5148507Z * [new tag] trunk/c199a4d0fd03ab3f7e36c6133839cfaf34ba59da -> trunk/c199a4d0fd03ab3f7e36c6133839cfaf34ba59da 2025-07-17T07:01:09.5149434Z * [new tag] trunk/c1a629f76d0afc2ddb4a5c7c1925caa1d12b5a5e -> trunk/c1a629f76d0afc2ddb4a5c7c1925caa1d12b5a5e 2025-07-17T07:01:09.5150400Z * [new tag] trunk/c1ad4b8e7a16f54c35a3908b56ed7d9f95eef586 -> trunk/c1ad4b8e7a16f54c35a3908b56ed7d9f95eef586 2025-07-17T07:01:09.5151324Z * [new tag] trunk/c1ae768baa9598ea97f301999a227b34a2efdecf -> trunk/c1ae768baa9598ea97f301999a227b34a2efdecf 2025-07-17T07:01:09.5152236Z * [new tag] trunk/c1cbaca7fd9937c0a089d98aa69066daf35c898f -> trunk/c1cbaca7fd9937c0a089d98aa69066daf35c898f 2025-07-17T07:01:09.5153236Z * [new tag] trunk/c1f531f0b0e6faf443d90f8de2936e866c8c27c2 -> trunk/c1f531f0b0e6faf443d90f8de2936e866c8c27c2 2025-07-17T07:01:09.5154128Z * [new tag] trunk/c202a7329ad798da676762a8af2aa588f882d288 -> trunk/c202a7329ad798da676762a8af2aa588f882d288 2025-07-17T07:01:09.5155133Z * [new tag] trunk/c2185dc4a5626848df37cad214b73d5ae7dd4f17 -> trunk/c2185dc4a5626848df37cad214b73d5ae7dd4f17 2025-07-17T07:01:09.5156030Z * [new tag] trunk/c219dbd2fc70227ba543c98e9740a84723ba36da -> trunk/c219dbd2fc70227ba543c98e9740a84723ba36da 2025-07-17T07:01:09.5157015Z * [new tag] trunk/c2510fcd86152028c3e6cf483740b177a10ac9b9 -> trunk/c2510fcd86152028c3e6cf483740b177a10ac9b9 2025-07-17T07:01:09.5158367Z * [new tag] trunk/c26ce593d8737cab4b55483b62956a6fea9e4375 -> trunk/c26ce593d8737cab4b55483b62956a6fea9e4375 2025-07-17T07:01:09.5159283Z * [new tag] trunk/c27f83dd91ff3599b5157866e6be014c20b967a0 -> trunk/c27f83dd91ff3599b5157866e6be014c20b967a0 2025-07-17T07:01:09.5160160Z * [new tag] trunk/c28e74e45743feac10559c30dbf71cc35bc12ccb -> trunk/c28e74e45743feac10559c30dbf71cc35bc12ccb 2025-07-17T07:01:09.5161125Z * [new tag] trunk/c2beeadeb40e927c51bc5bcd409b3f28374a5190 -> trunk/c2beeadeb40e927c51bc5bcd409b3f28374a5190 2025-07-17T07:01:09.5162197Z * [new tag] trunk/c2d1b225e62bdf3adbba91891f53bc60315adaac -> trunk/c2d1b225e62bdf3adbba91891f53bc60315adaac 2025-07-17T07:01:09.5163114Z * [new tag] trunk/c2f4cc59a70bfd7d7e46e9b5596bae8e4ae2cf9c -> trunk/c2f4cc59a70bfd7d7e46e9b5596bae8e4ae2cf9c 2025-07-17T07:01:09.5164054Z * [new tag] trunk/c329a8f19cc94cb7f9d3fc814484cded138ee3ca -> trunk/c329a8f19cc94cb7f9d3fc814484cded138ee3ca 2025-07-17T07:01:09.5165068Z * [new tag] trunk/c37ddcaefbe9b877e1816ce97dedb8ad26d09450 -> trunk/c37ddcaefbe9b877e1816ce97dedb8ad26d09450 2025-07-17T07:01:09.5166079Z * [new tag] trunk/c3ecabf0593066750156989fc75acbeeaddf0791 -> trunk/c3ecabf0593066750156989fc75acbeeaddf0791 2025-07-17T07:01:09.5167100Z * [new tag] trunk/c48d0f4643b7a69ebe24069e932ce1465a31cdbe -> trunk/c48d0f4643b7a69ebe24069e932ce1465a31cdbe 2025-07-17T07:01:09.5168048Z * [new tag] trunk/c4b93e6579c8e2f1252067c4923cbb859c476fb4 -> trunk/c4b93e6579c8e2f1252067c4923cbb859c476fb4 2025-07-17T07:01:09.5169051Z * [new tag] trunk/c4cdcda754e2b73b030902dd06fb651c7a026510 -> trunk/c4cdcda754e2b73b030902dd06fb651c7a026510 2025-07-17T07:01:09.5170177Z * [new tag] trunk/c515385b0ac4a94deef652159e71fe0912615d14 -> trunk/c515385b0ac4a94deef652159e71fe0912615d14 2025-07-17T07:01:09.5175118Z * [new tag] trunk/c54778625ec45b94eb97f52da3ad6c2eb3d3c3c9 -> trunk/c54778625ec45b94eb97f52da3ad6c2eb3d3c3c9 2025-07-17T07:01:09.5176097Z * [new tag] trunk/c553c55be76daaf70d977a4ac7664b46cbcfa7c4 -> trunk/c553c55be76daaf70d977a4ac7664b46cbcfa7c4 2025-07-17T07:01:09.5177025Z * [new tag] trunk/c5589074e64b28afd737174ae1e9c2ba0b925e56 -> trunk/c5589074e64b28afd737174ae1e9c2ba0b925e56 2025-07-17T07:01:09.5178306Z * [new tag] trunk/c55eef79f8880e4b610a0ca6f6131e690dc948dd -> trunk/c55eef79f8880e4b610a0ca6f6131e690dc948dd 2025-07-17T07:01:09.5179068Z * [new tag] trunk/c5a4fe9c17bc20eb46b15fda554d17030bb6a5b9 -> trunk/c5a4fe9c17bc20eb46b15fda554d17030bb6a5b9 2025-07-17T07:01:09.5179961Z * [new tag] trunk/c5b46b5408e136a5a3060b11a96afa51bd009fd5 -> trunk/c5b46b5408e136a5a3060b11a96afa51bd009fd5 2025-07-17T07:01:09.5180899Z * [new tag] trunk/c5d00e150ad503510bf28adf09f69201aeb94f5c -> trunk/c5d00e150ad503510bf28adf09f69201aeb94f5c 2025-07-17T07:01:09.5181806Z * [new tag] trunk/c5d3e7a4ff460eed70b8443485a7e3568e87aee9 -> trunk/c5d3e7a4ff460eed70b8443485a7e3568e87aee9 2025-07-17T07:01:09.5182691Z * [new tag] trunk/c60327ba74f4db232a2832f2c7ca4b2db43a3132 -> trunk/c60327ba74f4db232a2832f2c7ca4b2db43a3132 2025-07-17T07:01:09.5183615Z * [new tag] trunk/c60d8188d23801d44343c96746ec2e7d2971c5d7 -> trunk/c60d8188d23801d44343c96746ec2e7d2971c5d7 2025-07-17T07:01:09.5184642Z * [new tag] trunk/c620d0b5c7e8679413d620624725471223ce8359 -> trunk/c620d0b5c7e8679413d620624725471223ce8359 2025-07-17T07:01:09.5185455Z * [new tag] trunk/c68af9af1b3652a8e25bd6d0ff8dae89f206a81a -> trunk/c68af9af1b3652a8e25bd6d0ff8dae89f206a81a 2025-07-17T07:01:09.5186475Z * [new tag] trunk/c6a27bae3656021720074520ac6dad9cebe83ff5 -> trunk/c6a27bae3656021720074520ac6dad9cebe83ff5 2025-07-17T07:01:09.5188583Z * [new tag] trunk/c6b4f98625bb6b22bb9a60112a6d58e684a97e1b -> trunk/c6b4f98625bb6b22bb9a60112a6d58e684a97e1b 2025-07-17T07:01:09.5189677Z * [new tag] trunk/c74fd35050a7241f0c439501ef735aa6cdde751f -> trunk/c74fd35050a7241f0c439501ef735aa6cdde751f 2025-07-17T07:01:09.5190567Z * [new tag] trunk/c75c732481915c25295a0ae6321d39aa314eaa93 -> trunk/c75c732481915c25295a0ae6321d39aa314eaa93 2025-07-17T07:01:09.5191488Z * [new tag] trunk/c78bbdf4102d2c13bf6aa1abe4352aa7bca401ca -> trunk/c78bbdf4102d2c13bf6aa1abe4352aa7bca401ca 2025-07-17T07:01:09.5192451Z * [new tag] trunk/c78fce9e79b79686b87f4007cbaec819bdd0223f -> trunk/c78fce9e79b79686b87f4007cbaec819bdd0223f 2025-07-17T07:01:09.5193345Z * [new tag] trunk/c79c7bbe615265b6b3d7df39d6d5a68afd7d6b2a -> trunk/c79c7bbe615265b6b3d7df39d6d5a68afd7d6b2a 2025-07-17T07:01:09.5194515Z * [new tag] trunk/c7b6c98d1097bec9dc92bde2fe324aa126a5daa2 -> trunk/c7b6c98d1097bec9dc92bde2fe324aa126a5daa2 2025-07-17T07:01:09.5197606Z * [new tag] trunk/c808af514d59e25ea4a880c1e1e07d3232984e5d -> trunk/c808af514d59e25ea4a880c1e1e07d3232984e5d 2025-07-17T07:01:09.5198223Z * [new tag] trunk/c811f41cf58238b49e9c2f0a9fa00dcc471b2e10 -> trunk/c811f41cf58238b49e9c2f0a9fa00dcc471b2e10 2025-07-17T07:01:09.5198746Z * [new tag] trunk/c82a174ceab79f77ba18405dd263eb03692608fd -> trunk/c82a174ceab79f77ba18405dd263eb03692608fd 2025-07-17T07:01:09.5199279Z * [new tag] trunk/c83041cac2e9ca537b210b74876dbcee5e08ae9a -> trunk/c83041cac2e9ca537b210b74876dbcee5e08ae9a 2025-07-17T07:01:09.5199767Z * [new tag] trunk/c843909d9e32f92b2e31cf9b8f066daf311a6f18 -> trunk/c843909d9e32f92b2e31cf9b8f066daf311a6f18 2025-07-17T07:01:09.5200699Z * [new tag] trunk/c88e87f3553b7ef0b743fb030317fabb6fe2dc29 -> trunk/c88e87f3553b7ef0b743fb030317fabb6fe2dc29 2025-07-17T07:01:09.5201620Z * [new tag] trunk/c8c221c0b3abbb8b5e20138080644dd5f5cd0aa1 -> trunk/c8c221c0b3abbb8b5e20138080644dd5f5cd0aa1 2025-07-17T07:01:09.5202539Z * [new tag] trunk/c8c892b4a50fdad624753db5b8d2bbb0fc5bb110 -> trunk/c8c892b4a50fdad624753db5b8d2bbb0fc5bb110 2025-07-17T07:01:09.5203480Z * [new tag] trunk/c8d39a10457ea5d65184c6e8f037f46c5525d869 -> trunk/c8d39a10457ea5d65184c6e8f037f46c5525d869 2025-07-17T07:01:09.5204505Z * [new tag] trunk/c9174a20f75ba007b0f520326ced5c65d8a2b269 -> trunk/c9174a20f75ba007b0f520326ced5c65d8a2b269 2025-07-17T07:01:09.5205330Z * [new tag] trunk/c92f1075aaf3649f6368af2a3df9b5167f941b3f -> trunk/c92f1075aaf3649f6368af2a3df9b5167f941b3f 2025-07-17T07:01:09.5206305Z * [new tag] trunk/c9404faacb7c18af17086be26587b46e141afbcc -> trunk/c9404faacb7c18af17086be26587b46e141afbcc 2025-07-17T07:01:09.5207251Z * [new tag] trunk/c95705dac2da8134c946cdd573944632ef22f230 -> trunk/c95705dac2da8134c946cdd573944632ef22f230 2025-07-17T07:01:09.5208141Z * [new tag] trunk/c95f7fa874a3116f1067f9092456ee7281003614 -> trunk/c95f7fa874a3116f1067f9092456ee7281003614 2025-07-17T07:01:09.5209131Z * [new tag] trunk/c9a5bf09baa1a6776555e901331b1baefe6691bc -> trunk/c9a5bf09baa1a6776555e901331b1baefe6691bc 2025-07-17T07:01:09.5210178Z * [new tag] trunk/c9afcffed0870c211d2e8be422812d6a70aef3e2 -> trunk/c9afcffed0870c211d2e8be422812d6a70aef3e2 2025-07-17T07:01:09.5211140Z * [new tag] trunk/c9e9a0c82316ed59f6ef989a6000f0d5231b9b16 -> trunk/c9e9a0c82316ed59f6ef989a6000f0d5231b9b16 2025-07-17T07:01:09.5212174Z * [new tag] trunk/ca3cabd24ace1899ca4669431f5b0556c5ab9ebf -> trunk/ca3cabd24ace1899ca4669431f5b0556c5ab9ebf 2025-07-17T07:01:09.5213143Z * [new tag] trunk/ca5a40395d8b212dce0a57df01ca056eae55446f -> trunk/ca5a40395d8b212dce0a57df01ca056eae55446f 2025-07-17T07:01:09.5214104Z * [new tag] trunk/cadcb5d36802579441da3dbe3c2eecc74a0eae78 -> trunk/cadcb5d36802579441da3dbe3c2eecc74a0eae78 2025-07-17T07:01:09.5215367Z * [new tag] trunk/cb711c8fa04673d3490306e2b14539ab7dca3c23 -> trunk/cb711c8fa04673d3490306e2b14539ab7dca3c23 2025-07-17T07:01:09.5216273Z * [new tag] trunk/cb853945a77af54d9989ae7ac36d0007c0215b10 -> trunk/cb853945a77af54d9989ae7ac36d0007c0215b10 2025-07-17T07:01:09.5217140Z * [new tag] trunk/cb9b479f4f799eea058de9be3a0e09f977fc82da -> trunk/cb9b479f4f799eea058de9be3a0e09f977fc82da 2025-07-17T07:01:09.5218099Z * [new tag] trunk/cbafba57941c1d5f78640845320ac89157570b44 -> trunk/cbafba57941c1d5f78640845320ac89157570b44 2025-07-17T07:01:09.5218989Z * [new tag] trunk/cbcffce48a3422a5e9a2103888248c82d52d199c -> trunk/cbcffce48a3422a5e9a2103888248c82d52d199c 2025-07-17T07:01:09.5219926Z * [new tag] trunk/cc09d3a5ba2a5ae032078570e6123d523952ed22 -> trunk/cc09d3a5ba2a5ae032078570e6123d523952ed22 2025-07-17T07:01:09.5220904Z * [new tag] trunk/cc0faeb80fff17b3d170aa70041865aafb1790a9 -> trunk/cc0faeb80fff17b3d170aa70041865aafb1790a9 2025-07-17T07:01:09.5221744Z * [new tag] trunk/cc3ea2d84004b6348c77a285ba2639932b87c101 -> trunk/cc3ea2d84004b6348c77a285ba2639932b87c101 2025-07-17T07:01:09.5222646Z * [new tag] trunk/cc410d3761001499611bca6cf835239b86093791 -> trunk/cc410d3761001499611bca6cf835239b86093791 2025-07-17T07:01:09.5223704Z * [new tag] trunk/ccb1f687d63f0215ebcf3c1340c6682edeaccd28 -> trunk/ccb1f687d63f0215ebcf3c1340c6682edeaccd28 2025-07-17T07:01:09.5224477Z * [new tag] trunk/ccb67f39b4d75943cdc531d9032b3ba9235cfd56 -> trunk/ccb67f39b4d75943cdc531d9032b3ba9235cfd56 2025-07-17T07:01:09.5226059Z * [new tag] trunk/ccc6279b4086d55cd1f7e2d699473478610d8a7b -> trunk/ccc6279b4086d55cd1f7e2d699473478610d8a7b 2025-07-17T07:01:09.5226801Z * [new tag] trunk/cce4d213a67b7536dce431fd29c92f9791c9f81d -> trunk/cce4d213a67b7536dce431fd29c92f9791c9f81d 2025-07-17T07:01:09.5227582Z * [new tag] trunk/cd1a924dba145334aacb7c1b7276d6cef7ca41cc -> trunk/cd1a924dba145334aacb7c1b7276d6cef7ca41cc 2025-07-17T07:01:09.5228373Z * [new tag] trunk/cd361fc247a9abdbe9851867e31ac3cefcff299e -> trunk/cd361fc247a9abdbe9851867e31ac3cefcff299e 2025-07-17T07:01:09.5229364Z * [new tag] trunk/cd66ff80307862ef8e75520054ecd19a5eff9f7e -> trunk/cd66ff80307862ef8e75520054ecd19a5eff9f7e 2025-07-17T07:01:09.5230294Z * [new tag] trunk/cd75cf3cabedeac2ae4bbb266c05ca9b64181abe -> trunk/cd75cf3cabedeac2ae4bbb266c05ca9b64181abe 2025-07-17T07:01:09.5231218Z * [new tag] trunk/cd80f9a4c35a63ef415dbf6a361e4520a9cabf7b -> trunk/cd80f9a4c35a63ef415dbf6a361e4520a9cabf7b 2025-07-17T07:01:09.5232149Z * [new tag] trunk/cd82096973985042ed2eaa84e69fbf0f067f9301 -> trunk/cd82096973985042ed2eaa84e69fbf0f067f9301 2025-07-17T07:01:09.5233079Z * [new tag] trunk/cd995bfb2aac8891465809be3ce29543bd524287 -> trunk/cd995bfb2aac8891465809be3ce29543bd524287 2025-07-17T07:01:09.5234178Z * [new tag] trunk/cdb144fcf0aa4300c6de7158cb18ff7503d48492 -> trunk/cdb144fcf0aa4300c6de7158cb18ff7503d48492 2025-07-17T07:01:09.5235078Z * [new tag] trunk/cdfa33a328f2d3fdaeb645fde186194ddc2e66c0 -> trunk/cdfa33a328f2d3fdaeb645fde186194ddc2e66c0 2025-07-17T07:01:09.5235954Z * [new tag] trunk/ce1a07570d95cdd1543b9b2d45b3899c59e6802f -> trunk/ce1a07570d95cdd1543b9b2d45b3899c59e6802f 2025-07-17T07:01:09.5236853Z * [new tag] trunk/ce3406817d50b3357fa644784cc84ff167ce40ce -> trunk/ce3406817d50b3357fa644784cc84ff167ce40ce 2025-07-17T07:01:09.5237829Z * [new tag] trunk/ce44877961af7c8ec618f525853ce7edf3efa4eb -> trunk/ce44877961af7c8ec618f525853ce7edf3efa4eb 2025-07-17T07:01:09.5238837Z * [new tag] trunk/ce6e0523f9911c605860c4f5f278c2dad893dde9 -> trunk/ce6e0523f9911c605860c4f5f278c2dad893dde9 2025-07-17T07:01:09.5239696Z * [new tag] trunk/ce73b0c53f1f215345dcfe3953871a4aaf170a0c -> trunk/ce73b0c53f1f215345dcfe3953871a4aaf170a0c 2025-07-17T07:01:09.5240791Z * [new tag] trunk/ce79056471737557dcc64378985cd2b036e7322c -> trunk/ce79056471737557dcc64378985cd2b036e7322c 2025-07-17T07:01:09.5241685Z * [new tag] trunk/ce8180a61de405c519e00ac48eab8ff765ea71e6 -> trunk/ce8180a61de405c519e00ac48eab8ff765ea71e6 2025-07-17T07:01:09.5242662Z * [new tag] trunk/ce97a5dcfa3cb10c7805ff5cb44abd6a16b4ae8b -> trunk/ce97a5dcfa3cb10c7805ff5cb44abd6a16b4ae8b 2025-07-17T07:01:09.5243641Z * [new tag] trunk/ce9ba071fd29013e72100dd97728d01c860720d9 -> trunk/ce9ba071fd29013e72100dd97728d01c860720d9 2025-07-17T07:01:09.5244636Z * [new tag] trunk/cec264c8c6d74d4fbf5ee31983737b8b5e316dd0 -> trunk/cec264c8c6d74d4fbf5ee31983737b8b5e316dd0 2025-07-17T07:01:09.5245717Z * [new tag] trunk/cec59b76ca606c3e5d34ac0d0f9e0e22b8cfe5bb -> trunk/cec59b76ca606c3e5d34ac0d0f9e0e22b8cfe5bb 2025-07-17T07:01:09.5246683Z * [new tag] trunk/cf0749c92fdfcb8a583ea15f351add88c4d33618 -> trunk/cf0749c92fdfcb8a583ea15f351add88c4d33618 2025-07-17T07:01:09.5248117Z * [new tag] trunk/cf3247b74aaeb956b3c2b31d05e965a0aca5a8b4 -> trunk/cf3247b74aaeb956b3c2b31d05e965a0aca5a8b4 2025-07-17T07:01:09.5248976Z * [new tag] trunk/cf90c9f8d1632777ec5f4b6ccaa14bc5bf259e9c -> trunk/cf90c9f8d1632777ec5f4b6ccaa14bc5bf259e9c 2025-07-17T07:01:09.5249897Z * [new tag] trunk/cf9878d7a20b11d761934ae7732b01644ae137d6 -> trunk/cf9878d7a20b11d761934ae7732b01644ae137d6 2025-07-17T07:01:09.5251027Z * [new tag] trunk/d061a02e6ecf3b62f409578c7d05a564264d1288 -> trunk/d061a02e6ecf3b62f409578c7d05a564264d1288 2025-07-17T07:01:09.5251915Z * [new tag] trunk/d06a406656bf0b4bc9af2d056558dc1630a6e5b9 -> trunk/d06a406656bf0b4bc9af2d056558dc1630a6e5b9 2025-07-17T07:01:09.5252850Z * [new tag] trunk/d083841c0e0d879e460aebb45daac086a240a7dd -> trunk/d083841c0e0d879e460aebb45daac086a240a7dd 2025-07-17T07:01:09.5253807Z * [new tag] trunk/d0a9629435aaceb5acbf31aad70f2109cb8a3ea2 -> trunk/d0a9629435aaceb5acbf31aad70f2109cb8a3ea2 2025-07-17T07:01:09.5254781Z * [new tag] trunk/d0cfa3e5bf662b72068e26e06a1a5c2e640ce8d9 -> trunk/d0cfa3e5bf662b72068e26e06a1a5c2e640ce8d9 2025-07-17T07:01:09.5255696Z * [new tag] trunk/d158e9ea82ce3440e2e9a1bbbecae53a79869404 -> trunk/d158e9ea82ce3440e2e9a1bbbecae53a79869404 2025-07-17T07:01:09.5256638Z * [new tag] trunk/d1947a87074c5db2568038878b1948ea3a33cc23 -> trunk/d1947a87074c5db2568038878b1948ea3a33cc23 2025-07-17T07:01:09.5257559Z * [new tag] trunk/d1b4e0fa9a5feb22fc6de1d36dc4c9dac685caed -> trunk/d1b4e0fa9a5feb22fc6de1d36dc4c9dac685caed 2025-07-17T07:01:09.5258503Z * [new tag] trunk/d1c924c68aaf650439c2193f74cfefc9f16076f1 -> trunk/d1c924c68aaf650439c2193f74cfefc9f16076f1 2025-07-17T07:01:09.5259449Z * [new tag] trunk/d26ca5de058dbcf56ac52bb43e84dd98df2ace97 -> trunk/d26ca5de058dbcf56ac52bb43e84dd98df2ace97 2025-07-17T07:01:09.5260340Z * [new tag] trunk/d27d36136ce35d5d6dc3faa818ba840ba61d4357 -> trunk/d27d36136ce35d5d6dc3faa818ba840ba61d4357 2025-07-17T07:01:09.5261181Z * [new tag] trunk/d283fc79b15844ac470b3429b4dac5661621ae5c -> trunk/d283fc79b15844ac470b3429b4dac5661621ae5c 2025-07-17T07:01:09.5262288Z * [new tag] trunk/d2a2bfcb5867d4920e0a45113861cde6f74857b9 -> trunk/d2a2bfcb5867d4920e0a45113861cde6f74857b9 2025-07-17T07:01:09.5263173Z * [new tag] trunk/d2f06d2b062c9d868a898044bc324547f34c4760 -> trunk/d2f06d2b062c9d868a898044bc324547f34c4760 2025-07-17T07:01:09.5264027Z * [new tag] trunk/d309cd1d502eab8e9cb536876bf5eed88634eb41 -> trunk/d309cd1d502eab8e9cb536876bf5eed88634eb41 2025-07-17T07:01:09.5265023Z * [new tag] trunk/d32deb664a1dfc0e36f0a8d670695046632ebf2a -> trunk/d32deb664a1dfc0e36f0a8d670695046632ebf2a 2025-07-17T07:01:09.5265938Z * [new tag] trunk/d3d64c6db090ee9be051202e6ac6fd4acd5d3e97 -> trunk/d3d64c6db090ee9be051202e6ac6fd4acd5d3e97 2025-07-17T07:01:09.5267061Z * [new tag] trunk/d3d655ad14ee4cd1c135ac57bbf75d5623fc9fa6 -> trunk/d3d655ad14ee4cd1c135ac57bbf75d5623fc9fa6 2025-07-17T07:01:09.5268024Z * [new tag] trunk/d3da03d6fa02aecd01ff41246def793b8fc630bf -> trunk/d3da03d6fa02aecd01ff41246def793b8fc630bf 2025-07-17T07:01:09.5268964Z * [new tag] trunk/d3efd732348f8a455ca23e7fcae043651e41f65e -> trunk/d3efd732348f8a455ca23e7fcae043651e41f65e 2025-07-17T07:01:09.5269887Z * [new tag] trunk/d40aaa42ee8d7283d8de02c68c5625d67acf668a -> trunk/d40aaa42ee8d7283d8de02c68c5625d67acf668a 2025-07-17T07:01:09.5270956Z * [new tag] trunk/d41f62b7a06c51e4a57df4d58e7a2d86d2faa875 -> trunk/d41f62b7a06c51e4a57df4d58e7a2d86d2faa875 2025-07-17T07:01:09.5271896Z * [new tag] trunk/d42c11819f003a848c782d6090f44bbca11c7d60 -> trunk/d42c11819f003a848c782d6090f44bbca11c7d60 2025-07-17T07:01:09.5272798Z * [new tag] trunk/d43c0bdf46d82806cff195a6d2bfa103ab46dc14 -> trunk/d43c0bdf46d82806cff195a6d2bfa103ab46dc14 2025-07-17T07:01:09.5273723Z * [new tag] trunk/d4ad28042993dd09c80775d7fc5756fb4d13fdd4 -> trunk/d4ad28042993dd09c80775d7fc5756fb4d13fdd4 2025-07-17T07:01:09.5274869Z * [new tag] trunk/d4d0ede6bacb4b3b33c0e4aa4cb0e79d34e697ec -> trunk/d4d0ede6bacb4b3b33c0e4aa4cb0e79d34e697ec 2025-07-17T07:01:09.5275710Z * [new tag] trunk/d512584718838876ae14b32bb53cd836a1ceccae -> trunk/d512584718838876ae14b32bb53cd836a1ceccae 2025-07-17T07:01:09.5276483Z * [new tag] trunk/d55dc00f8479699f454e91c779b53e2a16cffc21 -> trunk/d55dc00f8479699f454e91c779b53e2a16cffc21 2025-07-17T07:01:09.5277340Z * [new tag] trunk/d56f11a1f275f2dc037cd5099b70240745990693 -> trunk/d56f11a1f275f2dc037cd5099b70240745990693 2025-07-17T07:01:09.5278239Z * [new tag] trunk/d5781c8d21b3dca35715a093ba52c5698551ad9b -> trunk/d5781c8d21b3dca35715a093ba52c5698551ad9b 2025-07-17T07:01:09.5279135Z * [new tag] trunk/d58ed04d89c34c6930d0f28be351c53db407078f -> trunk/d58ed04d89c34c6930d0f28be351c53db407078f 2025-07-17T07:01:09.5280118Z * [new tag] trunk/d59ed21d0fdcbb34b5c4b121a3b49ae64d8da367 -> trunk/d59ed21d0fdcbb34b5c4b121a3b49ae64d8da367 2025-07-17T07:01:09.5280973Z * [new tag] trunk/d5a89178b05db3124f16c733e9b00f8c5c4ab038 -> trunk/d5a89178b05db3124f16c733e9b00f8c5c4ab038 2025-07-17T07:01:09.5281840Z * [new tag] trunk/d5b4a329607514b30944c7682efcf79cf8950ed3 -> trunk/d5b4a329607514b30944c7682efcf79cf8950ed3 2025-07-17T07:01:09.5282763Z * [new tag] trunk/d5d14ee823e70224a154884a5c2912643d648094 -> trunk/d5d14ee823e70224a154884a5c2912643d648094 2025-07-17T07:01:09.5283718Z * [new tag] trunk/d5e6f4209424b96237ea5468dd47899e1124dfcb -> trunk/d5e6f4209424b96237ea5468dd47899e1124dfcb 2025-07-17T07:01:09.5285055Z * [new tag] trunk/d6237721c074484ea5e72fc05614587886e57fd6 -> trunk/d6237721c074484ea5e72fc05614587886e57fd6 2025-07-17T07:01:09.5286002Z * [new tag] trunk/d632cf2cc9aac8ab0e03d1537982265e42be95e5 -> trunk/d632cf2cc9aac8ab0e03d1537982265e42be95e5 2025-07-17T07:01:09.5287539Z * [new tag] trunk/d66b4bcc3f89ac6b9d2ccfd4cb01b0aa85d4e3fd -> trunk/d66b4bcc3f89ac6b9d2ccfd4cb01b0aa85d4e3fd 2025-07-17T07:01:09.5288253Z * [new tag] trunk/d6ee5144cab20141c8e0cf48856a90a6517753f1 -> trunk/d6ee5144cab20141c8e0cf48856a90a6517753f1 2025-07-17T07:01:09.5289417Z * [new tag] trunk/d75d30eeb610b164e69d0678a2e2b2dea81eec0f -> trunk/d75d30eeb610b164e69d0678a2e2b2dea81eec0f 2025-07-17T07:01:09.5290206Z * [new tag] trunk/d76323d41742cbc05ec6857319b267d2c7ea8fd9 -> trunk/d76323d41742cbc05ec6857319b267d2c7ea8fd9 2025-07-17T07:01:09.5291044Z * [new tag] trunk/d79651571fb082a7a20631059563ecdf9d11b7e6 -> trunk/d79651571fb082a7a20631059563ecdf9d11b7e6 2025-07-17T07:01:09.5291966Z * [new tag] trunk/d797038ea9f3951c7602e8710f4866f73d7e7acd -> trunk/d797038ea9f3951c7602e8710f4866f73d7e7acd 2025-07-17T07:01:09.5292871Z * [new tag] trunk/d7e1b8b11d7430c7633dcad6f6596b5df8fa02f7 -> trunk/d7e1b8b11d7430c7633dcad6f6596b5df8fa02f7 2025-07-17T07:01:09.5293834Z * [new tag] trunk/d7e3c9ce8289f26704b140e68dac2849df750040 -> trunk/d7e3c9ce8289f26704b140e68dac2849df750040 2025-07-17T07:01:09.5294709Z * [new tag] trunk/d7e657da358d6d393e2105f94f1312fb969654a2 -> trunk/d7e657da358d6d393e2105f94f1312fb969654a2 2025-07-17T07:01:09.5295699Z * [new tag] trunk/d83ff89d3bf54ecc95d441411ecbf07831cc0e5a -> trunk/d83ff89d3bf54ecc95d441411ecbf07831cc0e5a 2025-07-17T07:01:09.5296595Z * [new tag] trunk/d846e213553621cb4581f1f36ac0023e528ddb65 -> trunk/d846e213553621cb4581f1f36ac0023e528ddb65 2025-07-17T07:01:09.5297849Z * [new tag] trunk/d84efde3f02bdc4780e5c9ec43f9c515c744e9be -> trunk/d84efde3f02bdc4780e5c9ec43f9c515c744e9be 2025-07-17T07:01:09.5298674Z * [new tag] trunk/d859e65826d511f8379db4a8c4109417e26e0772 -> trunk/d859e65826d511f8379db4a8c4109417e26e0772 2025-07-17T07:01:09.5299631Z * [new tag] trunk/d89f30ad45b9d4bfe5cf5ab441b53e849e55df7b -> trunk/d89f30ad45b9d4bfe5cf5ab441b53e849e55df7b 2025-07-17T07:01:09.5300592Z * [new tag] trunk/d8bb5ac260dd81f75c8add6eadd8ce11e62be1a3 -> trunk/d8bb5ac260dd81f75c8add6eadd8ce11e62be1a3 2025-07-17T07:01:09.5301739Z * [new tag] trunk/d9426a81d2ab54f809a3b32a6ab2e606073fe66f -> trunk/d9426a81d2ab54f809a3b32a6ab2e606073fe66f 2025-07-17T07:01:09.5302604Z * [new tag] trunk/d9577df312d477e8fa5b9d7bc61fb1f2c07b8e48 -> trunk/d9577df312d477e8fa5b9d7bc61fb1f2c07b8e48 2025-07-17T07:01:09.5303486Z * [new tag] trunk/d96dec84151dfdea1aa2bf568deebdc182214f45 -> trunk/d96dec84151dfdea1aa2bf568deebdc182214f45 2025-07-17T07:01:09.5304605Z * [new tag] trunk/d9799a2ee7adb9d15f7a2d47ee17fc39c588af60 -> trunk/d9799a2ee7adb9d15f7a2d47ee17fc39c588af60 2025-07-17T07:01:09.5305337Z * [new tag] trunk/d98fa4a1033079ae19591aff5c3c354617bff482 -> trunk/d98fa4a1033079ae19591aff5c3c354617bff482 2025-07-17T07:01:09.5306246Z * [new tag] trunk/d99cac28160428a8b006890abffaaa0754bd28e1 -> trunk/d99cac28160428a8b006890abffaaa0754bd28e1 2025-07-17T07:01:09.5307118Z * [new tag] trunk/d9b8369f3976e89eef96c903dfede746fb438f63 -> trunk/d9b8369f3976e89eef96c903dfede746fb438f63 2025-07-17T07:01:09.5307969Z * [new tag] trunk/da05b7fb94fa6382c43e165a525a76d8ae62cadd -> trunk/da05b7fb94fa6382c43e165a525a76d8ae62cadd 2025-07-17T07:01:09.5308835Z * [new tag] trunk/da1f337bc43ce2d720aca1349f9c09712e037382 -> trunk/da1f337bc43ce2d720aca1349f9c09712e037382 2025-07-17T07:01:09.5309754Z * [new tag] trunk/da1f8980dfd646f14dc33bf0bc70fcb4d09096b3 -> trunk/da1f8980dfd646f14dc33bf0bc70fcb4d09096b3 2025-07-17T07:01:09.5310734Z * [new tag] trunk/da4e7c77a12746b0806a63af58d7c913ed241f55 -> trunk/da4e7c77a12746b0806a63af58d7c913ed241f55 2025-07-17T07:01:09.5311610Z * [new tag] trunk/da50835bdebd43275e0be4b1362e1bb92b568e72 -> trunk/da50835bdebd43275e0be4b1362e1bb92b568e72 2025-07-17T07:01:09.5312551Z * [new tag] trunk/da910e603a764c1f935dd0409b4c18bd84b1f045 -> trunk/da910e603a764c1f935dd0409b4c18bd84b1f045 2025-07-17T07:01:09.5313504Z * [new tag] trunk/dabb55baff2292ddd7728882b4e2113b8cb9e23b -> trunk/dabb55baff2292ddd7728882b4e2113b8cb9e23b 2025-07-17T07:01:09.5314507Z * [new tag] trunk/db01f1032ff133dc7cc3097b76bfb1b73ff533ce -> trunk/db01f1032ff133dc7cc3097b76bfb1b73ff533ce 2025-07-17T07:01:09.5315390Z * [new tag] trunk/db188503cb705230664c94d8b3a85165a00d632d -> trunk/db188503cb705230664c94d8b3a85165a00d632d 2025-07-17T07:01:09.5316638Z * [new tag] trunk/db491825e05e8bed9c7ed5d9fdd6ce206ab3167c -> trunk/db491825e05e8bed9c7ed5d9fdd6ce206ab3167c 2025-07-17T07:01:09.5317408Z * [new tag] trunk/db5970c1a67968f3b76d204d75789021d4304337 -> trunk/db5970c1a67968f3b76d204d75789021d4304337 2025-07-17T07:01:09.5318552Z * [new tag] trunk/dbec08bc1cc9113c13652128a4ddcfcf2426a8c0 -> trunk/dbec08bc1cc9113c13652128a4ddcfcf2426a8c0 2025-07-17T07:01:09.5319427Z * [new tag] trunk/dbf7d421dabced2335d17c7d7e57c1770f2f12c0 -> trunk/dbf7d421dabced2335d17c7d7e57c1770f2f12c0 2025-07-17T07:01:09.5320356Z * [new tag] trunk/dc5e8f7999cccb51efcf0f5fe197a740a918c73d -> trunk/dc5e8f7999cccb51efcf0f5fe197a740a918c73d 2025-07-17T07:01:09.5321261Z * [new tag] trunk/dcb97cd519e4e4974bc3bd4960512b557216f3e6 -> trunk/dcb97cd519e4e4974bc3bd4960512b557216f3e6 2025-07-17T07:01:09.5322217Z * [new tag] trunk/dd1b6621bc04a37b60ac304d913a3c838b0b1e4d -> trunk/dd1b6621bc04a37b60ac304d913a3c838b0b1e4d 2025-07-17T07:01:09.5323243Z * [new tag] trunk/dd3e7170c20cade9a308900aa4df46ab7656d253 -> trunk/dd3e7170c20cade9a308900aa4df46ab7656d253 2025-07-17T07:01:09.5324123Z * [new tag] trunk/dd41a3907cde3ce19fb69bd79c4055233a1e28d3 -> trunk/dd41a3907cde3ce19fb69bd79c4055233a1e28d3 2025-07-17T07:01:09.5325128Z * [new tag] trunk/dd78d6e7eaecf0aa5317076a721bc719c96b41f8 -> trunk/dd78d6e7eaecf0aa5317076a721bc719c96b41f8 2025-07-17T07:01:09.5325958Z * [new tag] trunk/dd93883231226576220a8ec0fa266c9e22eae82c -> trunk/dd93883231226576220a8ec0fa266c9e22eae82c 2025-07-17T07:01:09.5326953Z * [new tag] trunk/ddf502c988133835a89959bef945bf9c5f06b428 -> trunk/ddf502c988133835a89959bef945bf9c5f06b428 2025-07-17T07:01:09.5327854Z * [new tag] trunk/de1930a4290a27f3f03dd1d3454fb6ef9d12f3ea -> trunk/de1930a4290a27f3f03dd1d3454fb6ef9d12f3ea 2025-07-17T07:01:09.5328829Z * [new tag] trunk/de45c5f673ce261e9a82c54280beeda36cff640e -> trunk/de45c5f673ce261e9a82c54280beeda36cff640e 2025-07-17T07:01:09.5329779Z * [new tag] trunk/dea4864ce08115a0cdc871b84dd3080567d8b5e4 -> trunk/dea4864ce08115a0cdc871b84dd3080567d8b5e4 2025-07-17T07:01:09.5330690Z * [new tag] trunk/df72078fe1339751e702c7511c23b4597d022dcc -> trunk/df72078fe1339751e702c7511c23b4597d022dcc 2025-07-17T07:01:09.5331605Z * [new tag] trunk/dfa2649434f539d7580d38f08890176e73d45158 -> trunk/dfa2649434f539d7580d38f08890176e73d45158 2025-07-17T07:01:09.5332755Z * [new tag] trunk/dfc31b3345d78b0a49d446dcc1957404606a3aa2 -> trunk/dfc31b3345d78b0a49d446dcc1957404606a3aa2 2025-07-17T07:01:09.5333681Z * [new tag] trunk/dfcda613b65499e4b593b5bbb64812d57194858e -> trunk/dfcda613b65499e4b593b5bbb64812d57194858e 2025-07-17T07:01:09.5334619Z * [new tag] trunk/dfdd636cfa06ac70c4aa7ad5ee5e854c46b25a8e -> trunk/dfdd636cfa06ac70c4aa7ad5ee5e854c46b25a8e 2025-07-17T07:01:09.5335493Z * [new tag] trunk/dfef1e44085bb156abc4aff0f34a0b82a4a337b8 -> trunk/dfef1e44085bb156abc4aff0f34a0b82a4a337b8 2025-07-17T07:01:09.5336440Z * [new tag] trunk/e01fde82131c7f0b4c122222694911ee6fab36ca -> trunk/e01fde82131c7f0b4c122222694911ee6fab36ca 2025-07-17T07:01:09.5337351Z * [new tag] trunk/e0447bb5f84dca38e7515d1b1fdea42c647e5acd -> trunk/e0447bb5f84dca38e7515d1b1fdea42c647e5acd 2025-07-17T07:01:09.5338271Z * [new tag] trunk/e071837594f26a3bbaeee11eaa74f3bfd9c998ce -> trunk/e071837594f26a3bbaeee11eaa74f3bfd9c998ce 2025-07-17T07:01:09.5339176Z * [new tag] trunk/e0850123355a919427be3cb02f40c9a9e144fc3c -> trunk/e0850123355a919427be3cb02f40c9a9e144fc3c 2025-07-17T07:01:09.5340202Z * [new tag] trunk/e0ab1b538a646bff0739830d74a8e6ea6bf1eddd -> trunk/e0ab1b538a646bff0739830d74a8e6ea6bf1eddd 2025-07-17T07:01:09.5341092Z * [new tag] trunk/e0ae4ecca87928a96c97fb60cbb36aca0fc182f2 -> trunk/e0ae4ecca87928a96c97fb60cbb36aca0fc182f2 2025-07-17T07:01:09.5342088Z * [new tag] trunk/e0fd48be7d526625cacfd093f3db13506ca9cc17 -> trunk/e0fd48be7d526625cacfd093f3db13506ca9cc17 2025-07-17T07:01:09.5343584Z * [new tag] trunk/e1180c7228ba8c8b16cabf78706d4a67ca189a6b -> trunk/e1180c7228ba8c8b16cabf78706d4a67ca189a6b 2025-07-17T07:01:09.5344570Z * [new tag] trunk/e124a0d88ca2aa04bfaca2dcabf5de6244048e45 -> trunk/e124a0d88ca2aa04bfaca2dcabf5de6244048e45 2025-07-17T07:01:09.5345374Z * [new tag] trunk/e12597090c482ebf1eff7739794667a92cbff657 -> trunk/e12597090c482ebf1eff7739794667a92cbff657 2025-07-17T07:01:09.5346352Z * [new tag] trunk/e15848669f84d3767bfca724a29a6a6dde3308b9 -> trunk/e15848669f84d3767bfca724a29a6a6dde3308b9 2025-07-17T07:01:09.5347309Z * [new tag] trunk/e15ea965a1e84029eb900b93f5776767a39fd91e -> trunk/e15ea965a1e84029eb900b93f5776767a39fd91e 2025-07-17T07:01:09.5348724Z * [new tag] trunk/e15f4248ad2797539f1bf965bd0a3500b8ed15ed -> trunk/e15f4248ad2797539f1bf965bd0a3500b8ed15ed 2025-07-17T07:01:09.5349549Z * [new tag] trunk/e1723098805fcbf3ab7f3d20750fb0665bf65004 -> trunk/e1723098805fcbf3ab7f3d20750fb0665bf65004 2025-07-17T07:01:09.5350525Z * [new tag] trunk/e1a20988f3724317a7ee79c1777d574a8282a122 -> trunk/e1a20988f3724317a7ee79c1777d574a8282a122 2025-07-17T07:01:09.5352029Z * [new tag] trunk/e1aee86646aa6d1b9cb9d34351e43936401c5efc -> trunk/e1aee86646aa6d1b9cb9d34351e43936401c5efc 2025-07-17T07:01:09.5352861Z * [new tag] trunk/e1db10e05aa720aef1989773adcf48f311bcf920 -> trunk/e1db10e05aa720aef1989773adcf48f311bcf920 2025-07-17T07:01:09.5353696Z * [new tag] trunk/e1f28fe17bc55389fc5a31bad588d22e5ecca722 -> trunk/e1f28fe17bc55389fc5a31bad588d22e5ecca722 2025-07-17T07:01:09.5354639Z * [new tag] trunk/e20784f228abca24ab263cf0f69534667365ecba -> trunk/e20784f228abca24ab263cf0f69534667365ecba 2025-07-17T07:01:09.5355571Z * [new tag] trunk/e2351f2dcf7d300460edb9d0c2eb0ea11cc547c5 -> trunk/e2351f2dcf7d300460edb9d0c2eb0ea11cc547c5 2025-07-17T07:01:09.5356490Z * [new tag] trunk/e25ce0f928bfdd545323fcc2f88209233309bbbc -> trunk/e25ce0f928bfdd545323fcc2f88209233309bbbc 2025-07-17T07:01:09.5357330Z * [new tag] trunk/e265b719bd67f7c0a2b9001daef442a70232dcc8 -> trunk/e265b719bd67f7c0a2b9001daef442a70232dcc8 2025-07-17T07:01:09.5358256Z * [new tag] trunk/e28925aa7566da3ffe4f13dd8d59a6767bf97b2e -> trunk/e28925aa7566da3ffe4f13dd8d59a6767bf97b2e 2025-07-17T07:01:09.5359146Z * [new tag] trunk/e290a4c645e00926f0bfa44488f9f7dbd7cb2d0b -> trunk/e290a4c645e00926f0bfa44488f9f7dbd7cb2d0b 2025-07-17T07:01:09.5360143Z * [new tag] trunk/e2c9d8d6414927ce754bbc40b767edf103cf16da -> trunk/e2c9d8d6414927ce754bbc40b767edf103cf16da 2025-07-17T07:01:09.5361004Z * [new tag] trunk/e2f64eedafc6f0dcad9256ac1f38c0359477679a -> trunk/e2f64eedafc6f0dcad9256ac1f38c0359477679a 2025-07-17T07:01:09.5361914Z * [new tag] trunk/e311886e3d57c83a88b97a084dd0b95d6d1537a8 -> trunk/e311886e3d57c83a88b97a084dd0b95d6d1537a8 2025-07-17T07:01:09.5362862Z * [new tag] trunk/e31f20529276356092b5c63c2920d5b17ca9f4ba -> trunk/e31f20529276356092b5c63c2920d5b17ca9f4ba 2025-07-17T07:01:09.5364002Z * [new tag] trunk/e323d46b617c1552cc0f017ad8ec80189eacf187 -> trunk/e323d46b617c1552cc0f017ad8ec80189eacf187 2025-07-17T07:01:09.5364844Z * [new tag] trunk/e3320965b48d87b7257997c35db722302d923ead -> trunk/e3320965b48d87b7257997c35db722302d923ead 2025-07-17T07:01:09.5365914Z * [new tag] trunk/e375d21bb9b0ef6fefe7a8af5a054a17de8c63c9 -> trunk/e375d21bb9b0ef6fefe7a8af5a054a17de8c63c9 2025-07-17T07:01:09.5366823Z * [new tag] trunk/e3977e843de6c9c43be00ee8c67c533debfc0dc9 -> trunk/e3977e843de6c9c43be00ee8c67c533debfc0dc9 2025-07-17T07:01:09.5367737Z * [new tag] trunk/e3afbb03623559fa3fa7ba607c07c86ebed889f0 -> trunk/e3afbb03623559fa3fa7ba607c07c86ebed889f0 2025-07-17T07:01:09.5368960Z * [new tag] trunk/e3b44edfd837199880aed3ec802383617da731f3 -> trunk/e3b44edfd837199880aed3ec802383617da731f3 2025-07-17T07:01:09.5369869Z * [new tag] trunk/e3f2597b4529927b812b443cf8da19b44ed8dea4 -> trunk/e3f2597b4529927b812b443cf8da19b44ed8dea4 2025-07-17T07:01:09.5370973Z * [new tag] trunk/e3f8141c25b7213885f0b7b64f2b0ccc7858be95 -> trunk/e3f8141c25b7213885f0b7b64f2b0ccc7858be95 2025-07-17T07:01:09.5371943Z * [new tag] trunk/e3fe001d9e38153a7797ad25377fdfa34e461113 -> trunk/e3fe001d9e38153a7797ad25377fdfa34e461113 2025-07-17T07:01:09.5372857Z * [new tag] trunk/e40ade5182233f548b25f2732effe3719d16e9ad -> trunk/e40ade5182233f548b25f2732effe3719d16e9ad 2025-07-17T07:01:09.5373839Z * [new tag] trunk/e466dab164d9236bfe5817ec8e4d24c7b9d3e392 -> trunk/e466dab164d9236bfe5817ec8e4d24c7b9d3e392 2025-07-17T07:01:09.5374730Z * [new tag] trunk/e472daa80963aae389089f9dc324b04261e2a5ef -> trunk/e472daa80963aae389089f9dc324b04261e2a5ef 2025-07-17T07:01:09.5375727Z * [new tag] trunk/e4ae60a413b99688d308794baaa1c685b5c19025 -> trunk/e4ae60a413b99688d308794baaa1c685b5c19025 2025-07-17T07:01:09.5376666Z * [new tag] trunk/e4c17d5e1ccd0e730caef484af291243bc1d9cde -> trunk/e4c17d5e1ccd0e730caef484af291243bc1d9cde 2025-07-17T07:01:09.5377789Z * [new tag] trunk/e4c9f6d9a286bd367ce3a157428f588e267d2630 -> trunk/e4c9f6d9a286bd367ce3a157428f588e267d2630 2025-07-17T07:01:09.5378613Z * [new tag] trunk/e517066f41342f0f01043121dcb8ac6b235ee40c -> trunk/e517066f41342f0f01043121dcb8ac6b235ee40c 2025-07-17T07:01:09.5379532Z * [new tag] trunk/e53ddaf1f6ef3f1d22075ad33a5922fb8b277fe0 -> trunk/e53ddaf1f6ef3f1d22075ad33a5922fb8b277fe0 2025-07-17T07:01:09.5380421Z * [new tag] trunk/e581f015eebf483eb6f19447caf2d2452a602c2f -> trunk/e581f015eebf483eb6f19447caf2d2452a602c2f 2025-07-17T07:01:09.5381330Z * [new tag] trunk/e583b888194c8c74ebbd332c09c394acebbbbcff -> trunk/e583b888194c8c74ebbd332c09c394acebbbbcff 2025-07-17T07:01:09.5382299Z * [new tag] trunk/e5a0b73ce9e7bc489150932b60f673155d6ddc30 -> trunk/e5a0b73ce9e7bc489150932b60f673155d6ddc30 2025-07-17T07:01:09.5383226Z * [new tag] trunk/e5a11971919009b5e5bd050b3ed52e324f1ce894 -> trunk/e5a11971919009b5e5bd050b3ed52e324f1ce894 2025-07-17T07:01:09.5384196Z * [new tag] trunk/e5ea24fb27e0ef5dbb0c4039d88c0f4faa221fef -> trunk/e5ea24fb27e0ef5dbb0c4039d88c0f4faa221fef 2025-07-17T07:01:09.5385079Z * [new tag] trunk/e5ed267f830ce9fc6579f928082e563fbed37e3f -> trunk/e5ed267f830ce9fc6579f928082e563fbed37e3f 2025-07-17T07:01:09.5386045Z * [new tag] trunk/e5edd013ab418b8b3609cb3cb1df3804b69d8eef -> trunk/e5edd013ab418b8b3609cb3cb1df3804b69d8eef 2025-07-17T07:01:09.5386913Z * [new tag] trunk/e5f6ffd8109bee99416d9b127f961ab0e253a1c2 -> trunk/e5f6ffd8109bee99416d9b127f961ab0e253a1c2 2025-07-17T07:01:09.5387860Z * [new tag] trunk/e600e044a770d29d1fe5d9638b274a7d4f22f969 -> trunk/e600e044a770d29d1fe5d9638b274a7d4f22f969 2025-07-17T07:01:09.5388797Z * [new tag] trunk/e6252f62efa5e6e4ab0d56967d7461f1e8a7eb7c -> trunk/e6252f62efa5e6e4ab0d56967d7461f1e8a7eb7c 2025-07-17T07:01:09.5389723Z * [new tag] trunk/e694280d1215caf70f41575f2611bfa26c69ebdb -> trunk/e694280d1215caf70f41575f2611bfa26c69ebdb 2025-07-17T07:01:09.5390662Z * [new tag] trunk/e6d71f37896e99ced7daf9ee43a30c0ec03d60f2 -> trunk/e6d71f37896e99ced7daf9ee43a30c0ec03d60f2 2025-07-17T07:01:09.5391915Z * [new tag] trunk/e6d8ed02cbeabe961d1a5303973a6d89ee851736 -> trunk/e6d8ed02cbeabe961d1a5303973a6d89ee851736 2025-07-17T07:01:09.5392724Z * [new tag] trunk/e6ed4074e8411000eea2f0de0c0829d909e4701f -> trunk/e6ed4074e8411000eea2f0de0c0829d909e4701f 2025-07-17T07:01:09.5393611Z * [new tag] trunk/e71bb021b9553ddc2db6cb8ea7bf8643552f09fc -> trunk/e71bb021b9553ddc2db6cb8ea7bf8643552f09fc 2025-07-17T07:01:09.5394797Z * [new tag] trunk/e7698ff5cf40729d11df6c32c6df0a163e5d0ce0 -> trunk/e7698ff5cf40729d11df6c32c6df0a163e5d0ce0 2025-07-17T07:01:09.5395765Z * [new tag] trunk/e78f2ac92b709a060aa323d6e527ec2ecc36fb93 -> trunk/e78f2ac92b709a060aa323d6e527ec2ecc36fb93 2025-07-17T07:01:09.5396940Z * [new tag] trunk/e7a66166ce5294a52bf3966aef49562f94343475 -> trunk/e7a66166ce5294a52bf3966aef49562f94343475 2025-07-17T07:01:09.5397815Z * [new tag] trunk/e7da21806fbc96d47ac03ea8f6507deb0ab48481 -> trunk/e7da21806fbc96d47ac03ea8f6507deb0ab48481 2025-07-17T07:01:09.5398735Z * [new tag] trunk/e8217ad8becd2b297682c685a9179997cb0a98cc -> trunk/e8217ad8becd2b297682c685a9179997cb0a98cc 2025-07-17T07:01:09.5399669Z * [new tag] trunk/e895e9689c625cbcd8f46880115e0d093713fa37 -> trunk/e895e9689c625cbcd8f46880115e0d093713fa37 2025-07-17T07:01:09.5400610Z * [new tag] trunk/e8b3dfa7c0b6d74fc84714dbb79cb6a8bad43ae7 -> trunk/e8b3dfa7c0b6d74fc84714dbb79cb6a8bad43ae7 2025-07-17T07:01:09.5401498Z * [new tag] trunk/e8bfce9a43960f417a36636a0e7f6a58b7dc56d2 -> trunk/e8bfce9a43960f417a36636a0e7f6a58b7dc56d2 2025-07-17T07:01:09.5402450Z * [new tag] trunk/e8cf5ff5641c1ce4c3046a85df55b15eaaea38b2 -> trunk/e8cf5ff5641c1ce4c3046a85df55b15eaaea38b2 2025-07-17T07:01:09.5403427Z * [new tag] trunk/e8d29c45e02402bcb4ae7726abd415bebd441852 -> trunk/e8d29c45e02402bcb4ae7726abd415bebd441852 2025-07-17T07:01:09.5404355Z * [new tag] trunk/e90148c91d3b8a759db558374c8539e47338926b -> trunk/e90148c91d3b8a759db558374c8539e47338926b 2025-07-17T07:01:09.5405639Z * [new tag] trunk/e92e3eaf4eb815ea28db9a5af9d9ee48c3f7be3f -> trunk/e92e3eaf4eb815ea28db9a5af9d9ee48c3f7be3f 2025-07-17T07:01:09.5406524Z * [new tag] trunk/e9367a7a4288e626f01fada3912d68756f1ca6d3 -> trunk/e9367a7a4288e626f01fada3912d68756f1ca6d3 2025-07-17T07:01:09.5407670Z * [new tag] trunk/e959dd017d7dcd7c6351c9ef303f3667aebe11f5 -> trunk/e959dd017d7dcd7c6351c9ef303f3667aebe11f5 2025-07-17T07:01:09.5408544Z * [new tag] trunk/e95e8eed0a96f024dc84012494f465b34eae9d22 -> trunk/e95e8eed0a96f024dc84012494f465b34eae9d22 2025-07-17T07:01:09.5409418Z * [new tag] trunk/e96f530af5bf8ceaeaa87ec7f4651490a25bce07 -> trunk/e96f530af5bf8ceaeaa87ec7f4651490a25bce07 2025-07-17T07:01:09.5410845Z * [new tag] trunk/e98dd95446e009ace1722498effbf32250d623e4 -> trunk/e98dd95446e009ace1722498effbf32250d623e4 2025-07-17T07:01:09.5411692Z * [new tag] trunk/e99a2a2dba90c9b6276219104bc99aff2f67e2f7 -> trunk/e99a2a2dba90c9b6276219104bc99aff2f67e2f7 2025-07-17T07:01:09.5412641Z * [new tag] trunk/e99cc126a4f4bd5233ff363f27d14a0fff4b4392 -> trunk/e99cc126a4f4bd5233ff363f27d14a0fff4b4392 2025-07-17T07:01:09.5413547Z * [new tag] trunk/e9fdaf8701b599fd943bb899639b5e8a4966b3c3 -> trunk/e9fdaf8701b599fd943bb899639b5e8a4966b3c3 2025-07-17T07:01:09.5414490Z * [new tag] trunk/ea23eb4b98ae8af40f0c38538a9e63f1b0dc40e2 -> trunk/ea23eb4b98ae8af40f0c38538a9e63f1b0dc40e2 2025-07-17T07:01:09.5415287Z * [new tag] trunk/ea37f720995616d8570045c63486198a021f8285 -> trunk/ea37f720995616d8570045c63486198a021f8285 2025-07-17T07:01:09.5416224Z * [new tag] trunk/ea74fdd24aa7d98433231f4a3d75cfd241d8720e -> trunk/ea74fdd24aa7d98433231f4a3d75cfd241d8720e 2025-07-17T07:01:09.5417176Z * [new tag] trunk/eab45643f22e58ee12d95d8b0162d51ca0a50801 -> trunk/eab45643f22e58ee12d95d8b0162d51ca0a50801 2025-07-17T07:01:09.5418032Z * [new tag] trunk/eabf7cd3c552e6c17321a63d7e5a19da92909910 -> trunk/eabf7cd3c552e6c17321a63d7e5a19da92909910 2025-07-17T07:01:09.5418959Z * [new tag] trunk/eaceb243df6fc17a37a2c1d9f8775d1561a0f67c -> trunk/eaceb243df6fc17a37a2c1d9f8775d1561a0f67c 2025-07-17T07:01:09.5419909Z * [new tag] trunk/eaf32fffb7e83b5331951b254ad213ceb2ae72f8 -> trunk/eaf32fffb7e83b5331951b254ad213ceb2ae72f8 2025-07-17T07:01:09.5421069Z * [new tag] trunk/eaf704914eb63efffafeb402633f76f2cd521ef4 -> trunk/eaf704914eb63efffafeb402633f76f2cd521ef4 2025-07-17T07:01:09.5421892Z * [new tag] trunk/eb152ab1dd9eafc777b6642bb141ab1b8376359a -> trunk/eb152ab1dd9eafc777b6642bb141ab1b8376359a 2025-07-17T07:01:09.5422808Z * [new tag] trunk/eb2af14f8e75c22c0a2fcf407005d2e8173d0df5 -> trunk/eb2af14f8e75c22c0a2fcf407005d2e8173d0df5 2025-07-17T07:01:09.5423687Z * [new tag] trunk/eb331b59fedb7f70229ca491029f2f7f27bbff54 -> trunk/eb331b59fedb7f70229ca491029f2f7f27bbff54 2025-07-17T07:01:09.5424603Z * [new tag] trunk/eb4cf59ecdf69dd53805a37525a7f750c8f1e0dd -> trunk/eb4cf59ecdf69dd53805a37525a7f750c8f1e0dd 2025-07-17T07:01:09.5425667Z * [new tag] trunk/eb9efb37c8f315f1d30e86d5797490c6a8666889 -> trunk/eb9efb37c8f315f1d30e86d5797490c6a8666889 2025-07-17T07:01:09.5426755Z * [new tag] trunk/eba5fc91ac924a7a05569c33b0f90f0faf22696d -> trunk/eba5fc91ac924a7a05569c33b0f90f0faf22696d 2025-07-17T07:01:09.5427603Z * [new tag] trunk/ebab2799423987a16975ab07ee49dd944e5315e6 -> trunk/ebab2799423987a16975ab07ee49dd944e5315e6 2025-07-17T07:01:09.5428476Z * [new tag] trunk/ebf83b8b7772632c0558db9a88281ee10ff2df38 -> trunk/ebf83b8b7772632c0558db9a88281ee10ff2df38 2025-07-17T07:01:09.5429428Z * [new tag] trunk/ec0276103fc023b93c6eb17639d4605656ea4f10 -> trunk/ec0276103fc023b93c6eb17639d4605656ea4f10 2025-07-17T07:01:09.5430404Z * [new tag] trunk/ec08eb8ba22e66b113e4f2aba1f6afb738f9d861 -> trunk/ec08eb8ba22e66b113e4f2aba1f6afb738f9d861 2025-07-17T07:01:09.5431228Z * [new tag] trunk/ec816d73b4c8f74a14e275891939de6cfd6891b6 -> trunk/ec816d73b4c8f74a14e275891939de6cfd6891b6 2025-07-17T07:01:09.5432109Z * [new tag] trunk/ecd73c58eeaf7e919316f9b9596f8c677af96c66 -> trunk/ecd73c58eeaf7e919316f9b9596f8c677af96c66 2025-07-17T07:01:09.5433242Z * [new tag] trunk/ed03492238c9ef76f5c1df6cfa54da83a2a384e1 -> trunk/ed03492238c9ef76f5c1df6cfa54da83a2a384e1 2025-07-17T07:01:09.5433950Z * [new tag] trunk/ed051c308464904e07d33c39524b3931dc8c947a -> trunk/ed051c308464904e07d33c39524b3931dc8c947a 2025-07-17T07:01:09.5435067Z * [new tag] trunk/ed508cc0182b923789555d4e1ec1f8b23707b7db -> trunk/ed508cc0182b923789555d4e1ec1f8b23707b7db 2025-07-17T07:01:09.5435955Z * [new tag] trunk/ed5d6d2a200a0f03b164053322341bb10acc051d -> trunk/ed5d6d2a200a0f03b164053322341bb10acc051d 2025-07-17T07:01:09.5436798Z * [new tag] trunk/ed661a5f11de116539f70882f4f59a61d5e3e209 -> trunk/ed661a5f11de116539f70882f4f59a61d5e3e209 2025-07-17T07:01:09.5437682Z * [new tag] trunk/ed6ae20cf0e31d49d54177251293267205e24021 -> trunk/ed6ae20cf0e31d49d54177251293267205e24021 2025-07-17T07:01:09.5438626Z * [new tag] trunk/ed6df0e324233fda094e3c1cb4de4009d1ba2413 -> trunk/ed6df0e324233fda094e3c1cb4de4009d1ba2413 2025-07-17T07:01:09.5439844Z * [new tag] trunk/ed911747c2a56cf84d648d677403d5bf6b2ebd0b -> trunk/ed911747c2a56cf84d648d677403d5bf6b2ebd0b 2025-07-17T07:01:09.5440759Z * [new tag] trunk/eda0a9cc90b9a63127a49d617329f98b6404e90d -> trunk/eda0a9cc90b9a63127a49d617329f98b6404e90d 2025-07-17T07:01:09.5441977Z * [new tag] trunk/edb92e16ba9ad12bd51c4f73389556e163e9cc08 -> trunk/edb92e16ba9ad12bd51c4f73389556e163e9cc08 2025-07-17T07:01:09.5442909Z * [new tag] trunk/edd45f3a020f892c17672cc2d08f64cb960006ad -> trunk/edd45f3a020f892c17672cc2d08f64cb960006ad 2025-07-17T07:01:09.5443812Z * [new tag] trunk/edd9c09e73aaa8d1a1667fa7ea5a337aa31fa6ec -> trunk/edd9c09e73aaa8d1a1667fa7ea5a337aa31fa6ec 2025-07-17T07:01:09.5444771Z * [new tag] trunk/eddddea9087a8840ce5ae1bbb3c6f59556d7c0f0 -> trunk/eddddea9087a8840ce5ae1bbb3c6f59556d7c0f0 2025-07-17T07:01:09.5445741Z * [new tag] trunk/ede6ead8cd8e925cb093f2b3016342e645bd728d -> trunk/ede6ead8cd8e925cb093f2b3016342e645bd728d 2025-07-17T07:01:09.5446619Z * [new tag] trunk/edf7bb4f514220f96ddfa646ae6e9e930a305ec1 -> trunk/edf7bb4f514220f96ddfa646ae6e9e930a305ec1 2025-07-17T07:01:09.5447413Z * [new tag] trunk/ee0992871c99fc6a1e19eb839ab65391a168d2f8 -> trunk/ee0992871c99fc6a1e19eb839ab65391a168d2f8 2025-07-17T07:01:09.5448359Z * [new tag] trunk/ee4d343499c80be16a58d5ac604da6e2130cd94d -> trunk/ee4d343499c80be16a58d5ac604da6e2130cd94d 2025-07-17T07:01:09.5449453Z * [new tag] trunk/ee56e9f8a8202bfa02c2d9ae3cfa07d4a41ab567 -> trunk/ee56e9f8a8202bfa02c2d9ae3cfa07d4a41ab567 2025-07-17T07:01:09.5450334Z * [new tag] trunk/ee5c2908cbfcbda6e8a5737d9939d36ba417d627 -> trunk/ee5c2908cbfcbda6e8a5737d9939d36ba417d627 2025-07-17T07:01:09.5451284Z * [new tag] trunk/ee9ac36c2316f430c4de2a0982bde3cb8087cbe7 -> trunk/ee9ac36c2316f430c4de2a0982bde3cb8087cbe7 2025-07-17T07:01:09.5452181Z * [new tag] trunk/eea3bcb3d146f16a8f8c91a9e2a8f1b76c5917f4 -> trunk/eea3bcb3d146f16a8f8c91a9e2a8f1b76c5917f4 2025-07-17T07:01:09.5453357Z * [new tag] trunk/eeaefa133694811aac1fd215bcae2e7f1e098d1d -> trunk/eeaefa133694811aac1fd215bcae2e7f1e098d1d 2025-07-17T07:01:09.5454226Z * [new tag] trunk/eecaa0bbc6a39c89366f9ec97797479c27f6d760 -> trunk/eecaa0bbc6a39c89366f9ec97797479c27f6d760 2025-07-17T07:01:09.5455469Z * [new tag] trunk/eef253d9f6fc8b9774d199889a817f50e89572c2 -> trunk/eef253d9f6fc8b9774d199889a817f50e89572c2 2025-07-17T07:01:09.5456700Z * [new tag] trunk/ef4cca2d79eba61441da46906b30f8f6165cc455 -> trunk/ef4cca2d79eba61441da46906b30f8f6165cc455 2025-07-17T07:01:09.5457576Z * [new tag] trunk/ef6d2cee7a93c1e8f52a7595b6f630d0fcd83692 -> trunk/ef6d2cee7a93c1e8f52a7595b6f630d0fcd83692 2025-07-17T07:01:09.5458478Z * [new tag] trunk/ef6dfa06a9ff84bf04b0d83cfab4cb396a508a0e -> trunk/ef6dfa06a9ff84bf04b0d83cfab4cb396a508a0e 2025-07-17T07:01:09.5459396Z * [new tag] trunk/ef97bd47131423e0819b293dc227b62d0c376023 -> trunk/ef97bd47131423e0819b293dc227b62d0c376023 2025-07-17T07:01:09.5460328Z * [new tag] trunk/efbf07e7ea46c33c936cac882eb1c8b782d1d070 -> trunk/efbf07e7ea46c33c936cac882eb1c8b782d1d070 2025-07-17T07:01:09.5461288Z * [new tag] trunk/effe376db07c7071fa4d704dd0787a394a5eda50 -> trunk/effe376db07c7071fa4d704dd0787a394a5eda50 2025-07-17T07:01:09.5462184Z * [new tag] trunk/f04fd4dc4eaf16557f9212240bdaa8377d51bad1 -> trunk/f04fd4dc4eaf16557f9212240bdaa8377d51bad1 2025-07-17T07:01:09.5463104Z * [new tag] trunk/f096820d0f845f36529fe774cf761d5fc4ad02a8 -> trunk/f096820d0f845f36529fe774cf761d5fc4ad02a8 2025-07-17T07:01:09.5464067Z * [new tag] trunk/f0b388665efd20c1ec35fc48afb115a0f15116ce -> trunk/f0b388665efd20c1ec35fc48afb115a0f15116ce 2025-07-17T07:01:09.5465062Z * [new tag] trunk/f0bee87eea03f6ded538590e2a073cc62ecd2818 -> trunk/f0bee87eea03f6ded538590e2a073cc62ecd2818 2025-07-17T07:01:09.5466180Z * [new tag] trunk/f1331f3f1b43d1848341a0f0da66a13cb05570d0 -> trunk/f1331f3f1b43d1848341a0f0da66a13cb05570d0 2025-07-17T07:01:09.5467092Z * [new tag] trunk/f140fac8dcfa6ec20d594bc4637417a83bc90036 -> trunk/f140fac8dcfa6ec20d594bc4637417a83bc90036 2025-07-17T07:01:09.5468058Z * [new tag] trunk/f151b201236f959e3874b73dde9bfae5e10dae78 -> trunk/f151b201236f959e3874b73dde9bfae5e10dae78 2025-07-17T07:01:09.5468965Z * [new tag] trunk/f154f9b3040369a7979d5de7acb6fe21433eda83 -> trunk/f154f9b3040369a7979d5de7acb6fe21433eda83 2025-07-17T07:01:09.5470673Z * [new tag] trunk/f16053f0c9a09fa337fbf85aaf64f88712b8dcdb -> trunk/f16053f0c9a09fa337fbf85aaf64f88712b8dcdb 2025-07-17T07:01:09.5471518Z * [new tag] trunk/f179b7198522e6d93bd103efba1a1ebd5a2cf891 -> trunk/f179b7198522e6d93bd103efba1a1ebd5a2cf891 2025-07-17T07:01:09.5472859Z * [new tag] trunk/f17f6581252ff07e75f33fdce0b4248acdb5da0b -> trunk/f17f6581252ff07e75f33fdce0b4248acdb5da0b 2025-07-17T07:01:09.5473757Z * [new tag] trunk/f1f49e56b079bfc73b1b2fb061d150ec787ee716 -> trunk/f1f49e56b079bfc73b1b2fb061d150ec787ee716 2025-07-17T07:01:09.5474738Z * [new tag] trunk/f2b44424a1f3481ddc066e8dd62c0cafa1298e92 -> trunk/f2b44424a1f3481ddc066e8dd62c0cafa1298e92 2025-07-17T07:01:09.5475689Z * [new tag] trunk/f2d70898c6fad6c6e867d9bf60eced6aacfa9782 -> trunk/f2d70898c6fad6c6e867d9bf60eced6aacfa9782 2025-07-17T07:01:09.5476571Z * [new tag] trunk/f2e712ca14dbbb8435427fd536b0dd63994a9265 -> trunk/f2e712ca14dbbb8435427fd536b0dd63994a9265 2025-07-17T07:01:09.5477544Z * [new tag] trunk/f2ecf6145fde55baa8a91e27b6b3489172f0e639 -> trunk/f2ecf6145fde55baa8a91e27b6b3489172f0e639 2025-07-17T07:01:09.5478496Z * [new tag] trunk/f34335bf3373301ba3af3ff8268cd0cd1715bd2e -> trunk/f34335bf3373301ba3af3ff8268cd0cd1715bd2e 2025-07-17T07:01:09.5479457Z * [new tag] trunk/f34ab1628b6798cc62f55260dfad872f5df8fd94 -> trunk/f34ab1628b6798cc62f55260dfad872f5df8fd94 2025-07-17T07:01:09.5480556Z * [new tag] trunk/f3e6c8e834a49f738e329b802b4b10912e33915f -> trunk/f3e6c8e834a49f738e329b802b4b10912e33915f 2025-07-17T07:01:09.5481413Z * [new tag] trunk/f3ec16c26a24bcbdcb96c692e321be1a4464067c -> trunk/f3ec16c26a24bcbdcb96c692e321be1a4464067c 2025-07-17T07:01:09.5482368Z * [new tag] trunk/f402eed4d9515dee5bb9b11a2b157de57a5988c1 -> trunk/f402eed4d9515dee5bb9b11a2b157de57a5988c1 2025-07-17T07:01:09.5483242Z * [new tag] trunk/f40efde2a474ffd77c021686da2f14864d6aeb6d -> trunk/f40efde2a474ffd77c021686da2f14864d6aeb6d 2025-07-17T07:01:09.5484389Z * [new tag] trunk/f41d017aa6ca1bd121cee6e428875b7fd31a7ad0 -> trunk/f41d017aa6ca1bd121cee6e428875b7fd31a7ad0 2025-07-17T07:01:09.5485335Z * [new tag] trunk/f4376cac54978b9d7c859c1e3495a57d72ab9601 -> trunk/f4376cac54978b9d7c859c1e3495a57d72ab9601 2025-07-17T07:01:09.5486419Z * [new tag] trunk/f4406689b8805ed23dfef34c6320bb99ea6d3767 -> trunk/f4406689b8805ed23dfef34c6320bb99ea6d3767 2025-07-17T07:01:09.5487389Z * [new tag] trunk/f44a9eee4778d2a2aafe3a0beeea7a37ab8d380e -> trunk/f44a9eee4778d2a2aafe3a0beeea7a37ab8d380e 2025-07-17T07:01:09.5488585Z * [new tag] trunk/f45f483884ef524f2d8260dcf2b2ba2c203eab2f -> trunk/f45f483884ef524f2d8260dcf2b2ba2c203eab2f 2025-07-17T07:01:09.5489525Z * [new tag] trunk/f45f6e86b9ef3d9c94b87c2240dbe9a07bb9fd3d -> trunk/f45f6e86b9ef3d9c94b87c2240dbe9a07bb9fd3d 2025-07-17T07:01:09.5490378Z * [new tag] trunk/f48a1576606186cf2104c82be367b617912322de -> trunk/f48a1576606186cf2104c82be367b617912322de 2025-07-17T07:01:09.5491325Z * [new tag] trunk/f4d60a68dd2fb9fda92af83df016f4cfe3af00ba -> trunk/f4d60a68dd2fb9fda92af83df016f4cfe3af00ba 2025-07-17T07:01:09.5492244Z * [new tag] trunk/f56bfb3030acff03e21d568089f3af9e09ec7cb2 -> trunk/f56bfb3030acff03e21d568089f3af9e09ec7cb2 2025-07-17T07:01:09.5493219Z * [new tag] trunk/f58a680d09e13658a52c6ba05c63c15759846bcc -> trunk/f58a680d09e13658a52c6ba05c63c15759846bcc 2025-07-17T07:01:09.5494232Z * [new tag] trunk/f59c76b5494f83abbb2ca169e13201439396c1aa -> trunk/f59c76b5494f83abbb2ca169e13201439396c1aa 2025-07-17T07:01:09.5495130Z * [new tag] trunk/f5bbaa22536437e9f689db8ee7a5ca472fdf4bd0 -> trunk/f5bbaa22536437e9f689db8ee7a5ca472fdf4bd0 2025-07-17T07:01:09.5496065Z * [new tag] trunk/f5e1b24945cf7852a1425923ca543e1f83be14b1 -> trunk/f5e1b24945cf7852a1425923ca543e1f83be14b1 2025-07-17T07:01:09.5496884Z * [new tag] trunk/f5e6e52f2504d0d2c553fd292c89d999b2033616 -> trunk/f5e6e52f2504d0d2c553fd292c89d999b2033616 2025-07-17T07:01:09.5497788Z * [new tag] trunk/f5eb42e4c0405141134e9c52919ebb36ec77ca5f -> trunk/f5eb42e4c0405141134e9c52919ebb36ec77ca5f 2025-07-17T07:01:09.5498674Z * [new tag] trunk/f5f4beaf562911b5cf1a9e8b9eae5e5946681f3c -> trunk/f5f4beaf562911b5cf1a9e8b9eae5e5946681f3c 2025-07-17T07:01:09.5499483Z * [new tag] trunk/f6d138807f138868de0397936e2bee482c1fb987 -> trunk/f6d138807f138868de0397936e2bee482c1fb987 2025-07-17T07:01:09.5500354Z * [new tag] trunk/f6e18bc1054624bb148632a85c10371d6cc62492 -> trunk/f6e18bc1054624bb148632a85c10371d6cc62492 2025-07-17T07:01:09.5501281Z * [new tag] trunk/f70c80105ebc2a118af848c80a18d6efff820f72 -> trunk/f70c80105ebc2a118af848c80a18d6efff820f72 2025-07-17T07:01:09.5502164Z * [new tag] trunk/f7127b9b940a98596599acda1f89fc5153635a5d -> trunk/f7127b9b940a98596599acda1f89fc5153635a5d 2025-07-17T07:01:09.5503326Z * [new tag] trunk/f7130c097efa826313df44f0dcfa7d4d2e4253ec -> trunk/f7130c097efa826313df44f0dcfa7d4d2e4253ec 2025-07-17T07:01:09.5504018Z * [new tag] trunk/f742b32a2ff6326f67512d2b426cdc2da8413a75 -> trunk/f742b32a2ff6326f67512d2b426cdc2da8413a75 2025-07-17T07:01:09.5504803Z * [new tag] trunk/f79689bd3d145e76746e4cf81e99c40df8272a72 -> trunk/f79689bd3d145e76746e4cf81e99c40df8272a72 2025-07-17T07:01:09.5505768Z * [new tag] trunk/f7a5ad6c2987ee5a83aa5d868cee3b8067d3de94 -> trunk/f7a5ad6c2987ee5a83aa5d868cee3b8067d3de94 2025-07-17T07:01:09.5506723Z * [new tag] trunk/f80a61adf57badf999387efe47b8b2ff3388bd96 -> trunk/f80a61adf57badf999387efe47b8b2ff3388bd96 2025-07-17T07:01:09.5507626Z * [new tag] trunk/f810480dbefabbff6cf0852c9f610f84dd440b8d -> trunk/f810480dbefabbff6cf0852c9f610f84dd440b8d 2025-07-17T07:01:09.5508588Z * [new tag] trunk/f810e98143b7b1fe3436d5315101b22aa8438775 -> trunk/f810e98143b7b1fe3436d5315101b22aa8438775 2025-07-17T07:01:09.5509524Z * [new tag] trunk/f8293116f55a9ad399e4938f0fe3e34c6faa47c4 -> trunk/f8293116f55a9ad399e4938f0fe3e34c6faa47c4 2025-07-17T07:01:09.5510706Z * [new tag] trunk/f85954e043a5b6affb589012e8cc5eff8fdb5358 -> trunk/f85954e043a5b6affb589012e8cc5eff8fdb5358 2025-07-17T07:01:09.5511553Z * [new tag] trunk/f860992db5601a78f73eefc0a56af1d7158d6953 -> trunk/f860992db5601a78f73eefc0a56af1d7158d6953 2025-07-17T07:01:09.5512432Z * [new tag] trunk/f87d1179391d66854e3c6ca20717803cfa22f878 -> trunk/f87d1179391d66854e3c6ca20717803cfa22f878 2025-07-17T07:01:09.5513416Z * [new tag] trunk/f88d7a7a34d5a54d58f0a7edc01ff69f46221b6c -> trunk/f88d7a7a34d5a54d58f0a7edc01ff69f46221b6c 2025-07-17T07:01:09.5514369Z * [new tag] trunk/f8baec8984ed90b526fdc03eec19d8039e7d373b -> trunk/f8baec8984ed90b526fdc03eec19d8039e7d373b 2025-07-17T07:01:09.5515270Z * [new tag] trunk/f8c0a4bd28087b02958b92d7b4f41ebc607292b7 -> trunk/f8c0a4bd28087b02958b92d7b4f41ebc607292b7 2025-07-17T07:01:09.5516230Z * [new tag] trunk/f8cc4c0af802269fbe16a418386a94b3b6547c74 -> trunk/f8cc4c0af802269fbe16a418386a94b3b6547c74 2025-07-17T07:01:09.5517165Z * [new tag] trunk/f97f03c7efcf2b7a45384b9094eb6be4cb419546 -> trunk/f97f03c7efcf2b7a45384b9094eb6be4cb419546 2025-07-17T07:01:09.5518357Z * [new tag] trunk/fa0ea57f5e083daab1eb9cda39ab53a5159b077d -> trunk/fa0ea57f5e083daab1eb9cda39ab53a5159b077d 2025-07-17T07:01:09.5519105Z * [new tag] trunk/fa1c20ae9285f7994a73d2d06025065f96b67a57 -> trunk/fa1c20ae9285f7994a73d2d06025065f96b67a57 2025-07-17T07:01:09.5520043Z * [new tag] trunk/fa3c38c7ae17b8d8fccd0958831f9f1ced9e46b3 -> trunk/fa3c38c7ae17b8d8fccd0958831f9f1ced9e46b3 2025-07-17T07:01:09.5520941Z * [new tag] trunk/fa4f07b5b80bdcf99a1c7452de41939d2ab5886f -> trunk/fa4f07b5b80bdcf99a1c7452de41939d2ab5886f 2025-07-17T07:01:09.5521822Z * [new tag] trunk/fa705f791249c5eee912096f1d7ac7b2d5b60e8c -> trunk/fa705f791249c5eee912096f1d7ac7b2d5b60e8c 2025-07-17T07:01:09.5522739Z * [new tag] trunk/fab53dfdf1d89cecd5e82b12cced9b6dd217e87c -> trunk/fab53dfdf1d89cecd5e82b12cced9b6dd217e87c 2025-07-17T07:01:09.5523599Z * [new tag] trunk/fab85fc5f995ef79e67dc4b083f8cfabe7a90798 -> trunk/fab85fc5f995ef79e67dc4b083f8cfabe7a90798 2025-07-17T07:01:09.5524540Z * [new tag] trunk/fac0cc16efd342637a3d1953caf2ecfa8a89947c -> trunk/fac0cc16efd342637a3d1953caf2ecfa8a89947c 2025-07-17T07:01:09.5525590Z * [new tag] trunk/fadc936fad0793e931ed2eb89577e1d10d212f71 -> trunk/fadc936fad0793e931ed2eb89577e1d10d212f71 2025-07-17T07:01:09.5526455Z * [new tag] trunk/fb45649df7267e97efffec8305cddcb23e97d53f -> trunk/fb45649df7267e97efffec8305cddcb23e97d53f 2025-07-17T07:01:09.5527400Z * [new tag] trunk/fb462cec8d8674ad547c55dbe90710bde1dc2019 -> trunk/fb462cec8d8674ad547c55dbe90710bde1dc2019 2025-07-17T07:01:09.5528508Z * [new tag] trunk/fb731fe371cb1b5bf95de84b19c213590526acb2 -> trunk/fb731fe371cb1b5bf95de84b19c213590526acb2 2025-07-17T07:01:09.5529408Z * [new tag] trunk/fb75dea2c1b93c78dccf08d5fd5e20b362ecd405 -> trunk/fb75dea2c1b93c78dccf08d5fd5e20b362ecd405 2025-07-17T07:01:09.5530533Z * [new tag] trunk/fb9a5d248f36ddce041025c8fc5be0d8bee454b0 -> trunk/fb9a5d248f36ddce041025c8fc5be0d8bee454b0 2025-07-17T07:01:09.5531427Z * [new tag] trunk/fbbab794ef6befbe7ffab3648e9b1f2042942fed -> trunk/fbbab794ef6befbe7ffab3648e9b1f2042942fed 2025-07-17T07:01:09.5532317Z * [new tag] trunk/fbd88ae2b5f444cb4b419c415258caeaef4b7325 -> trunk/fbd88ae2b5f444cb4b419c415258caeaef4b7325 2025-07-17T07:01:09.5533718Z * [new tag] trunk/fc0376e8b162d8fcf4375ae30566139eae7d48ed -> trunk/fc0376e8b162d8fcf4375ae30566139eae7d48ed 2025-07-17T07:01:09.5534611Z * [new tag] trunk/fc10d4b1d649f1460b587f3ab45ad4403d84518c -> trunk/fc10d4b1d649f1460b587f3ab45ad4403d84518c 2025-07-17T07:01:09.5536185Z * [new tag] trunk/fc177801afcbf12543b5e193e736b155f79d4ad3 -> trunk/fc177801afcbf12543b5e193e736b155f79d4ad3 2025-07-17T07:01:09.5536968Z * [new tag] trunk/fc5ae1229341ca2841a977197c644733c6a5c789 -> trunk/fc5ae1229341ca2841a977197c644733c6a5c789 2025-07-17T07:01:09.5537793Z * [new tag] trunk/fc772692622e89335dc28638c512bb33dbed1729 -> trunk/fc772692622e89335dc28638c512bb33dbed1729 2025-07-17T07:01:09.5539074Z * [new tag] trunk/fca7013f85d4e7ac07bdd461f490aa159feac6a0 -> trunk/fca7013f85d4e7ac07bdd461f490aa159feac6a0 2025-07-17T07:01:09.5539994Z * [new tag] trunk/fcbf7c749a839cc817927ceba8ea2887cc28dbf5 -> trunk/fcbf7c749a839cc817927ceba8ea2887cc28dbf5 2025-07-17T07:01:09.5540819Z * [new tag] trunk/fcc682be4bda58894a15fee1d9041c6043fea66f -> trunk/fcc682be4bda58894a15fee1d9041c6043fea66f 2025-07-17T07:01:09.5541687Z * [new tag] trunk/fd4bb29410c035b31ca55262c3012cadb1194aae -> trunk/fd4bb29410c035b31ca55262c3012cadb1194aae 2025-07-17T07:01:09.5542683Z * [new tag] trunk/fd4f704905f95b46c4c8fb4108461ff56ce750c5 -> trunk/fd4f704905f95b46c4c8fb4108461ff56ce750c5 2025-07-17T07:01:09.5543613Z * [new tag] trunk/fd8ea3c8a35e5b4aea3ebd712f2c7ee28c5a3655 -> trunk/fd8ea3c8a35e5b4aea3ebd712f2c7ee28c5a3655 2025-07-17T07:01:09.5544552Z * [new tag] trunk/fdc5b42a8fa2b15526c81f2c83f614e086056320 -> trunk/fdc5b42a8fa2b15526c81f2c83f614e086056320 2025-07-17T07:01:09.5545386Z * [new tag] trunk/fdf5d97fa8393f56aea2779877efd8a264ad5811 -> trunk/fdf5d97fa8393f56aea2779877efd8a264ad5811 2025-07-17T07:01:09.5546662Z * [new tag] trunk/fe1f1a38dff7c59ec0ec5b05fef058629845d061 -> trunk/fe1f1a38dff7c59ec0ec5b05fef058629845d061 2025-07-17T07:01:09.5547496Z * [new tag] trunk/fec571cfd458c4644a2f483dbf9f5480feca7939 -> trunk/fec571cfd458c4644a2f483dbf9f5480feca7939 2025-07-17T07:01:09.5548380Z * [new tag] trunk/fec8af8b98f5e17740ff947e9f8a1c447a497413 -> trunk/fec8af8b98f5e17740ff947e9f8a1c447a497413 2025-07-17T07:01:09.5549289Z * [new tag] trunk/fedbd1a48e1e474cf9da5637aae89b5bc4c20626 -> trunk/fedbd1a48e1e474cf9da5637aae89b5bc4c20626 2025-07-17T07:01:09.5550140Z * [new tag] trunk/fee2377f9ea62223f69ea9904c5e25ccb2af5961 -> trunk/fee2377f9ea62223f69ea9904c5e25ccb2af5961 2025-07-17T07:01:09.5550964Z * [new tag] trunk/feea575082439a0496dd404a4925b7d551039065 -> trunk/feea575082439a0496dd404a4925b7d551039065 2025-07-17T07:01:09.5552412Z * [new tag] trunk/ff611d971fe5362a71c15109cf020d30e6c4b2b9 -> trunk/ff611d971fe5362a71c15109cf020d30e6c4b2b9 2025-07-17T07:01:09.5553001Z * [new tag] trunk/ff7dd1776f9cb8448336338b19b9b53073f2fbda -> trunk/ff7dd1776f9cb8448336338b19b9b53073f2fbda 2025-07-17T07:01:09.5553948Z * [new tag] trunk/ff8b53c056e6556187690a37c944c92feb964d2d -> trunk/ff8b53c056e6556187690a37c944c92feb964d2d 2025-07-17T07:01:09.5565526Z * [new tag] trunk/ffac0de07e0173a073c92c157f43c515009c0de1 -> trunk/ffac0de07e0173a073c92c157f43c515009c0de1 2025-07-17T07:01:09.5566135Z * [new tag] trunk/ffaed8c569406839335bf46dafc4c3e8871e4b8a -> trunk/ffaed8c569406839335bf46dafc4c3e8871e4b8a 2025-07-17T07:01:09.5566562Z * [new tag] trunk/ffc6cbfaf78ca219092ce64dcf113377ae698300 -> trunk/ffc6cbfaf78ca219092ce64dcf113377ae698300 2025-07-17T07:01:09.5566720Z * [new tag] v0.1.1 -> v0.1.1 2025-07-17T07:01:09.5566861Z * [new tag] v0.1.10 -> v0.1.10 2025-07-17T07:01:09.5566999Z * [new tag] v0.1.11 -> v0.1.11 2025-07-17T07:01:09.5567149Z * [new tag] v0.1.12 -> v0.1.12 2025-07-17T07:01:09.5567399Z * [new tag] v0.1.2 -> v0.1.2 2025-07-17T07:01:09.5567533Z * [new tag] v0.1.3 -> v0.1.3 2025-07-17T07:01:09.5567679Z * [new tag] v0.1.4 -> v0.1.4 2025-07-17T07:01:09.5567818Z * [new tag] v0.1.5 -> v0.1.5 2025-07-17T07:01:09.5567963Z * [new tag] v0.1.6 -> v0.1.6 2025-07-17T07:01:09.5568094Z * [new tag] v0.1.7 -> v0.1.7 2025-07-17T07:01:09.5568232Z * [new tag] v0.1.8 -> v0.1.8 2025-07-17T07:01:09.5568377Z * [new tag] v0.1.9 -> v0.1.9 2025-07-17T07:01:09.5568509Z * [new tag] v0.2.0 -> v0.2.0 2025-07-17T07:01:09.5569031Z * [new tag] v0.3.0 -> v0.3.0 2025-07-17T07:01:09.5570207Z * [new tag] v0.3.1 -> v0.3.1 2025-07-17T07:01:09.5574684Z * [new tag] v0.4.0 -> v0.4.0 2025-07-17T07:01:09.5575659Z * [new tag] v0.4.1 -> v0.4.1 2025-07-17T07:01:09.5576549Z * [new tag] v1.0.0 -> v1.0.0 2025-07-17T07:01:09.5577391Z * [new tag] v1.0.0a0 -> v1.0.0a0 2025-07-17T07:01:09.5578199Z * [new tag] v1.0.1 -> v1.0.1 2025-07-17T07:01:09.5579091Z * [new tag] v1.0rc0 -> v1.0rc0 2025-07-17T07:01:09.5580005Z * [new tag] v1.0rc1 -> v1.0rc1 2025-07-17T07:01:09.5580630Z * [new tag] v1.1.0 -> v1.1.0 2025-07-17T07:01:09.5581746Z * [new tag] v1.1.0a0 -> v1.1.0a0 2025-07-17T07:01:09.5582858Z * [new tag] v1.10.0 -> v1.10.0 2025-07-17T07:01:09.5583590Z * [new tag] v1.10.0-rc1 -> v1.10.0-rc1 2025-07-17T07:01:09.5584409Z * [new tag] v1.10.0-rc2 -> v1.10.0-rc2 2025-07-17T07:01:09.5585089Z * [new tag] v1.10.0-rc3 -> v1.10.0-rc3 2025-07-17T07:01:09.5586195Z * [new tag] v1.10.1 -> v1.10.1 2025-07-17T07:01:09.5586672Z * [new tag] v1.10.1-rc1 -> v1.10.1-rc1 2025-07-17T07:01:09.5587285Z * [new tag] v1.10.2 -> v1.10.2 2025-07-17T07:01:09.5588015Z * [new tag] v1.10.2-rc1 -> v1.10.2-rc1 2025-07-17T07:01:09.5588982Z * [new tag] v1.11.0 -> v1.11.0 2025-07-17T07:01:09.5589801Z * [new tag] v1.11.0-rc1 -> v1.11.0-rc1 2025-07-17T07:01:09.5590796Z * [new tag] v1.11.0-rc2 -> v1.11.0-rc2 2025-07-17T07:01:09.5591763Z * [new tag] v1.11.0-rc3 -> v1.11.0-rc3 2025-07-17T07:01:09.5592596Z * [new tag] v1.11.0-rc4 -> v1.11.0-rc4 2025-07-17T07:01:09.5593520Z * [new tag] v1.11.0-rc5 -> v1.11.0-rc5 2025-07-17T07:01:09.5594086Z * [new tag] v1.11.0-rc6 -> v1.11.0-rc6 2025-07-17T07:01:09.5594785Z * [new tag] v1.11.0-rc7 -> v1.11.0-rc7 2025-07-17T07:01:09.5595763Z * [new tag] v1.12.0 -> v1.12.0 2025-07-17T07:01:09.5596637Z * [new tag] v1.12.0-rc1 -> v1.12.0-rc1 2025-07-17T07:01:09.5597506Z * [new tag] v1.12.0-rc2 -> v1.12.0-rc2 2025-07-17T07:01:09.5598374Z * [new tag] v1.12.0-rc3 -> v1.12.0-rc3 2025-07-17T07:01:09.5599300Z * [new tag] v1.12.0-rc4 -> v1.12.0-rc4 2025-07-17T07:01:09.5600180Z * [new tag] v1.12.0-rc5 -> v1.12.0-rc5 2025-07-17T07:01:09.5601121Z * [new tag] v1.12.0-rc6 -> v1.12.0-rc6 2025-07-17T07:01:09.5601704Z * [new tag] v1.12.0-rc7 -> v1.12.0-rc7 2025-07-17T07:01:09.5602419Z * [new tag] v1.12.0-rc8 -> v1.12.0-rc8 2025-07-17T07:01:09.5603146Z * [new tag] v1.12.1 -> v1.12.1 2025-07-17T07:01:09.5604159Z * [new tag] v1.12.1-rc1 -> v1.12.1-rc1 2025-07-17T07:01:09.5604978Z * [new tag] v1.12.1-rc2 -> v1.12.1-rc2 2025-07-17T07:01:09.5606233Z * [new tag] v1.12.1-rc3 -> v1.12.1-rc3 2025-07-17T07:01:09.5607022Z * [new tag] v1.12.1-rc4 -> v1.12.1-rc4 2025-07-17T07:01:09.5607554Z * [new tag] v1.12.1-rc5 -> v1.12.1-rc5 2025-07-17T07:01:09.5608674Z * [new tag] v1.13.0 -> v1.13.0 2025-07-17T07:01:09.5609496Z * [new tag] v1.13.0-rc1 -> v1.13.0-rc1 2025-07-17T07:01:09.5610284Z * [new tag] v1.13.0-rc2 -> v1.13.0-rc2 2025-07-17T07:01:09.5611231Z * [new tag] v1.13.0-rc3 -> v1.13.0-rc3 2025-07-17T07:01:09.5612278Z * [new tag] v1.13.0-rc4 -> v1.13.0-rc4 2025-07-17T07:01:09.5612957Z * [new tag] v1.13.0-rc5 -> v1.13.0-rc5 2025-07-17T07:01:09.5613585Z * [new tag] v1.13.0-rc6 -> v1.13.0-rc6 2025-07-17T07:01:09.5614530Z * [new tag] v1.13.1 -> v1.13.1 2025-07-17T07:01:09.5615146Z * [new tag] v1.13.1-rc1 -> v1.13.1-rc1 2025-07-17T07:01:09.5616021Z * [new tag] v1.2.0 -> v1.2.0 2025-07-17T07:01:09.5616873Z * [new tag] v1.2.0a0 -> v1.2.0a0 2025-07-17T07:01:09.5617712Z * [new tag] v1.3.0 -> v1.3.0 2025-07-17T07:01:09.5618548Z * [new tag] v1.3.0a0 -> v1.3.0a0 2025-07-17T07:01:09.5619155Z * [new tag] v1.3.1 -> v1.3.1 2025-07-17T07:01:09.5620342Z * [new tag] v1.4.0 -> v1.4.0 2025-07-17T07:01:09.5621222Z * [new tag] v1.4.0a0 -> v1.4.0a0 2025-07-17T07:01:09.5621988Z * [new tag] v1.4.1 -> v1.4.1 2025-07-17T07:01:09.5623065Z * [new tag] v1.5.0 -> v1.5.0 2025-07-17T07:01:09.5623742Z * [new tag] v1.5.0-rc1 -> v1.5.0-rc1 2025-07-17T07:01:09.5624709Z * [new tag] v1.5.0-rc2 -> v1.5.0-rc2 2025-07-17T07:01:09.5625729Z * [new tag] v1.5.0-rc3 -> v1.5.0-rc3 2025-07-17T07:01:09.5626401Z * [new tag] v1.5.0-rc4 -> v1.5.0-rc4 2025-07-17T07:01:09.5627531Z * [new tag] v1.5.0-rc5 -> v1.5.0-rc5 2025-07-17T07:01:09.5628491Z * [new tag] v1.5.1 -> v1.5.1 2025-07-17T07:01:09.5629102Z * [new tag] v1.5.1-rc1 -> v1.5.1-rc1 2025-07-17T07:01:09.5629727Z * [new tag] v1.6.0 -> v1.6.0 2025-07-17T07:01:09.5630664Z * [new tag] v1.6.0-rc1 -> v1.6.0-rc1 2025-07-17T07:01:09.5631568Z * [new tag] v1.6.0-rc2 -> v1.6.0-rc2 2025-07-17T07:01:09.5632532Z * [new tag] v1.6.0-rc3 -> v1.6.0-rc3 2025-07-17T07:01:09.5633453Z * [new tag] v1.6.0-rc4 -> v1.6.0-rc4 2025-07-17T07:01:09.5634290Z * [new tag] v1.6.0-rc5 -> v1.6.0-rc5 2025-07-17T07:01:09.5635173Z * [new tag] v1.6.0-rc6 -> v1.6.0-rc6 2025-07-17T07:01:09.5635823Z * [new tag] v1.6.0-rc7 -> v1.6.0-rc7 2025-07-17T07:01:09.5636773Z * [new tag] v1.7.0 -> v1.7.0 2025-07-17T07:01:09.5637683Z * [new tag] v1.7.0-rc1 -> v1.7.0-rc1 2025-07-17T07:01:09.5638622Z * [new tag] v1.7.0-rc2 -> v1.7.0-rc2 2025-07-17T07:01:09.5639520Z * [new tag] v1.7.0-rc3 -> v1.7.0-rc3 2025-07-17T07:01:09.5640252Z * [new tag] v1.7.0-rc4 -> v1.7.0-rc4 2025-07-17T07:01:09.5641060Z * [new tag] v1.7.1 -> v1.7.1 2025-07-17T07:01:09.5642158Z * [new tag] v1.7.1-rc1 -> v1.7.1-rc1 2025-07-17T07:01:09.5642976Z * [new tag] v1.7.1-rc2 -> v1.7.1-rc2 2025-07-17T07:01:09.5643748Z * [new tag] v1.7.1-rc3 -> v1.7.1-rc3 2025-07-17T07:01:09.5644586Z * [new tag] v1.8.0 -> v1.8.0 2025-07-17T07:01:09.5645380Z * [new tag] v1.8.0-rc1 -> v1.8.0-rc1 2025-07-17T07:01:09.5646498Z * [new tag] v1.8.0-rc2 -> v1.8.0-rc2 2025-07-17T07:01:09.5647370Z * [new tag] v1.8.0-rc3 -> v1.8.0-rc3 2025-07-17T07:01:09.5648069Z * [new tag] v1.8.0-rc4 -> v1.8.0-rc4 2025-07-17T07:01:09.5648835Z * [new tag] v1.8.0-rc5 -> v1.8.0-rc5 2025-07-17T07:01:09.5649647Z * [new tag] v1.8.1 -> v1.8.1 2025-07-17T07:01:09.5650500Z * [new tag] v1.8.1-rc1 -> v1.8.1-rc1 2025-07-17T07:01:09.5651120Z * [new tag] v1.8.1-rc2 -> v1.8.1-rc2 2025-07-17T07:01:09.5651807Z * [new tag] v1.8.1-rc3 -> v1.8.1-rc3 2025-07-17T07:01:09.5653322Z * [new tag] v1.8.2 -> v1.8.2 2025-07-17T07:01:09.5654023Z * [new tag] v1.8.2-rc1 -> v1.8.2-rc1 2025-07-17T07:01:09.5654707Z * [new tag] v1.9.0 -> v1.9.0 2025-07-17T07:01:09.5655780Z * [new tag] v1.9.0-rc1 -> v1.9.0-rc1 2025-07-17T07:01:09.5656644Z * [new tag] v1.9.0-rc2 -> v1.9.0-rc2 2025-07-17T07:01:09.5657612Z * [new tag] v1.9.0-rc3 -> v1.9.0-rc3 2025-07-17T07:01:09.5658229Z * [new tag] v1.9.0-rc4 -> v1.9.0-rc4 2025-07-17T07:01:09.5659057Z * [new tag] v1.9.1 -> v1.9.1 2025-07-17T07:01:09.5660122Z * [new tag] v1.9.1-rc1 -> v1.9.1-rc1 2025-07-17T07:01:09.5660731Z * [new tag] v1.9.1-rc2 -> v1.9.1-rc2 2025-07-17T07:01:09.5661698Z * [new tag] v2.0.0 -> v2.0.0 2025-07-17T07:01:09.5662567Z * [new tag] v2.0.0-rc1 -> v2.0.0-rc1 2025-07-17T07:01:09.5663530Z * [new tag] v2.0.0-rc2 -> v2.0.0-rc2 2025-07-17T07:01:09.5664467Z * [new tag] v2.0.0-rc3 -> v2.0.0-rc3 2025-07-17T07:01:09.5665335Z * [new tag] v2.0.0-rc4 -> v2.0.0-rc4 2025-07-17T07:01:09.5666218Z * [new tag] v2.0.0-rc5 -> v2.0.0-rc5 2025-07-17T07:01:09.5666822Z * [new tag] v2.0.0-rc6 -> v2.0.0-rc6 2025-07-17T07:01:09.5667841Z * [new tag] v2.0.1 -> v2.0.1 2025-07-17T07:01:09.5668739Z * [new tag] v2.0.1-rc1 -> v2.0.1-rc1 2025-07-17T07:01:09.5669393Z * [new tag] v2.0.1-rc2 -> v2.0.1-rc2 2025-07-17T07:01:09.5670375Z * [new tag] v2.0.1-rc3 -> v2.0.1-rc3 2025-07-17T07:01:09.5671046Z * [new tag] v2.0.1-rc4 -> v2.0.1-rc4 2025-07-17T07:01:09.5672516Z * [new tag] v2.1.0 -> v2.1.0 2025-07-17T07:01:09.5673386Z * [new tag] v2.1.0-rc1 -> v2.1.0-rc1 2025-07-17T07:01:09.5674288Z * [new tag] v2.1.0-rc2 -> v2.1.0-rc2 2025-07-17T07:01:09.5675182Z * [new tag] v2.1.0-rc3 -> v2.1.0-rc3 2025-07-17T07:01:09.5676132Z * [new tag] v2.1.0-rc4 -> v2.1.0-rc4 2025-07-17T07:01:09.5677040Z * [new tag] v2.1.0-rc5 -> v2.1.0-rc5 2025-07-17T07:01:09.5677759Z * [new tag] v2.1.0-rc6 -> v2.1.0-rc6 2025-07-17T07:01:09.5678601Z * [new tag] v2.1.1 -> v2.1.1 2025-07-17T07:01:09.5679598Z * [new tag] v2.1.1-rc1 -> v2.1.1-rc1 2025-07-17T07:01:09.5680341Z * [new tag] v2.1.1-rc2 -> v2.1.1-rc2 2025-07-17T07:01:09.5681421Z * [new tag] v2.1.1-rc3 -> v2.1.1-rc3 2025-07-17T07:01:09.5682366Z * [new tag] v2.1.1-rc4 -> v2.1.1-rc4 2025-07-17T07:01:09.5683622Z * [new tag] v2.1.1-rc5 -> v2.1.1-rc5 2025-07-17T07:01:09.5684240Z * [new tag] v2.1.1-rc6 -> v2.1.1-rc6 2025-07-17T07:01:09.5685209Z * [new tag] v2.1.2 -> v2.1.2 2025-07-17T07:01:09.5686497Z * [new tag] v2.1.2-rc1 -> v2.1.2-rc1 2025-07-17T07:01:09.5687173Z * [new tag] v2.1.2-rc2 -> v2.1.2-rc2 2025-07-17T07:01:09.5687821Z * [new tag] v2.1.2-rc3 -> v2.1.2-rc3 2025-07-17T07:01:09.5688931Z * [new tag] v2.2.0 -> v2.2.0 2025-07-17T07:01:09.5689642Z * [new tag] v2.2.0-rc1 -> v2.2.0-rc1 2025-07-17T07:01:09.5690583Z * [new tag] v2.2.0-rc2 -> v2.2.0-rc2 2025-07-17T07:01:09.5691303Z * [new tag] v2.2.0-rc3 -> v2.2.0-rc3 2025-07-17T07:01:09.5692309Z * [new tag] v2.2.0-rc4 -> v2.2.0-rc4 2025-07-17T07:01:09.5693127Z * [new tag] v2.2.0-rc5 -> v2.2.0-rc5 2025-07-17T07:01:09.5694056Z * [new tag] v2.2.0-rc6 -> v2.2.0-rc6 2025-07-17T07:01:09.5694662Z * [new tag] v2.2.0-rc7 -> v2.2.0-rc7 2025-07-17T07:01:09.5695301Z * [new tag] v2.2.0-rc8 -> v2.2.0-rc8 2025-07-17T07:01:09.5696190Z * [new tag] v2.2.1 -> v2.2.1 2025-07-17T07:01:09.5697105Z * [new tag] v2.2.1-rc1 -> v2.2.1-rc1 2025-07-17T07:01:09.5697706Z * [new tag] v2.2.1-rc2 -> v2.2.1-rc2 2025-07-17T07:01:09.5698408Z * [new tag] v2.2.1-rc3 -> v2.2.1-rc3 2025-07-17T07:01:09.5699059Z * [new tag] v2.2.2 -> v2.2.2 2025-07-17T07:01:09.5700063Z * [new tag] v2.2.2-rc1 -> v2.2.2-rc1 2025-07-17T07:01:09.5700669Z * [new tag] v2.2.2-rc2 -> v2.2.2-rc2 2025-07-17T07:01:09.5701370Z * [new tag] v2.2.2-rc3 -> v2.2.2-rc3 2025-07-17T07:01:09.5702310Z * [new tag] v2.3.0 -> v2.3.0 2025-07-17T07:01:09.5703182Z * [new tag] v2.3.0-rc1 -> v2.3.0-rc1 2025-07-17T07:01:09.5704059Z * [new tag] v2.3.0-rc10 -> v2.3.0-rc10 2025-07-17T07:01:09.5705021Z * [new tag] v2.3.0-rc11 -> v2.3.0-rc11 2025-07-17T07:01:09.5705660Z * [new tag] v2.3.0-rc12 -> v2.3.0-rc12 2025-07-17T07:01:09.5706610Z * [new tag] v2.3.0-rc2 -> v2.3.0-rc2 2025-07-17T07:01:09.5707467Z * [new tag] v2.3.0-rc3 -> v2.3.0-rc3 2025-07-17T07:01:09.5708360Z * [new tag] v2.3.0-rc4 -> v2.3.0-rc4 2025-07-17T07:01:09.5709240Z * [new tag] v2.3.0-rc5 -> v2.3.0-rc5 2025-07-17T07:01:09.5709806Z * [new tag] v2.3.0-rc6 -> v2.3.0-rc6 2025-07-17T07:01:09.5710760Z * [new tag] v2.3.0-rc7 -> v2.3.0-rc7 2025-07-17T07:01:09.5711657Z * [new tag] v2.3.0-rc8 -> v2.3.0-rc8 2025-07-17T07:01:09.5712352Z * [new tag] v2.3.0-rc9 -> v2.3.0-rc9 2025-07-17T07:01:09.5713006Z * [new tag] v2.3.1 -> v2.3.1 2025-07-17T07:01:09.5713974Z * [new tag] v2.3.1-rc1 -> v2.3.1-rc1 2025-07-17T07:01:09.5714799Z * [new tag] v2.3.1-rc2 -> v2.3.1-rc2 2025-07-17T07:01:09.5715878Z * [new tag] v2.3.1-rc3 -> v2.3.1-rc3 2025-07-17T07:01:09.5716614Z * [new tag] v2.4.0 -> v2.4.0 2025-07-17T07:01:09.5717606Z * [new tag] v2.4.0-rc1 -> v2.4.0-rc1 2025-07-17T07:01:09.5718439Z * [new tag] v2.4.0-rc2 -> v2.4.0-rc2 2025-07-17T07:01:09.5719417Z * [new tag] v2.4.0-rc3 -> v2.4.0-rc3 2025-07-17T07:01:09.5720153Z * [new tag] v2.4.0-rc4 -> v2.4.0-rc4 2025-07-17T07:01:09.5721396Z * [new tag] v2.4.0-rc5 -> v2.4.0-rc5 2025-07-17T07:01:09.5722164Z * [new tag] v2.4.0-rc6 -> v2.4.0-rc6 2025-07-17T07:01:09.5722914Z * [new tag] v2.4.0-rc7 -> v2.4.0-rc7 2025-07-17T07:01:09.5723900Z * [new tag] v2.4.0-rc8 -> v2.4.0-rc8 2025-07-17T07:01:09.5724741Z * [new tag] v2.4.0-rc9 -> v2.4.0-rc9 2025-07-17T07:01:09.5725488Z * [new tag] v2.4.1 -> v2.4.1 2025-07-17T07:01:09.5726616Z * [new tag] v2.4.1-rc1 -> v2.4.1-rc1 2025-07-17T07:01:09.5727592Z * [new tag] v2.4.1-rc2 -> v2.4.1-rc2 2025-07-17T07:01:09.5728434Z * [new tag] v2.4.1-rc3 -> v2.4.1-rc3 2025-07-17T07:01:09.5729373Z * [new tag] v2.5.0 -> v2.5.0 2025-07-17T07:01:09.5730330Z * [new tag] v2.5.0-rc1 -> v2.5.0-rc1 2025-07-17T07:01:09.5731018Z * [new tag] v2.5.0-rc10 -> v2.5.0-rc10 2025-07-17T07:01:09.5732079Z * [new tag] v2.5.0-rc2 -> v2.5.0-rc2 2025-07-17T07:01:09.5732900Z * [new tag] v2.5.0-rc3 -> v2.5.0-rc3 2025-07-17T07:01:09.5733661Z * [new tag] v2.5.0-rc4 -> v2.5.0-rc4 2025-07-17T07:01:09.5734736Z * [new tag] v2.5.0-rc5 -> v2.5.0-rc5 2025-07-17T07:01:09.5735581Z * [new tag] v2.5.0-rc6 -> v2.5.0-rc6 2025-07-17T07:01:09.5736405Z * [new tag] v2.5.0-rc7 -> v2.5.0-rc7 2025-07-17T07:01:09.5737417Z * [new tag] v2.5.0-rc8 -> v2.5.0-rc8 2025-07-17T07:01:09.5738626Z * [new tag] v2.5.0-rc9 -> v2.5.0-rc9 2025-07-17T07:01:09.5739315Z * [new tag] v2.5.1 -> v2.5.1 2025-07-17T07:01:09.5739978Z * [new tag] v2.5.1-rc1 -> v2.5.1-rc1 2025-07-17T07:01:09.5740639Z * [new tag] v2.6.0 -> v2.6.0 2025-07-17T07:01:09.5741773Z * [new tag] v2.6.0-rc1 -> v2.6.0-rc1 2025-07-17T07:01:09.5742605Z * [new tag] v2.6.0-rc2 -> v2.6.0-rc2 2025-07-17T07:01:09.5743603Z * [new tag] v2.6.0-rc3 -> v2.6.0-rc3 2025-07-17T07:01:09.5744420Z * [new tag] v2.6.0-rc4 -> v2.6.0-rc4 2025-07-17T07:01:09.5745583Z * [new tag] v2.6.0-rc5 -> v2.6.0-rc5 2025-07-17T07:01:09.5746713Z * [new tag] v2.6.0-rc6 -> v2.6.0-rc6 2025-07-17T07:01:09.5747751Z * [new tag] v2.6.0-rc7 -> v2.6.0-rc7 2025-07-17T07:01:09.5748599Z * [new tag] v2.6.0-rc8 -> v2.6.0-rc8 2025-07-17T07:01:09.5749421Z * [new tag] v2.6.0-rc9 -> v2.6.0-rc9 2025-07-17T07:01:09.5750588Z * [new tag] v2.7.0 -> v2.7.0 2025-07-17T07:01:09.5751462Z * [new tag] v2.7.0-rc1 -> v2.7.0-rc1 2025-07-17T07:01:09.5752138Z * [new tag] v2.7.0-rc10 -> v2.7.0-rc10 2025-07-17T07:01:09.5753179Z * [new tag] v2.7.0-rc2 -> v2.7.0-rc2 2025-07-17T07:01:09.5754004Z * [new tag] v2.7.0-rc3 -> v2.7.0-rc3 2025-07-17T07:01:09.5755028Z * [new tag] v2.7.0-rc4 -> v2.7.0-rc4 2025-07-17T07:01:09.5755785Z * [new tag] v2.7.0-rc5 -> v2.7.0-rc5 2025-07-17T07:01:09.5756699Z * [new tag] v2.7.0-rc6 -> v2.7.0-rc6 2025-07-17T07:01:09.5757636Z * [new tag] v2.7.0-rc7 -> v2.7.0-rc7 2025-07-17T07:01:09.5758685Z * [new tag] v2.7.0-rc8 -> v2.7.0-rc8 2025-07-17T07:01:09.5759525Z * [new tag] v2.7.0-rc9 -> v2.7.0-rc9 2025-07-17T07:01:09.5760182Z * [new tag] v2.7.1 -> v2.7.1 2025-07-17T07:01:09.5761188Z * [new tag] v2.7.1-rc1 -> v2.7.1-rc1 2025-07-17T07:01:09.5762065Z * [new tag] v2.7.1-rc2 -> v2.7.1-rc2 2025-07-17T07:01:09.5763199Z * [new tag] v2.7.1-rc3 -> v2.7.1-rc3 2025-07-17T07:01:09.5764182Z * [new tag] v2.7.1-rc4 -> v2.7.1-rc4 2025-07-17T07:01:09.5764824Z * [new tag] v2.7.1-rc5 -> v2.7.1-rc5 2025-07-17T07:01:09.5765893Z * [new tag] v2.8.0-rc1 -> v2.8.0-rc1 2025-07-17T07:01:09.5766813Z * [new tag] v2.8.0-rc2 -> v2.8.0-rc2 2025-07-17T07:01:09.5767775Z * [new tag] v2.8.0-rc3 -> v2.8.0-rc3 2025-07-17T07:01:09.5768739Z * [new tag] v2.8.0-rc4 -> v2.8.0-rc4 2025-07-17T07:01:09.5769672Z * [new tag] v2.8.0-rc5 -> v2.8.0-rc5 2025-07-17T07:01:09.5770719Z * [new tag] whc_flight_1 -> whc_flight_1 2025-07-17T07:01:09.5771321Z * [new tag] whc_flight_2 -> whc_flight_2 2025-07-17T07:01:09.5772183Z * [new tag] whc_flight_4 -> whc_flight_4 2025-07-17T07:01:09.6597118Z [command]/usr/bin/git rev-parse --verify --quiet a38f433be2e94a64b095a44ba39879d02d0c2316^{object} 2025-07-17T07:01:09.6623026Z a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:01:09.6627632Z ##[endgroup] 2025-07-17T07:01:09.6628081Z ##[group]Determining the checkout info 2025-07-17T07:01:09.6628732Z ##[endgroup] 2025-07-17T07:01:09.6633334Z [command]/usr/bin/git sparse-checkout disable 2025-07-17T07:01:09.6675358Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-07-17T07:01:09.6713462Z ##[group]Checking out the ref 2025-07-17T07:01:09.6717480Z [command]/usr/bin/git checkout --progress --force a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:01:10.6994422Z Updating files: 86% (16956/19589) 2025-07-17T07:01:10.7122309Z Updating files: 87% (17043/19589) 2025-07-17T07:01:10.7246875Z Updating files: 88% (17239/19589) 2025-07-17T07:01:10.7358103Z Updating files: 89% (17435/19589) 2025-07-17T07:01:10.7516674Z Updating files: 90% (17631/19589) 2025-07-17T07:01:10.7648335Z Updating files: 91% (17826/19589) 2025-07-17T07:01:10.7770465Z Updating files: 92% (18022/19589) 2025-07-17T07:01:10.7922242Z Updating files: 93% (18218/19589) 2025-07-17T07:01:10.8105085Z Updating files: 94% (18414/19589) 2025-07-17T07:01:10.8302665Z Updating files: 95% (18610/19589) 2025-07-17T07:01:10.8454989Z Updating files: 96% (18806/19589) 2025-07-17T07:01:10.8623789Z Updating files: 97% (19002/19589) 2025-07-17T07:01:10.8888545Z Updating files: 98% (19198/19589) 2025-07-17T07:01:10.9040332Z Updating files: 99% (19394/19589) 2025-07-17T07:01:10.9040673Z Updating files: 100% (19589/19589) 2025-07-17T07:01:10.9040987Z Updating files: 100% (19589/19589), done. 2025-07-17T07:01:10.9305768Z Note: switching to 'a38f433be2e94a64b095a44ba39879d02d0c2316'. 2025-07-17T07:01:10.9306115Z 2025-07-17T07:01:10.9306352Z You are in 'detached HEAD' state. You can look around, make experimental 2025-07-17T07:01:10.9306961Z changes and commit them, and you can discard any commits you make in this 2025-07-17T07:01:10.9307527Z state without impacting any branches by switching back to a branch. 2025-07-17T07:01:10.9307858Z 2025-07-17T07:01:10.9308080Z If you want to create a new branch to retain commits you create, you may 2025-07-17T07:01:10.9308585Z do so (now or later) by using -c with the switch command. Example: 2025-07-17T07:01:10.9308890Z 2025-07-17T07:01:10.9309028Z git switch -c 2025-07-17T07:01:10.9309237Z 2025-07-17T07:01:10.9309550Z Or undo this operation with: 2025-07-17T07:01:10.9309736Z 2025-07-17T07:01:10.9309842Z git switch - 2025-07-17T07:01:10.9309973Z 2025-07-17T07:01:10.9310215Z Turn off this advice by setting config variable advice.detachedHead to false 2025-07-17T07:01:10.9310584Z 2025-07-17T07:01:10.9310855Z HEAD is now at a38f433be2e [Docker builds] Move from Miniconda to Miniforge (#158370) 2025-07-17T07:01:10.9378944Z ##[endgroup] 2025-07-17T07:01:10.9379594Z ##[group]Setting up auth for fetching submodules 2025-07-17T07:01:10.9385517Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-07-17T07:01:10.9426969Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-07-17T07:01:10.9454609Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-07-17T07:01:10.9481531Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-07-17T07:01:10.9503847Z ##[endgroup] 2025-07-17T07:01:10.9504526Z ##[group]Fetching submodules 2025-07-17T07:01:10.9508319Z [command]/usr/bin/git submodule sync --recursive 2025-07-17T07:01:10.9820512Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-07-17T07:01:11.0169665Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni' 2025-07-17T07:01:11.0172471Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16' 2025-07-17T07:01:11.0467960Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv' 2025-07-17T07:01:11.0471170Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK' 2025-07-17T07:01:11.0475593Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX' 2025-07-17T07:01:11.0479655Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator' 2025-07-17T07:01:11.0483288Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK' 2025-07-17T07:01:11.0492569Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter' 2025-07-17T07:01:11.0496654Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark' 2025-07-17T07:01:11.0500924Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel' 2025-07-17T07:01:11.0505023Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib' 2025-07-17T07:01:11.0509303Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo' 2025-07-17T07:01:11.0513844Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend' 2025-07-17T07:01:11.0522790Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass' 2025-07-17T07:01:11.0527673Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm' 2025-07-17T07:01:11.0534032Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention' 2025-07-17T07:01:11.0538215Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers' 2025-07-17T07:01:11.0542980Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt' 2025-07-17T07:01:11.0553065Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp' 2025-07-17T07:01:11.0557649Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo' 2025-07-17T07:01:11.0564417Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest' 2025-07-17T07:01:11.0569763Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep' 2025-07-17T07:01:11.0575540Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi' 2025-07-17T07:01:11.0580945Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto' 2025-07-17T07:01:11.0591527Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai' 2025-07-17T07:01:11.0597175Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc' 2025-07-17T07:01:11.0602821Z Submodule 'third_party/nlohmann' (https://github.com/nlohmann/json.git) registered for path 'third_party/nlohmann' 2025-07-17T07:01:11.0608668Z Submodule 'third_party/onnx' (https://github.com/onnx/onnx.git) registered for path 'third_party/onnx' 2025-07-17T07:01:11.0614858Z Submodule 'third_party/opentelemetry-cpp' (https://github.com/open-telemetry/opentelemetry-cpp.git) registered for path 'third_party/opentelemetry-cpp' 2025-07-17T07:01:11.0626653Z Submodule 'third_party/pocketfft' (https://github.com/mreineck/pocketfft) registered for path 'third_party/pocketfft' 2025-07-17T07:01:11.0632813Z Submodule 'third_party/protobuf' (https://github.com/protocolbuffers/protobuf.git) registered for path 'third_party/protobuf' 2025-07-17T07:01:11.0639076Z Submodule 'third_party/NNPACK_deps/psimd' (https://github.com/Maratyszcza/psimd.git) registered for path 'third_party/psimd' 2025-07-17T07:01:11.0645503Z Submodule 'third_party/NNPACK_deps/pthreadpool' (https://github.com/Maratyszcza/pthreadpool.git) registered for path 'third_party/pthreadpool' 2025-07-17T07:01:11.0651771Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/pybind11' 2025-07-17T07:01:11.0658435Z Submodule 'third_party/python-peachpy' (https://github.com/malfet/PeachPy.git) registered for path 'third_party/python-peachpy' 2025-07-17T07:01:11.0669939Z Submodule 'third_party/sleef' (https://github.com/shibatch/sleef) registered for path 'third_party/sleef' 2025-07-17T07:01:11.0677214Z Submodule 'third_party/tensorpipe' (https://github.com/pytorch/tensorpipe.git) registered for path 'third_party/tensorpipe' 2025-07-17T07:01:11.0709469Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/android/libs/fbjni'... 2025-07-17T07:01:11.3199210Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/FP16'... 2025-07-17T07:01:11.3201024Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/FXdiv'... 2025-07-17T07:01:11.3236811Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/benchmark'... 2025-07-17T07:01:11.7147059Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/NNPACK'... 2025-07-17T07:01:11.7148958Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/NVTX'... 2025-07-17T07:01:11.7185689Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/composable_kernel'... 2025-07-17T07:01:19.3036124Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cpuinfo'... 2025-07-17T07:01:19.3037561Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cpp-httplib'... 2025-07-17T07:01:19.3039013Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention'... 2025-07-17T07:01:19.3040715Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cudnn_frontend'... 2025-07-17T07:01:19.3042271Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'... 2025-07-17T07:01:19.3043817Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/gemmlowp/gemmlowp'... 2025-07-17T07:01:19.3045207Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/gloo'... 2025-07-17T07:01:19.3046615Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cutlass'... 2025-07-17T07:01:19.3047995Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flatbuffers'... 2025-07-17T07:01:19.3049365Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ideep'... 2025-07-17T07:01:19.3050668Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ittapi'... 2025-07-17T07:01:19.3051931Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fmt'... 2025-07-17T07:01:19.3290077Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm'... 2025-07-17T07:01:20.1609228Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kleidiai'... 2025-07-17T07:01:20.1917021Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/mimalloc'... 2025-07-17T07:01:21.0879629Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/googletest'... 2025-07-17T07:01:21.0881605Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pocketfft'... 2025-07-17T07:01:21.0883990Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/aiter'... 2025-07-17T07:01:21.0885653Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/psimd'... 2025-07-17T07:01:21.0915120Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/protobuf'... 2025-07-17T07:01:49.1239079Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pthreadpool'... 2025-07-17T07:01:49.1240808Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto'... 2025-07-17T07:01:49.1242448Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/python-peachpy'... 2025-07-17T07:01:49.1244125Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe'... 2025-07-17T07:01:49.1246084Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/sleef'... 2025-07-17T07:01:49.1247637Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pybind11'... 2025-07-17T07:01:49.1249185Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/onnx'... 2025-07-17T07:01:49.1250743Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/nlohmann'... 2025-07-17T07:01:49.2240375Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/XNNPACK'... 2025-07-17T07:01:50.1528342Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp'... 2025-07-17T07:01:50.1687295Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-07-17T07:01:50.1812140Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-07-17T07:01:50.1907334Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-07-17T07:01:50.2160255Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-07-17T07:01:50.2970320Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-07-17T07:01:50.3482248Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-07-17T07:01:51.0780947Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-07-17T07:01:51.2209129Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-07-17T07:01:51.2229867Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel' 2025-07-17T07:01:51.2257767Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'... 2025-07-17T07:01:54.3734694Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-07-17T07:01:54.3972171Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-07-17T07:01:54.6795458Z Submodule path 'third_party/composable_kernel': checked out '434d19f696da62c12b5372b32cbc9ba968588d7e' 2025-07-17T07:01:54.7326436Z Submodule path 'third_party/cpp-httplib': checked out '3af7f2c16147f3fbc6e4d717032daf505dc1652c' 2025-07-17T07:01:54.8306747Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-07-17T07:01:54.8758151Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-07-17T07:01:55.5221894Z Submodule path 'third_party/cutlass': checked out 'b995f933179c22d3fe0d871c3a53d11e4681950f' 2025-07-17T07:01:55.6512485Z Submodule path 'third_party/fbgemm': checked out '157e88b750c452bef2ab4653fe9d1eeb151ce4c3' 2025-07-17T07:01:55.6533305Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit' 2025-07-17T07:01:55.6535916Z Submodule 'external/composable_kernel' (https://github.com/jwfromm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel' 2025-07-17T07:01:55.6538455Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo' 2025-07-17T07:01:55.6541258Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass' 2025-07-17T07:01:55.6544104Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest' 2025-07-17T07:01:55.6547123Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch' 2025-07-17T07:01:55.6550081Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json' 2025-07-17T07:01:55.6580416Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'... 2025-07-17T07:01:57.4416255Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/hipify_torch'... 2025-07-17T07:01:57.4473513Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/cpuinfo'... 2025-07-17T07:01:57.5417354Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/composable_kernel'... 2025-07-17T07:01:57.7975198Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'... 2025-07-17T07:01:57.8976342Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/cutlass'... 2025-07-17T07:01:58.8570203Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/json'... 2025-07-17T07:02:04.7712142Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'e5d7c0bd5d9aec44d68830187138149e6a8c4e32' 2025-07-17T07:02:04.9998481Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out '4a61bdd4bd4ed730e078aebc7c0fcf046ff29406' 2025-07-17T07:02:05.1015727Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-07-17T07:02:05.4075068Z From https://github.com/jwfromm/cutlass 2025-07-17T07:02:05.4075578Z * branch 3ed8d2ec4ba35ef5d9d8353826209b6f868f63d3 -> FETCH_HEAD 2025-07-17T07:02:05.9736811Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '3ed8d2ec4ba35ef5d9d8353826209b6f868f63d3' 2025-07-17T07:02:06.0183152Z Submodule path 'third_party/fbgemm/external/googletest': checked out 'f8d7d77c06936315286eb55f8de22cd23c188571' 2025-07-17T07:02:06.0306719Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out 'a4337c69fe0e2552a7b7b0669178926beeed828c' 2025-07-17T07:02:06.1567583Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-07-17T07:02:06.2279582Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-07-17T07:02:06.2298860Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel' 2025-07-17T07:02:06.2301094Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass' 2025-07-17T07:02:06.2329313Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'... 2025-07-17T07:02:09.4074026Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'... 2025-07-17T07:02:09.6474550Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-07-17T07:02:10.2070256Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-07-17T07:02:10.3478338Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-07-17T07:02:10.3816202Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-07-17T07:02:10.4215039Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-07-17T07:02:10.4469924Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-07-17T07:02:10.4940794Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-07-17T07:02:10.5073811Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-07-17T07:02:10.5090357Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn' 2025-07-17T07:02:10.5114747Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'... 2025-07-17T07:02:23.1907878Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-07-17T07:02:23.2116306Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-07-17T07:02:23.2992966Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-07-17T07:02:23.3012048Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog' 2025-07-17T07:02:23.3014414Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt' 2025-07-17T07:02:23.3017176Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest' 2025-07-17T07:02:23.3048359Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'... 2025-07-17T07:02:24.5176201Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'... 2025-07-17T07:02:25.3135238Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'... 2025-07-17T07:02:25.3982374Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-07-17T07:02:25.3999881Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-07-17T07:02:25.4001799Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-07-17T07:02:25.4004525Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-07-17T07:02:25.4007494Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-07-17T07:02:25.4010388Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-07-17T07:02:25.4013928Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-07-17T07:02:25.4016524Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-07-17T07:02:25.4019652Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-07-17T07:02:25.4050373Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'... 2025-07-17T07:02:27.2822591Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'... 2025-07-17T07:02:27.2824885Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'... 2025-07-17T07:02:27.2827229Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'... 2025-07-17T07:02:27.2829508Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'... 2025-07-17T07:02:27.3823949Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'... 2025-07-17T07:02:27.7231424Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'... 2025-07-17T07:02:27.8232539Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'... 2025-07-17T07:02:34.2212526Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-07-17T07:02:34.2393356Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-07-17T07:02:34.2771086Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-07-17T07:02:34.2911377Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-07-17T07:02:34.2927508Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-07-17T07:02:34.2954141Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'... 2025-07-17T07:02:34.5799602Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-07-17T07:02:34.5991570Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-07-17T07:02:34.6399958Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-07-17T07:02:34.7447537Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-07-17T07:02:34.7631663Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-07-17T07:02:34.8024001Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-07-17T07:02:34.8620442Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-07-17T07:02:34.9040762Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-07-17T07:02:34.9428968Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e' 2025-07-17T07:02:35.0565064Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72' 2025-07-17T07:02:35.4582648Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83' 2025-07-17T07:02:35.4621911Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/onnx/third_party/pybind11' 2025-07-17T07:02:35.4650330Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/onnx/third_party/pybind11'... 2025-07-17T07:02:36.4281950Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4' 2025-07-17T07:02:36.4988801Z Submodule path 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2025-07-17T07:02:36.5029711Z Submodule 'third_party/opentracing-cpp' (https://github.com/opentracing/opentracing-cpp.git) registered for path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-07-17T07:02:36.5034311Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-07-17T07:02:36.5038453Z Submodule 'tools/vcpkg' (https://github.com/Microsoft/vcpkg) registered for path 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-07-17T07:02:36.5067775Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/benchmark'... 2025-07-17T07:02:36.9728821Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentracing-cpp'... 2025-07-17T07:02:36.9731081Z Cloning into 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2025-07-17T07:02:48.0031635Z Submodule 'civetweb' (https://github.com/civetweb/civetweb.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-07-17T07:02:48.0033913Z Submodule 'googletest' (https://github.com/google/googletest.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-07-17T07:02:48.0064787Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'... 2025-07-17T07:02:50.3255391Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'... 2025-07-17T07:02:50.5761277Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4' 2025-07-17T07:02:50.6230697Z Submodule path 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'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-07-17T07:02:56.6355561Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-07-17T07:02:56.6398443Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-07-17T07:02:56.6442076Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-07-17T07:02:56.6483277Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-07-17T07:02:56.6526357Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-07-17T07:02:56.6568915Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-07-17T07:02:56.6632061Z Entering 'third_party/pocketfft' 2025-07-17T07:02:56.6675832Z Entering 'third_party/protobuf' 2025-07-17T07:02:56.6722096Z Entering 'third_party/protobuf/third_party/benchmark' 2025-07-17T07:02:56.6763058Z Entering 'third_party/protobuf/third_party/googletest' 2025-07-17T07:02:56.6805029Z Entering 'third_party/psimd' 2025-07-17T07:02:56.6847178Z Entering 'third_party/pthreadpool' 2025-07-17T07:02:56.6889073Z Entering 'third_party/pybind11' 2025-07-17T07:02:56.6932467Z Entering 'third_party/python-peachpy' 2025-07-17T07:02:56.6976065Z Entering 'third_party/sleef' 2025-07-17T07:02:56.7017954Z Entering 'third_party/tensorpipe' 2025-07-17T07:02:56.7059400Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-07-17T07:02:56.7100320Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-07-17T07:02:56.7139831Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-07-17T07:02:56.7179973Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-07-17T07:02:56.7223603Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-07-17T07:02:56.7283867Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'org-21003710@github.com:' 2025-07-17T07:02:56.7580491Z Entering 'android/libs/fbjni' 2025-07-17T07:02:56.7623769Z Entering 'third_party/FP16' 2025-07-17T07:02:56.7665572Z Entering 'third_party/FXdiv' 2025-07-17T07:02:56.7712530Z Entering 'third_party/NNPACK' 2025-07-17T07:02:56.7754377Z Entering 'third_party/NVTX' 2025-07-17T07:02:56.7797989Z Entering 'third_party/VulkanMemoryAllocator' 2025-07-17T07:02:56.7840169Z Entering 'third_party/XNNPACK' 2025-07-17T07:02:56.7898288Z Entering 'third_party/aiter' 2025-07-17T07:02:56.7941587Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-07-17T07:02:56.7993593Z Entering 'third_party/benchmark' 2025-07-17T07:02:56.8036396Z Entering 'third_party/composable_kernel' 2025-07-17T07:02:56.8085367Z Entering 'third_party/cpp-httplib' 2025-07-17T07:02:56.8127233Z Entering 'third_party/cpuinfo' 2025-07-17T07:02:56.8170118Z Entering 'third_party/cudnn_frontend' 2025-07-17T07:02:56.8214248Z Entering 'third_party/cutlass' 2025-07-17T07:02:56.8266803Z Entering 'third_party/fbgemm' 2025-07-17T07:02:56.8311579Z Entering 'third_party/fbgemm/external/asmjit' 2025-07-17T07:02:56.8352532Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-07-17T07:02:56.8400941Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-07-17T07:02:56.8442346Z Entering 'third_party/fbgemm/external/cutlass' 2025-07-17T07:02:56.8493092Z Entering 'third_party/fbgemm/external/googletest' 2025-07-17T07:02:56.8534931Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-07-17T07:02:56.8575194Z Entering 'third_party/fbgemm/external/json' 2025-07-17T07:02:56.8618414Z Entering 'third_party/flash-attention' 2025-07-17T07:02:56.8661300Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-07-17T07:02:56.8708434Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-07-17T07:02:56.8758871Z Entering 'third_party/flatbuffers' 2025-07-17T07:02:56.8804521Z Entering 'third_party/fmt' 2025-07-17T07:02:56.8847356Z Entering 'third_party/gemmlowp/gemmlowp' 2025-07-17T07:02:56.8889502Z Entering 'third_party/gloo' 2025-07-17T07:02:56.8931494Z Entering 'third_party/googletest' 2025-07-17T07:02:56.8974174Z Entering 'third_party/ideep' 2025-07-17T07:02:56.9016808Z Entering 'third_party/ideep/mkl-dnn' 2025-07-17T07:02:56.9066470Z Entering 'third_party/ittapi' 2025-07-17T07:02:56.9111100Z Entering 'third_party/kineto' 2025-07-17T07:02:56.9154925Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-07-17T07:02:56.9198100Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-07-17T07:02:56.9243409Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-07-17T07:02:56.9285854Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-07-17T07:02:56.9329081Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-07-17T07:02:56.9369450Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-07-17T07:02:56.9412697Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-07-17T07:02:56.9453684Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-07-17T07:02:56.9498065Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-07-17T07:02:56.9539995Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-07-17T07:02:56.9583333Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-07-17T07:02:56.9624518Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-07-17T07:02:56.9667187Z Entering 'third_party/kleidiai' 2025-07-17T07:02:56.9710320Z Entering 'third_party/mimalloc' 2025-07-17T07:02:56.9753134Z Entering 'third_party/nlohmann' 2025-07-17T07:02:56.9798096Z Entering 'third_party/onnx' 2025-07-17T07:02:56.9860397Z Entering 'third_party/onnx/third_party/pybind11' 2025-07-17T07:02:56.9904474Z Entering 'third_party/opentelemetry-cpp' 2025-07-17T07:02:56.9949433Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-07-17T07:02:56.9990765Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-07-17T07:02:57.0031058Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-07-17T07:02:57.0072921Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-07-17T07:02:57.0115589Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-07-17T07:02:57.0156648Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-07-17T07:02:57.0197968Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-07-17T07:02:57.0238242Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-07-17T07:02:57.0281010Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-07-17T07:02:57.0326396Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-07-17T07:02:57.0388666Z Entering 'third_party/pocketfft' 2025-07-17T07:02:57.0430450Z Entering 'third_party/protobuf' 2025-07-17T07:02:57.0476343Z Entering 'third_party/protobuf/third_party/benchmark' 2025-07-17T07:02:57.0517285Z Entering 'third_party/protobuf/third_party/googletest' 2025-07-17T07:02:57.0559818Z Entering 'third_party/psimd' 2025-07-17T07:02:57.0606403Z Entering 'third_party/pthreadpool' 2025-07-17T07:02:57.0648142Z Entering 'third_party/pybind11' 2025-07-17T07:02:57.0690423Z Entering 'third_party/python-peachpy' 2025-07-17T07:02:57.0732490Z Entering 'third_party/sleef' 2025-07-17T07:02:57.0778900Z Entering 'third_party/tensorpipe' 2025-07-17T07:02:57.0820452Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-07-17T07:02:57.0860855Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-07-17T07:02:57.0901226Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-07-17T07:02:57.0941497Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-07-17T07:02:57.0982054Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-07-17T07:02:57.1036126Z ##[endgroup] 2025-07-17T07:02:57.1073282Z [command]/usr/bin/git log -1 --format=%H 2025-07-17T07:02:57.1095704Z a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:02:57.1292419Z Prepare all required actions 2025-07-17T07:02:57.1293105Z Getting action download info 2025-07-17T07:02:57.2508061Z ##[group]Run ./.github/actions/setup-linux 2025-07-17T07:02:57.2508390Z env: 2025-07-17T07:02:57.2508612Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:02:57.2508896Z ##[endgroup] 2025-07-17T07:02:57.2552903Z ##[group]Run set -euo pipefail 2025-07-17T07:02:57.2553317Z set -euo pipefail 2025-07-17T07:02:57.2553624Z function get_ec2_metadata() { 2025-07-17T07:02:57.2553999Z  # Pulled from instance metadata endpoint for EC2 2025-07-17T07:02:57.2554649Z  # see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html 2025-07-17T07:02:57.2555225Z  category=$1 2025-07-17T07:02:57.2555579Z  # If it is GCP runner (runner name contains gcp), do not run this 2025-07-17T07:02:57.2556027Z  runner_name_str=i-00d4fcac0f1d6282f 2025-07-17T07:02:57.2556449Z  if [[ -f /.inarc ]]; then 2025-07-17T07:02:57.2556792Z  echo "ARC Runner, no info on ec2 metadata" 2025-07-17T07:02:57.2557189Z  elif [[ $runner_name_str == *"gcp"* ]]; then 2025-07-17T07:02:57.2557673Z  echo "Runner is from Google Cloud Platform, No info on ec2 metadata" 2025-07-17T07:02:57.2558118Z  else 2025-07-17T07:02:57.2558987Z  curl -H "X-aws-ec2-metadata-token: $(curl -s -X PUT "http://169.254.169.254/latest/api/token" -H "X-aws-ec2-metadata-token-ttl-seconds: 30")" -fsSL "http://169.254.169.254/latest/meta-data/${category}" 2025-07-17T07:02:57.2559928Z  fi 2025-07-17T07:02:57.2560149Z } 2025-07-17T07:02:57.2560420Z echo "ami-id: $(get_ec2_metadata ami-id)" 2025-07-17T07:02:57.2560842Z echo "instance-id: $(get_ec2_metadata instance-id)" 2025-07-17T07:02:57.2561330Z echo "instance-type: $(get_ec2_metadata instance-type)" 2025-07-17T07:02:57.2561759Z echo "system info $(uname -a)" 2025-07-17T07:02:57.2571966Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:02:57.2572356Z env: 2025-07-17T07:02:57.2572575Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:02:57.2572828Z ##[endgroup] 2025-07-17T07:02:57.2728721Z ami-id: ami-05ffe3c48a9991133 2025-07-17T07:02:57.2830059Z instance-id: i-00d4fcac0f1d6282f 2025-07-17T07:02:57.2926038Z instance-type: c5.2xlarge 2025-07-17T07:02:57.2936786Z system info Linux ip-10-0-42-148.ec2.internal 6.1.141-155.222.amzn2023.x86_64 #1 SMP PREEMPT_DYNAMIC Tue Jun 17 10:29:47 UTC 2025 x86_64 x86_64 x86_64 GNU/Linux 2025-07-17T07:02:57.2961847Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-07-17T07:02:57.2962821Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-07-17T07:02:57.2970346Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:02:57.2970754Z env: 2025-07-17T07:02:57.2970979Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:02:57.2971305Z ##[endgroup] 2025-07-17T07:02:57.3028827Z ##[group]Run if systemctl is-active --quiet docker; then 2025-07-17T07:02:57.3029291Z if systemctl is-active --quiet docker; then 2025-07-17T07:02:57.3029674Z  echo "Docker daemon is running..."; 2025-07-17T07:02:57.3030010Z else 2025-07-17T07:02:57.3030373Z  echo "Starting docker daemon..." && sudo systemctl start docker; 2025-07-17T07:02:57.3030798Z fi 2025-07-17T07:02:57.3036100Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:02:57.3036489Z env: 2025-07-17T07:02:57.3036710Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:02:57.3036962Z ##[endgroup] 2025-07-17T07:02:57.3115215Z Docker daemon is running... 2025-07-17T07:02:57.3162162Z ##[group]Run nick-fields/retry@v3.0.0 2025-07-17T07:02:57.3162466Z with: 2025-07-17T07:02:57.3162681Z shell: bash 2025-07-17T07:02:57.3163173Z timeout_minutes: 5 2025-07-17T07:02:57.3163415Z max_attempts: 3 2025-07-17T07:02:57.3163665Z retry_wait_seconds: 30 2025-07-17T07:02:57.3166106Z command: AWS_ACCOUNT_ID=$(aws sts get-caller-identity|grep Account|cut -f4 -d\") aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \ --password-stdin "$AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com" # For LF Runners we need to make sure we also login to Meta's ECR docker registry too. META_AWS_ACCOUNT_ID=308535385114 if [ "$AWS_ACCOUNT_ID" != "$META_AWS_ACCOUNT_ID" ] ; then aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \ --password-stdin "$META_AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com" fi 2025-07-17T07:02:57.3168499Z polling_interval_seconds: 1 2025-07-17T07:02:57.3168802Z warning_on_retry: true 2025-07-17T07:02:57.3169078Z continue_on_error: false 2025-07-17T07:02:57.3169332Z env: 2025-07-17T07:02:57.3169563Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:02:57.3169840Z AWS_RETRY_MODE: standard 2025-07-17T07:02:57.3170320Z AWS_MAX_ATTEMPTS: 5 2025-07-17T07:02:57.3170595Z AWS_DEFAULT_REGION: us-east-1 2025-07-17T07:02:57.3170881Z ##[endgroup] 2025-07-17T07:02:58.5163519Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-07-17T07:02:58.5164560Z Configure a credential helper to remove this warning. See 2025-07-17T07:02:58.5165581Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-07-17T07:02:58.5166239Z 2025-07-17T07:02:58.5261016Z Login Succeeded 2025-07-17T07:02:59.4563133Z Command completed after 1 attempt(s). 2025-07-17T07:02:59.4630133Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-07-17T07:02:59.4630681Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-07-17T07:02:59.4631165Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-07-17T07:02:59.4638344Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:02:59.4638750Z env: 2025-07-17T07:02:59.4638981Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:02:59.4639258Z ##[endgroup] 2025-07-17T07:02:59.4732415Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty 2025-07-17T07:02:59.4732999Z # ignore expansion of "docker ps -q" since it could be empty 2025-07-17T07:02:59.4733439Z # shellcheck disable=SC2046 2025-07-17T07:02:59.4733777Z docker stop $(docker ps -q) || true 2025-07-17T07:02:59.4734117Z # Prune all of the docker images 2025-07-17T07:02:59.4734454Z docker system prune -af 2025-07-17T07:02:59.4739865Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:02:59.4740251Z env: 2025-07-17T07:02:59.4740478Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:02:59.4740730Z ##[endgroup] 2025-07-17T07:02:59.5159482Z "docker stop" requires at least 1 argument. 2025-07-17T07:02:59.5159897Z See 'docker stop --help'. 2025-07-17T07:02:59.5160117Z 2025-07-17T07:02:59.5160297Z Usage: docker stop [OPTIONS] CONTAINER [CONTAINER...] 2025-07-17T07:02:59.5160579Z 2025-07-17T07:02:59.5160703Z Stop one or more running containers 2025-07-17T07:02:59.5359847Z Total reclaimed space: 0B 2025-07-17T07:02:59.5400193Z ##[group]Run set +e 2025-07-17T07:02:59.5400482Z set +e 2025-07-17T07:02:59.5400746Z set -x 2025-07-17T07:02:59.5400975Z  2025-07-17T07:02:59.5401208Z PT_DOMAIN=download.pytorch.org 2025-07-17T07:02:59.5401801Z # TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400, 2025-07-17T07:02:59.5402583Z # cleaning this up once the issue is fixed. There are more than one resolved IP here, the last 2025-07-17T07:02:59.5403131Z # one is returned at random 2025-07-17T07:02:59.5403520Z RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1) 2025-07-17T07:02:59.5403908Z  2025-07-17T07:02:59.5404291Z if [ -z "${RESOLVED_IP}" ]; then 2025-07-17T07:02:59.5404841Z  echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..." 2025-07-17T07:02:59.5405494Z  RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1) 2025-07-17T07:02:59.5405903Z  2025-07-17T07:02:59.5406141Z  if [ -z "${RESOLVED_IP}" ]; then 2025-07-17T07:02:59.5406524Z  echo "Couldn't resolve ${PT_DOMAIN}, exiting..." 2025-07-17T07:02:59.5406896Z  exit 1 2025-07-17T07:02:59.5407133Z  fi 2025-07-17T07:02:59.5407340Z fi 2025-07-17T07:02:59.5407550Z  2025-07-17T07:02:59.5407810Z if grep -r "${PT_DOMAIN}" /etc/hosts; then 2025-07-17T07:02:59.5408173Z  # Clean up any old records first 2025-07-17T07:02:59.5408541Z  sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts 2025-07-17T07:02:59.5408871Z fi 2025-07-17T07:02:59.5409080Z  2025-07-17T07:02:59.5409383Z echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts 2025-07-17T07:02:59.5409794Z cat /etc/hosts 2025-07-17T07:02:59.5415730Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:02:59.5416107Z env: 2025-07-17T07:02:59.5416336Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:02:59.5416603Z ##[endgroup] 2025-07-17T07:02:59.5440381Z + PT_DOMAIN=download.pytorch.org 2025-07-17T07:02:59.5445753Z ++ dig -4 +short download.pytorch.org 2025-07-17T07:02:59.5446471Z ++ tail -n1 2025-07-17T07:02:59.5744297Z + RESOLVED_IP=18.160.10.76 2025-07-17T07:02:59.5744888Z + '[' -z 18.160.10.76 ']' 2025-07-17T07:02:59.5745421Z + grep -r download.pytorch.org /etc/hosts 2025-07-17T07:02:59.5761596Z + echo '18.160.10.76 download.pytorch.org' 2025-07-17T07:02:59.5762756Z + sudo tee -a /etc/hosts 2025-07-17T07:02:59.9362312Z 18.160.10.76 download.pytorch.org 2025-07-17T07:02:59.9385329Z + cat /etc/hosts 2025-07-17T07:02:59.9395166Z 127.0.0.1 localhost localhost.localdomain localhost4 localhost4.localdomain4 2025-07-17T07:02:59.9401085Z ::1 localhost6 localhost6.localdomain6 2025-07-17T07:02:59.9401467Z 18.160.10.76 download.pytorch.org 2025-07-17T07:02:59.9578637Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main 2025-07-17T07:02:59.9579111Z with: 2025-07-17T07:02:59.9579867Z docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:02:59.9580733Z use-custom-docker-registry: true 2025-07-17T07:02:59.9581052Z docker-build-dir: .ci/docker 2025-07-17T07:02:59.9581342Z docker-build-script: ./build.sh 2025-07-17T07:02:59.9581652Z working-directory: . 2025-07-17T07:02:59.9582008Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-07-17T07:02:59.9582403Z force-push: false 2025-07-17T07:02:59.9582639Z env: 2025-07-17T07:02:59.9582853Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:02:59.9583100Z ##[endgroup] 2025-07-17T07:02:59.9610957Z ##[group]Run set -ex 2025-07-17T07:02:59.9611284Z set -ex 2025-07-17T07:02:59.9611512Z  2025-07-17T07:02:59.9611958Z # If the docker build directory or the build script doesn't exist, the action will 2025-07-17T07:02:59.9612639Z # gracefully return the docker image name as it is. Pulling docker image in Linux 2025-07-17T07:02:59.9613209Z # job could then download the pre-built image as usual 2025-07-17T07:02:59.9613909Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then 2025-07-17T07:02:59.9614567Z  echo "skip=false" >> "${GITHUB_OUTPUT}" 2025-07-17T07:02:59.9614896Z else 2025-07-17T07:02:59.9615162Z  echo "skip=true" >> "${GITHUB_OUTPUT}" 2025-07-17T07:02:59.9615623Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-07-17T07:02:59.9616041Z  2025-07-17T07:02:59.9616601Z  echo "Not using custom ECR registry. Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..." 2025-07-17T07:02:59.9617418Z  exit 0 2025-07-17T07:02:59.9617644Z fi 2025-07-17T07:02:59.9617843Z  2025-07-17T07:02:59.9618184Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then 2025-07-17T07:02:59.9618800Z  # The docker image name already includes the ECR prefix and tag, so we can just 2025-07-17T07:02:59.9619405Z  # use it as it is, but first let's extract the tag 2025-07-17T07:02:59.9619883Z  DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}') 2025-07-17T07:02:59.9620399Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-07-17T07:02:59.9620900Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-07-17T07:02:59.9621316Z else 2025-07-17T07:02:59.9621566Z  if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then 2025-07-17T07:02:59.9621961Z  CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:} 2025-07-17T07:02:59.9622366Z  DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*} 2025-07-17T07:02:59.9622695Z  fi 2025-07-17T07:02:59.9623159Z  DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}") 2025-07-17T07:02:59.9623780Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-07-17T07:02:59.9624434Z  echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-07-17T07:02:59.9625141Z  echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}" 2025-07-17T07:02:59.9625577Z fi 2025-07-17T07:02:59.9633158Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:02:59.9633547Z env: 2025-07-17T07:02:59.9633769Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:02:59.9634029Z REPO_NAME: pytorch 2025-07-17T07:02:59.9634921Z DOCKER_IMAGE_NAME: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:02:59.9635782Z DOCKER_BUILD_DIR: .ci/docker 2025-07-17T07:02:59.9636080Z DOCKER_BUILD_SCRIPT: ./build.sh 2025-07-17T07:02:59.9636458Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-07-17T07:02:59.9636869Z USE_CUSTOM_DOCKER_REGISTRY: true 2025-07-17T07:02:59.9637168Z CUSTOM_TAG_PREFIX: 2025-07-17T07:02:59.9637403Z ##[endgroup] 2025-07-17T07:02:59.9663861Z + [[ -d .ci/docker ]] 2025-07-17T07:02:59.9664141Z + [[ -f .ci/docker/./build.sh ]] 2025-07-17T07:02:59.9664429Z + [[ true == \t\r\u\e ]] 2025-07-17T07:02:59.9664686Z + echo skip=false 2025-07-17T07:02:59.9665732Z + [[ 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d == *\3\0\8\5\3\5\3\8\5\1\1\4\.\d\k\r\.\e\c\r\.\u\s\-\e\a\s\t\-\1\.\a\m\a\z\o\n\a\w\s\.\c\o\m\/\p\y\t\o\r\c\h* ]] 2025-07-17T07:02:59.9671606Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:02:59.9675624Z ++ awk -F '[:,]' '{print $2}' 2025-07-17T07:02:59.9698039Z + DOCKER_TAG=pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:02:59.9699432Z + echo docker-tag=pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:02:59.9701019Z + echo docker-image=308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:02:59.9736325Z ##[group]Run set +e 2025-07-17T07:02:59.9736634Z set +e 2025-07-17T07:02:59.9736869Z set -x 2025-07-17T07:02:59.9737097Z  2025-07-17T07:02:59.9737299Z login() { 2025-07-17T07:02:59.9737788Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-07-17T07:02:59.9738464Z } 2025-07-17T07:02:59.9738660Z  2025-07-17T07:02:59.9738876Z retry () { 2025-07-17T07:02:59.9739153Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-07-17T07:02:59.9739461Z } 2025-07-17T07:02:59.9739682Z  2025-07-17T07:02:59.9739915Z retry login "${DOCKER_REGISTRY}" 2025-07-17T07:02:59.9740224Z  2025-07-17T07:02:59.9740433Z START_TIME=$(date +%s) 2025-07-17T07:02:59.9740773Z # Wait up to 120 minutes 2025-07-17T07:02:59.9741140Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do 2025-07-17T07:02:59.9741627Z  # Check if image already exists, if it does then skip building it 2025-07-17T07:02:59.9742129Z  if docker manifest inspect "${DOCKER_IMAGE}"; then 2025-07-17T07:02:59.9742498Z  exit 0 2025-07-17T07:02:59.9742721Z  fi 2025-07-17T07:02:59.9742932Z  2025-07-17T07:02:59.9743316Z  # NB: This flag is used by Docker build workflow to push the image to ECR, so we can 2025-07-17T07:02:59.9744005Z  # use this to differentiate between the Docker build and regular build jobs. For the 2025-07-17T07:02:59.9744670Z  # latter, it will wait for the Docker images to become available before continuing 2025-07-17T07:02:59.9745200Z  if [ "${DOCKER_PUSH:-false}" == "true" ]; then 2025-07-17T07:02:59.9745604Z  # It's a Docker build job, let's build the image 2025-07-17T07:02:59.9745955Z  break 2025-07-17T07:02:59.9746176Z  else 2025-07-17T07:02:59.9746520Z  # It's a regular build job, wait for the image to become available 2025-07-17T07:02:59.9746939Z  sleep 300 2025-07-17T07:02:59.9747173Z  fi 2025-07-17T07:02:59.9747391Z done 2025-07-17T07:02:59.9747613Z  2025-07-17T07:02:59.9747954Z # NB: This part requires a full checkout. Otherwise, the merge base will 2025-07-17T07:02:59.9748545Z # be empty. The default action would be to continue rebuild the image 2025-07-17T07:02:59.9749169Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then 2025-07-17T07:02:59.9749637Z  # if we're on the base branch then use the parent commit 2025-07-17T07:02:59.9750034Z  MERGE_BASE=$(git rev-parse HEAD~) 2025-07-17T07:02:59.9750353Z else 2025-07-17T07:02:59.9750680Z  # otherwise we're on a PR, so use the most recent base commit 2025-07-17T07:02:59.9751153Z  MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION") 2025-07-17T07:02:59.9751521Z fi 2025-07-17T07:02:59.9751731Z  2025-07-17T07:02:59.9751964Z if [[ -z "${MERGE_BASE}" ]]; then 2025-07-17T07:02:59.9752311Z  echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-07-17T07:02:59.9752647Z  2025-07-17T07:02:59.9753122Z  echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..." 2025-07-17T07:02:59.9753685Z  exit 0 2025-07-17T07:02:59.9753912Z fi 2025-07-17T07:02:59.9754125Z  2025-07-17T07:02:59.9754419Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then 2025-07-17T07:02:59.9755116Z  echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit" 2025-07-17T07:02:59.9755715Z  exit 1 2025-07-17T07:02:59.9755941Z fi 2025-07-17T07:02:59.9756135Z  2025-07-17T07:02:59.9756540Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}") 2025-07-17T07:02:59.9757210Z # If no image exists but the hash is the same as the previous hash then we should error out here 2025-07-17T07:02:59.9757811Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then 2025-07-17T07:02:59.9758495Z  echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch" 2025-07-17T07:02:59.9759346Z  echo " Will re-build docker image to store in local cache, TTS may be longer" 2025-07-17T07:02:59.9759811Z fi 2025-07-17T07:02:59.9760010Z  2025-07-17T07:02:59.9760270Z echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-07-17T07:02:59.9766302Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:02:59.9766687Z env: 2025-07-17T07:02:59.9766896Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:02:59.9767180Z DOCKER_BUILD_DIR: .ci/docker 2025-07-17T07:02:59.9767577Z BASE_REVISION: a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:02:59.9768438Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:02:59.9769468Z DOCKER_TAG: pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:02:59.9770319Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-07-17T07:02:59.9770731Z DOCKER_PUSH: 2025-07-17T07:02:59.9770946Z ##[endgroup] 2025-07-17T07:02:59.9794321Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-07-17T07:02:59.9794762Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-07-17T07:02:59.9797331Z + aws ecr get-login-password --region us-east-1 2025-07-17T07:02:59.9798416Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-07-17T07:03:00.4835924Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-07-17T07:03:00.4836563Z Configure a credential helper to remove this warning. See 2025-07-17T07:03:00.4837161Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-07-17T07:03:00.4837580Z 2025-07-17T07:03:00.4839616Z Login Succeeded 2025-07-17T07:03:00.4854303Z ++ date +%s 2025-07-17T07:03:00.4863980Z + START_TIME=1752735780 2025-07-17T07:03:00.4867255Z ++ date +%s 2025-07-17T07:03:00.4876758Z + [[ 1752728580 -lt 1752735780 ]] 2025-07-17T07:03:00.4878217Z + docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:03:00.6963665Z { 2025-07-17T07:03:00.6964036Z "schemaVersion": 2, 2025-07-17T07:03:00.6964737Z "mediaType": "application/vnd.docker.distribution.manifest.v2+json", 2025-07-17T07:03:00.6965214Z "config": { 2025-07-17T07:03:00.6965629Z "mediaType": "application/vnd.docker.container.image.v1+json", 2025-07-17T07:03:00.6966049Z "size": 29789, 2025-07-17T07:03:00.6966598Z "digest": 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"sha256:72f42db112acff3fe786e412852e40172547e2f0805d8bb3165250351607bcc6" 2025-07-17T07:03:00.7056020Z }, 2025-07-17T07:03:00.7056210Z { 2025-07-17T07:03:00.7056523Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7056942Z "size": 134, 2025-07-17T07:03:00.7057345Z "digest": "sha256:7c952e9bce00315c28853ab1776128c841cf6569a57847f459cba91f5a8acc8e" 2025-07-17T07:03:00.7057816Z }, 2025-07-17T07:03:00.7057995Z { 2025-07-17T07:03:00.7058322Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7058741Z "size": 32, 2025-07-17T07:03:00.7059140Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-07-17T07:03:00.7059620Z }, 2025-07-17T07:03:00.7059812Z { 2025-07-17T07:03:00.7060135Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7060619Z "size": 195, 2025-07-17T07:03:00.7061037Z "digest": "sha256:3b1502de0f3b198fb39afb20836194ba99700dc67ce7ad4c243e568453198d25" 2025-07-17T07:03:00.7061500Z }, 2025-07-17T07:03:00.7061694Z { 2025-07-17T07:03:00.7062021Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7062431Z "size": 116, 2025-07-17T07:03:00.7062841Z "digest": "sha256:173b45b41ce0878e815890c196d343fc210775ebe229cedf931b07f2bc460e27" 2025-07-17T07:03:00.7063313Z }, 2025-07-17T07:03:00.7063508Z { 2025-07-17T07:03:00.7063822Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7064240Z "size": 32, 2025-07-17T07:03:00.7064654Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-07-17T07:03:00.7065129Z }, 2025-07-17T07:03:00.7065332Z { 2025-07-17T07:03:00.7065731Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7066143Z "size": 128, 2025-07-17T07:03:00.7066547Z "digest": "sha256:50399975739a3670b93a14d30c63319a2d88a9f69f88c53da9233122cd897cfc" 2025-07-17T07:03:00.7067010Z }, 2025-07-17T07:03:00.7067190Z { 2025-07-17T07:03:00.7067515Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7067933Z "size": 777, 2025-07-17T07:03:00.7068339Z "digest": "sha256:34b7cc5cf1d9abe64f6305deb3656733eaf90f26eaa3f85cfbb2c9dd7e043e3d" 2025-07-17T07:03:00.7068823Z }, 2025-07-17T07:03:00.7069013Z { 2025-07-17T07:03:00.7069340Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7069748Z "size": 724, 2025-07-17T07:03:00.7070594Z "digest": "sha256:c3fd79404829cd24625740ba8c0595c401878e558aa17f440e34f121dd6facdf" 2025-07-17T07:03:00.7071072Z }, 2025-07-17T07:03:00.7071252Z { 2025-07-17T07:03:00.7071577Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7071996Z "size": 141, 2025-07-17T07:03:00.7072418Z "digest": "sha256:dffea587205ddaa02cc6d95ddd5de1d6dbf175b6a2dbc7dbe952b096fe96ba62" 2025-07-17T07:03:00.7072912Z }, 2025-07-17T07:03:00.7073225Z { 2025-07-17T07:03:00.7073542Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7073964Z "size": 32, 2025-07-17T07:03:00.7074380Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-07-17T07:03:00.7074861Z }, 2025-07-17T07:03:00.7075043Z { 2025-07-17T07:03:00.7075375Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7075798Z "size": 160, 2025-07-17T07:03:00.7076205Z "digest": "sha256:8d04c6fef71e3cf9be0786633cdb12ad20e580a221f50d7fa1fa5d30f3687514" 2025-07-17T07:03:00.7076689Z }, 2025-07-17T07:03:00.7076880Z { 2025-07-17T07:03:00.7077193Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7077611Z "size": 1012, 2025-07-17T07:03:00.7078031Z "digest": "sha256:56cdce5d93425b58fcc507ea1c93c64ca9a646f16afacc7d86ed7a3b54c06a2b" 2025-07-17T07:03:00.7078508Z }, 2025-07-17T07:03:00.7078697Z { 2025-07-17T07:03:00.7079026Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7079432Z "size": 724, 2025-07-17T07:03:00.7079833Z "digest": "sha256:c3fd79404829cd24625740ba8c0595c401878e558aa17f440e34f121dd6facdf" 2025-07-17T07:03:00.7080296Z }, 2025-07-17T07:03:00.7080489Z { 2025-07-17T07:03:00.7080802Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7081217Z "size": 134, 2025-07-17T07:03:00.7081627Z "digest": "sha256:060e0a2319133e77ebf1b7b23c81602e9b9d2c25f7f9ee43fde89b7a6a645d7a" 2025-07-17T07:03:00.7082089Z }, 2025-07-17T07:03:00.7082278Z { 2025-07-17T07:03:00.7082602Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7083006Z "size": 32, 2025-07-17T07:03:00.7083415Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-07-17T07:03:00.7084009Z }, 2025-07-17T07:03:00.7084185Z { 2025-07-17T07:03:00.7084516Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7084934Z "size": 159, 2025-07-17T07:03:00.7085417Z "digest": "sha256:3c6a2d65b5bbb8f68cf3618a693f7fb4accbe30e3aa5786873365b3eed8b8b1b" 2025-07-17T07:03:00.7085903Z }, 2025-07-17T07:03:00.7086094Z { 2025-07-17T07:03:00.7086417Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7086821Z "size": 1370, 2025-07-17T07:03:00.7087229Z "digest": "sha256:a7015d1f229ed3837db36de6f01b45e34074b67f082934d1609845314e238350" 2025-07-17T07:03:00.7087698Z }, 2025-07-17T07:03:00.7087879Z { 2025-07-17T07:03:00.7088210Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7088631Z "size": 32, 2025-07-17T07:03:00.7089032Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-07-17T07:03:00.7089511Z }, 2025-07-17T07:03:00.7089703Z { 2025-07-17T07:03:00.7090017Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7090445Z "size": 136, 2025-07-17T07:03:00.7090855Z "digest": "sha256:0ddb9567cfa96bb304d84caed95336e9802f53dc71b7b2255a1d8f6612fc6455" 2025-07-17T07:03:00.7091333Z }, 2025-07-17T07:03:00.7091509Z { 2025-07-17T07:03:00.7091836Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7092253Z "size": 380, 2025-07-17T07:03:00.7092657Z "digest": "sha256:08123ea660cb56e40bf8cfe8ddc3856fc67ee90548bba0b2f37f7b56a36785b5" 2025-07-17T07:03:00.7093139Z }, 2025-07-17T07:03:00.7093331Z { 2025-07-17T07:03:00.7093647Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7094067Z "size": 32, 2025-07-17T07:03:00.7094475Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-07-17T07:03:00.7094944Z }, 2025-07-17T07:03:00.7095119Z { 2025-07-17T07:03:00.7095433Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7095849Z "size": 104, 2025-07-17T07:03:00.7096303Z "digest": "sha256:06f07ca145d9a61b91372346682b9c0d458fe83ef704153799346502349aafe6" 2025-07-17T07:03:00.7096763Z }, 2025-07-17T07:03:00.7096942Z { 2025-07-17T07:03:00.7097251Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7097661Z "size": 407, 2025-07-17T07:03:00.7098073Z "digest": "sha256:a151adebebbf7bcaa2e64b35305f5def7cde3f60b683da7b9150e0794d72b355" 2025-07-17T07:03:00.7098546Z }, 2025-07-17T07:03:00.7098727Z { 2025-07-17T07:03:00.7099038Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7099442Z "size": 32, 2025-07-17T07:03:00.7099845Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-07-17T07:03:00.7100314Z }, 2025-07-17T07:03:00.7100482Z { 2025-07-17T07:03:00.7100797Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7101210Z "size": 109, 2025-07-17T07:03:00.7101607Z "digest": "sha256:a567163437c52a32d717b879e4e67e0d26700afb8fb1dcc6adf07cce1f378541" 2025-07-17T07:03:00.7102064Z }, 2025-07-17T07:03:00.7102243Z { 2025-07-17T07:03:00.7102560Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7102960Z "size": 1897, 2025-07-17T07:03:00.7103356Z "digest": "sha256:f70d840f762475b3bdb839fa2820789f2283b17049693adfd5bd8a28111a1636" 2025-07-17T07:03:00.7103818Z }, 2025-07-17T07:03:00.7103988Z { 2025-07-17T07:03:00.7104301Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7104709Z "size": 241722875, 2025-07-17T07:03:00.7105131Z "digest": "sha256:d7369ebc3a9abb1dfd0315f8d8b2acfe67465121ec4d4ca53a3912de4666d7b4" 2025-07-17T07:03:00.7105605Z }, 2025-07-17T07:03:00.7105778Z { 2025-07-17T07:03:00.7106082Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7106541Z "size": 106, 2025-07-17T07:03:00.7106935Z "digest": "sha256:4184c6a7fd64e170b5f6feff80108032071e259411230ad9b6285c51c16b3b1c" 2025-07-17T07:03:00.7107388Z }, 2025-07-17T07:03:00.7107553Z { 2025-07-17T07:03:00.7107863Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7108271Z "size": 165, 2025-07-17T07:03:00.7108653Z "digest": "sha256:22ddb070c1113f484657d52b520abe86a237739eb1e504061ac0919605df0563" 2025-07-17T07:03:00.7109108Z }, 2025-07-17T07:03:00.7109284Z { 2025-07-17T07:03:00.7109586Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7109992Z "size": 7944, 2025-07-17T07:03:00.7110396Z "digest": "sha256:e4b9b40818eba0d7a5c5dbbc6bf60a852ba56250ac95c5bd47336b812004f2d6" 2025-07-17T07:03:00.7110854Z }, 2025-07-17T07:03:00.7111024Z { 2025-07-17T07:03:00.7111335Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7111738Z "size": 8069, 2025-07-17T07:03:00.7112131Z "digest": "sha256:403c8a0d600099f8231b52cb057d5b98607787dda95ccbca1b9228642002e7e5" 2025-07-17T07:03:00.7112591Z }, 2025-07-17T07:03:00.7112770Z { 2025-07-17T07:03:00.7113074Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7113509Z "size": 303, 2025-07-17T07:03:00.7113910Z "digest": "sha256:6ce29e0f73ef2e1778e2252d8da8392c2bd06903f31860fbf08d26a8ca17c76e" 2025-07-17T07:03:00.7114367Z }, 2025-07-17T07:03:00.7114547Z { 2025-07-17T07:03:00.7114860Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7115260Z "size": 32, 2025-07-17T07:03:00.7115659Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-07-17T07:03:00.7116123Z }, 2025-07-17T07:03:00.7116293Z { 2025-07-17T07:03:00.7116596Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7116995Z "size": 108, 2025-07-17T07:03:00.7117387Z "digest": "sha256:8341c69d63c87382777fa1e7dfc5f846cc3428ee64adae6d44a82d1bed0efc49" 2025-07-17T07:03:00.7117847Z }, 2025-07-17T07:03:00.7118021Z { 2025-07-17T07:03:00.7118390Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7118796Z "size": 54145699, 2025-07-17T07:03:00.7119206Z "digest": "sha256:9fb68e35f66fa77f535422964bc64a23cbd493353936c0fc95a895e200cdfbfb" 2025-07-17T07:03:00.7119664Z }, 2025-07-17T07:03:00.7119845Z { 2025-07-17T07:03:00.7120162Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-07-17T07:03:00.7120564Z "size": 32, 2025-07-17T07:03:00.7120952Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-07-17T07:03:00.7121415Z } 2025-07-17T07:03:00.7121585Z ] 2025-07-17T07:03:00.7121751Z } 2025-07-17T07:03:00.7157446Z ##[group]Run set -eux 2025-07-17T07:03:00.7157729Z set -eux 2025-07-17T07:03:00.7158639Z aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token | jq --raw-output '.SecretString' | jq -r .docker_hub_readonly_token | docker login --username pytorchbot --password-stdin 2025-07-17T07:03:00.7167318Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:03:00.7167692Z env: 2025-07-17T07:03:00.7167911Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:03:00.7168177Z ##[endgroup] 2025-07-17T07:03:00.7196897Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token 2025-07-17T07:03:00.7197735Z + jq --raw-output .SecretString 2025-07-17T07:03:00.7198534Z + jq -r .docker_hub_readonly_token 2025-07-17T07:03:00.7201284Z + docker login --username pytorchbot --password-stdin 2025-07-17T07:03:01.2965168Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-07-17T07:03:01.2965935Z Configure a credential helper to remove this warning. See 2025-07-17T07:03:01.2966514Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-07-17T07:03:01.2966932Z 2025-07-17T07:03:01.2970411Z Login Succeeded 2025-07-17T07:03:01.3055022Z ##[group]Run tag=${ECR_DOCKER_IMAGE##*:} 2025-07-17T07:03:01.3055408Z tag=${ECR_DOCKER_IMAGE##*:} 2025-07-17T07:03:01.3055809Z echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}" 2025-07-17T07:03:01.3061704Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:03:01.3062095Z env: 2025-07-17T07:03:01.3062303Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:03:01.3063100Z ECR_DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:03:01.3063924Z ##[endgroup] 2025-07-17T07:03:01.3089989Z docker pull ghcr.io/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:03:01.3167420Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main 2025-07-17T07:03:01.3167857Z with: 2025-07-17T07:03:01.3168586Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:03:01.3169517Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-07-17T07:03:01.3169911Z env: 2025-07-17T07:03:01.3170320Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:03:01.3170589Z ##[endgroup] 2025-07-17T07:03:01.3194313Z ##[group]Run set -x 2025-07-17T07:03:01.3194584Z set -x 2025-07-17T07:03:01.3194813Z set +e 2025-07-17T07:03:01.3195038Z  2025-07-17T07:03:01.3195236Z login() { 2025-07-17T07:03:01.3195730Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-07-17T07:03:01.3196264Z } 2025-07-17T07:03:01.3196461Z  2025-07-17T07:03:01.3196730Z retry () { 2025-07-17T07:03:01.3196996Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-07-17T07:03:01.3197321Z } 2025-07-17T07:03:01.3197534Z  2025-07-17T07:03:01.3197816Z retry login "${DOCKER_REGISTRY}" 2025-07-17T07:03:01.3198129Z  2025-07-17T07:03:01.3198625Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024') 2025-07-17T07:03:01.3199365Z echo "Compressed size of image in MB: ${IMAGE_SIZE}" 2025-07-17T07:03:01.3199733Z  2025-07-17T07:03:01.3199943Z set -e 2025-07-17T07:03:01.3200303Z # ignore output since only exit code is used for conditional 2025-07-17T07:03:01.3200802Z # only pull docker image if it's not available locally 2025-07-17T07:03:01.3201343Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then 2025-07-17T07:03:01.3201860Z  retry docker pull "${DOCKER_IMAGE}" 2025-07-17T07:03:01.3202183Z fi 2025-07-17T07:03:01.3207848Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:03:01.3208239Z env: 2025-07-17T07:03:01.3208455Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:03:01.3209238Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:03:01.3210146Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-07-17T07:03:01.3210542Z ##[endgroup] 2025-07-17T07:03:01.3233164Z + set +e 2025-07-17T07:03:01.3233897Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-07-17T07:03:01.3234364Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-07-17T07:03:01.3237096Z + aws ecr get-login-password --region us-east-1 2025-07-17T07:03:01.3237878Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-07-17T07:03:01.8408487Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-07-17T07:03:01.8409164Z Configure a credential helper to remove this warning. See 2025-07-17T07:03:01.8410051Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-07-17T07:03:01.8410963Z 2025-07-17T07:03:01.8411129Z Login Succeeded 2025-07-17T07:03:01.8428561Z ++ docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:03:01.8429522Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024' 2025-07-17T07:03:02.0460246Z + IMAGE_SIZE=4469.723728179932 2025-07-17T07:03:02.0460676Z + echo 'Compressed size of image in MB: 4469.723728179932' 2025-07-17T07:03:02.0461052Z + set -e 2025-07-17T07:03:02.0461849Z + docker inspect --type=image 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:03:02.0463093Z Compressed size of image in MB: 4469.723728179932 2025-07-17T07:03:02.0595755Z + retry docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:03:02.0597147Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:03:02.2724893Z pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d: Pulling from pytorch/ci-image 2025-07-17T07:03:02.2732213Z 66587c81b81a: Pulling fs layer 2025-07-17T07:03:02.2734085Z 7a5c9899d937: Pulling fs layer 2025-07-17T07:03:02.2734687Z 9d8fe31f4371: Pulling fs layer 2025-07-17T07:03:02.2735171Z 4ea72d4d995b: Pulling fs layer 2025-07-17T07:03:02.2735583Z 0b21d3c7919b: Pulling fs layer 2025-07-17T07:03:02.2736035Z ff0141e78db7: Pulling fs layer 2025-07-17T07:03:02.2736469Z a8aa8a9fa61b: Pulling fs layer 2025-07-17T07:03:02.2736918Z a1030ae92635: Pulling fs layer 2025-07-17T07:03:02.2737350Z 1bd9396864e4: Pulling fs layer 2025-07-17T07:03:02.2737634Z e80da71796c5: Pulling fs layer 2025-07-17T07:03:02.2737907Z c0c195959436: Pulling fs layer 2025-07-17T07:03:02.2738251Z c3fd79404829: Pulling fs layer 2025-07-17T07:03:02.2738606Z 0b21d3c7919b: Waiting 2025-07-17T07:03:02.2738841Z a8aa8a9fa61b: Waiting 2025-07-17T07:03:02.2739082Z a1030ae92635: Waiting 2025-07-17T07:03:02.2739322Z e80da71796c5: Waiting 2025-07-17T07:03:02.2739581Z 4ea72d4d995b: Waiting 2025-07-17T07:03:02.2739834Z 6f5ba5923d9e: Pulling fs layer 2025-07-17T07:03:02.2740110Z ff0141e78db7: Waiting 2025-07-17T07:03:02.2740694Z cc5ad5bb5c8f: Pulling fs layer 2025-07-17T07:03:02.2741029Z c0c195959436: Waiting 2025-07-17T07:03:02.2741439Z c3fd79404829: Waiting 2025-07-17T07:03:02.2741742Z 4f4fb700ef54: Pulling fs layer 2025-07-17T07:03:02.2742080Z 6f5ba5923d9e: Waiting 2025-07-17T07:03:02.2742334Z 287d90495ed7: Pulling fs layer 2025-07-17T07:03:02.2742644Z 1bd9396864e4: Waiting 2025-07-17T07:03:02.2742985Z e1da75f4dceb: Pulling fs layer 2025-07-17T07:03:02.2743263Z cc5ad5bb5c8f: Waiting 2025-07-17T07:03:02.2743505Z 4f4fb700ef54: Waiting 2025-07-17T07:03:02.2743737Z 287d90495ed7: Waiting 2025-07-17T07:03:02.2744058Z dbbbaf55f1bc: Pulling fs layer 2025-07-17T07:03:02.2744357Z b5993da49da4: Pulling fs layer 2025-07-17T07:03:02.2744718Z 13afcd2a66bb: Pulling fs layer 2025-07-17T07:03:02.2745069Z 58af60b83765: Pulling fs layer 2025-07-17T07:03:02.2745351Z 696aad357da7: Pulling fs layer 2025-07-17T07:03:02.2745618Z e5249a336770: Pulling fs layer 2025-07-17T07:03:02.2746013Z 8d76da75d1af: Pulling fs layer 2025-07-17T07:03:02.2746288Z dbbbaf55f1bc: Waiting 2025-07-17T07:03:02.2746815Z 95145717af0c: Pulling fs layer 2025-07-17T07:03:02.2747089Z 13afcd2a66bb: Waiting 2025-07-17T07:03:02.2747377Z b5993da49da4: Waiting 2025-07-17T07:03:02.2747619Z e5249a336770: Waiting 2025-07-17T07:03:02.2747903Z 58af60b83765: Waiting 2025-07-17T07:03:02.2748223Z 696aad357da7: Waiting 2025-07-17T07:03:02.2748481Z f66e02cad216: Pulling fs layer 2025-07-17T07:03:02.2748814Z 23bfc6bfeaf4: Pulling fs layer 2025-07-17T07:03:02.2749166Z 8d76da75d1af: Waiting 2025-07-17T07:03:02.2749421Z 714df0485f2f: Pulling fs layer 2025-07-17T07:03:02.2749715Z 95145717af0c: Waiting 2025-07-17T07:03:02.2750210Z 4fe817dc2597: Pulling fs layer 2025-07-17T07:03:02.2750717Z f66e02cad216: Waiting 2025-07-17T07:03:02.2750978Z 23bfc6bfeaf4: Waiting 2025-07-17T07:03:02.2751219Z 714df0485f2f: Waiting 2025-07-17T07:03:02.2751557Z 8b772aad6dc1: Pulling fs layer 2025-07-17T07:03:02.2751832Z 5eec907873a0: Pulling fs layer 2025-07-17T07:03:02.2752234Z 4fe817dc2597: Waiting 2025-07-17T07:03:02.2752494Z f5b31abb16c4: Pulling fs layer 2025-07-17T07:03:02.2752758Z 8b772aad6dc1: Waiting 2025-07-17T07:03:02.2753222Z da73c7805e85: Pulling fs layer 2025-07-17T07:03:02.2753735Z 5eec907873a0: Waiting 2025-07-17T07:03:02.2754002Z a9fc0454e936: Pulling fs layer 2025-07-17T07:03:02.2754284Z f5b31abb16c4: Waiting 2025-07-17T07:03:02.2754591Z da73c7805e85: Waiting 2025-07-17T07:03:02.2755011Z fdda510353fb: Pulling fs layer 2025-07-17T07:03:02.2755375Z 72f42db112ac: Pulling fs layer 2025-07-17T07:03:02.2755656Z a9fc0454e936: Waiting 2025-07-17T07:03:02.2755895Z 7c952e9bce00: Pulling fs layer 2025-07-17T07:03:02.2756238Z 72f42db112ac: Waiting 2025-07-17T07:03:02.2756525Z 7c952e9bce00: Waiting 2025-07-17T07:03:02.2756893Z 3b1502de0f3b: Pulling fs layer 2025-07-17T07:03:02.2757188Z 173b45b41ce0: Pulling fs layer 2025-07-17T07:03:02.2757500Z 50399975739a: Pulling fs layer 2025-07-17T07:03:02.2757935Z 34b7cc5cf1d9: Pulling fs layer 2025-07-17T07:03:02.2758337Z 173b45b41ce0: Waiting 2025-07-17T07:03:02.2758750Z dffea587205d: Pulling fs layer 2025-07-17T07:03:02.2759083Z 50399975739a: Waiting 2025-07-17T07:03:02.2759333Z 34b7cc5cf1d9: Waiting 2025-07-17T07:03:02.2759600Z 8d04c6fef71e: Pulling fs layer 2025-07-17T07:03:02.2759886Z 3b1502de0f3b: Waiting 2025-07-17T07:03:02.2760410Z 56cdce5d9342: Pulling fs layer 2025-07-17T07:03:02.2760676Z dffea587205d: Waiting 2025-07-17T07:03:02.2760917Z 8d04c6fef71e: Waiting 2025-07-17T07:03:02.2761245Z 56cdce5d9342: Waiting 2025-07-17T07:03:02.2761521Z 060e0a231913: Pulling fs layer 2025-07-17T07:03:02.2761947Z 3c6a2d65b5bb: Pulling fs layer 2025-07-17T07:03:02.2762331Z a7015d1f229e: Pulling fs layer 2025-07-17T07:03:02.2762651Z 0ddb9567cfa9: Pulling fs layer 2025-07-17T07:03:02.2762976Z 08123ea660cb: Pulling fs layer 2025-07-17T07:03:02.2763249Z 3c6a2d65b5bb: Waiting 2025-07-17T07:03:02.2763541Z 060e0a231913: Waiting 2025-07-17T07:03:02.2763791Z 06f07ca145d9: Pulling fs layer 2025-07-17T07:03:02.2764075Z a151adebebbf: Pulling fs layer 2025-07-17T07:03:02.2764335Z a7015d1f229e: Waiting 2025-07-17T07:03:02.2764577Z 0ddb9567cfa9: Waiting 2025-07-17T07:03:02.2764998Z 06f07ca145d9: Waiting 2025-07-17T07:03:02.2765263Z 08123ea660cb: Waiting 2025-07-17T07:03:02.2765716Z a567163437c5: Pulling fs layer 2025-07-17T07:03:02.2766148Z f70d840f7624: Pulling fs layer 2025-07-17T07:03:02.2766423Z d7369ebc3a9a: Pulling fs layer 2025-07-17T07:03:02.2766777Z 4184c6a7fd64: Pulling fs layer 2025-07-17T07:03:02.2767075Z 22ddb070c111: Pulling fs layer 2025-07-17T07:03:02.2767379Z a151adebebbf: Waiting 2025-07-17T07:03:02.2767645Z a567163437c5: Waiting 2025-07-17T07:03:02.2767892Z e4b9b40818eb: Pulling fs layer 2025-07-17T07:03:02.2768263Z f70d840f7624: Waiting 2025-07-17T07:03:02.2768502Z 403c8a0d6000: Pulling fs layer 2025-07-17T07:03:02.2768774Z 22ddb070c111: Waiting 2025-07-17T07:03:02.2769153Z e4b9b40818eb: Waiting 2025-07-17T07:03:02.2769387Z 4184c6a7fd64: Waiting 2025-07-17T07:03:02.2769637Z 6ce29e0f73ef: Pulling fs layer 2025-07-17T07:03:02.2770266Z 8341c69d63c8: Pulling fs layer 2025-07-17T07:03:02.2770717Z 9fb68e35f66f: Pulling fs layer 2025-07-17T07:03:02.2771063Z 403c8a0d6000: Waiting 2025-07-17T07:03:02.2771307Z 6ce29e0f73ef: Waiting 2025-07-17T07:03:02.2771605Z 8341c69d63c8: Waiting 2025-07-17T07:03:02.2771847Z 9fb68e35f66f: Waiting 2025-07-17T07:03:02.3364764Z 7a5c9899d937: Verifying Checksum 2025-07-17T07:03:02.3365150Z 7a5c9899d937: Download complete 2025-07-17T07:03:02.4124328Z 4ea72d4d995b: Verifying Checksum 2025-07-17T07:03:02.4124733Z 4ea72d4d995b: Download complete 2025-07-17T07:03:02.6211551Z 66587c81b81a: Download complete 2025-07-17T07:03:02.6966771Z ff0141e78db7: Verifying Checksum 2025-07-17T07:03:02.6967304Z ff0141e78db7: Download complete 2025-07-17T07:03:02.7700259Z a8aa8a9fa61b: Verifying Checksum 2025-07-17T07:03:02.7700887Z a8aa8a9fa61b: Download complete 2025-07-17T07:03:02.8422752Z a1030ae92635: Verifying Checksum 2025-07-17T07:03:02.8423307Z a1030ae92635: Download complete 2025-07-17T07:03:02.9131756Z 1bd9396864e4: Verifying Checksum 2025-07-17T07:03:02.9132187Z 1bd9396864e4: Download complete 2025-07-17T07:03:02.9769181Z e80da71796c5: Download complete 2025-07-17T07:03:03.0500747Z c0c195959436: Download complete 2025-07-17T07:03:03.1063752Z 0b21d3c7919b: Verifying Checksum 2025-07-17T07:03:03.1064790Z 0b21d3c7919b: Download complete 2025-07-17T07:03:03.1540908Z c3fd79404829: Verifying Checksum 2025-07-17T07:03:03.1541439Z c3fd79404829: Download complete 2025-07-17T07:03:03.1649568Z 6f5ba5923d9e: Download complete 2025-07-17T07:03:03.1704711Z 4f4fb700ef54: Verifying Checksum 2025-07-17T07:03:03.1705160Z 4f4fb700ef54: Download complete 2025-07-17T07:03:03.2352520Z 287d90495ed7: Verifying Checksum 2025-07-17T07:03:03.2353193Z 287d90495ed7: Download complete 2025-07-17T07:03:03.3151239Z e1da75f4dceb: Verifying Checksum 2025-07-17T07:03:03.3151721Z e1da75f4dceb: Download complete 2025-07-17T07:03:03.4417042Z dbbbaf55f1bc: Verifying Checksum 2025-07-17T07:03:03.4418021Z dbbbaf55f1bc: Download complete 2025-07-17T07:03:03.5569937Z b5993da49da4: Verifying Checksum 2025-07-17T07:03:03.5570583Z b5993da49da4: Download complete 2025-07-17T07:03:03.5625077Z 66587c81b81a: Pull complete 2025-07-17T07:03:03.5839686Z 7a5c9899d937: Pull complete 2025-07-17T07:03:03.6331162Z 13afcd2a66bb: Verifying Checksum 2025-07-17T07:03:03.6331744Z 13afcd2a66bb: Download complete 2025-07-17T07:03:03.7166449Z 58af60b83765: Download complete 2025-07-17T07:03:03.7982222Z 696aad357da7: Verifying Checksum 2025-07-17T07:03:03.7983005Z 696aad357da7: Download complete 2025-07-17T07:03:03.8630655Z e5249a336770: Verifying Checksum 2025-07-17T07:03:03.8631090Z e5249a336770: Download complete 2025-07-17T07:03:03.9549382Z 8d76da75d1af: Verifying Checksum 2025-07-17T07:03:03.9549786Z 8d76da75d1af: Download complete 2025-07-17T07:03:04.0517167Z 95145717af0c: Download complete 2025-07-17T07:03:04.1273649Z f66e02cad216: Verifying Checksum 2025-07-17T07:03:04.1274215Z f66e02cad216: Download complete 2025-07-17T07:03:04.1875721Z 23bfc6bfeaf4: Verifying Checksum 2025-07-17T07:03:04.1876175Z 23bfc6bfeaf4: Download complete 2025-07-17T07:03:05.7609992Z 9d8fe31f4371: Verifying Checksum 2025-07-17T07:03:05.7610538Z 9d8fe31f4371: Download complete 2025-07-17T07:03:05.8223951Z 4fe817dc2597: Download complete 2025-07-17T07:03:05.8907220Z 8b772aad6dc1: Verifying Checksum 2025-07-17T07:03:05.8907801Z 8b772aad6dc1: Download complete 2025-07-17T07:03:05.9737715Z 5eec907873a0: Verifying Checksum 2025-07-17T07:03:05.9738389Z 5eec907873a0: Download complete 2025-07-17T07:03:06.0621753Z f5b31abb16c4: Download complete 2025-07-17T07:03:06.3177227Z da73c7805e85: Verifying Checksum 2025-07-17T07:03:06.3177854Z da73c7805e85: Download complete 2025-07-17T07:03:06.3885246Z a9fc0454e936: Verifying Checksum 2025-07-17T07:03:06.3885884Z a9fc0454e936: Download complete 2025-07-17T07:03:06.4909301Z fdda510353fb: Verifying Checksum 2025-07-17T07:03:06.4909747Z fdda510353fb: Download complete 2025-07-17T07:03:06.5706705Z 72f42db112ac: Verifying Checksum 2025-07-17T07:03:06.5707399Z 72f42db112ac: Download complete 2025-07-17T07:03:06.6803820Z 7c952e9bce00: Download complete 2025-07-17T07:03:06.7620133Z 3b1502de0f3b: Download complete 2025-07-17T07:03:06.8367010Z 173b45b41ce0: Verifying Checksum 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2025-07-17T07:04:54.5957918Z 8341c69d63c8: Pull complete 2025-07-17T07:04:56.4562668Z 9fb68e35f66f: Pull complete 2025-07-17T07:04:56.5332757Z Digest: sha256:298ca350eaba018a1adf58a70fad4c1b682d6f0738c0f0b4a6d27f040d02eb09 2025-07-17T07:04:56.5369115Z Status: Downloaded newer image for 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:04:56.5469346Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:04:56.5518765Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-07-17T07:04:56.5519808Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-07-17T07:04:56.5527613Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:04:56.5527993Z env: 2025-07-17T07:04:56.5528219Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:04:56.5528534Z ##[endgroup] 2025-07-17T07:04:56.5699136Z Prepare all required actions 2025-07-17T07:04:56.5737912Z ##[group]Run ./.github/actions/get-workflow-job-id 2025-07-17T07:04:56.5738272Z with: 2025-07-17T07:04:56.5738876Z github-token: *** 2025-07-17T07:04:56.5739097Z env: 2025-07-17T07:04:56.5739313Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:04:56.5739576Z ##[endgroup] 2025-07-17T07:04:56.5763321Z ##[group]Run set -eux 2025-07-17T07:04:56.5763599Z set -eux 2025-07-17T07:04:56.5764052Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-07-17T07:04:56.5770302Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:04:56.5770696Z env: 2025-07-17T07:04:56.5770920Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:04:56.5771356Z GITHUB_TOKEN: *** 2025-07-17T07:04:56.5771583Z ##[endgroup] 2025-07-17T07:04:56.5797142Z + python3 .github/scripts/get_workflow_job_id.py 16337959907 i-00d4fcac0f1d6282f 2025-07-17T07:04:58.6611487Z Setting output job-id=46154839619 2025-07-17T07:04:58.6612196Z Setting output job-name=linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T07:04:58.6795729Z ##[group]Run python3 -m pip install psutil==5.9.1 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-07-17T07:04:58.6796506Z python3 -m pip install psutil==5.9.1 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-07-17T07:04:58.6797499Z python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 & 2025-07-17T07:04:58.6798516Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}" 2025-07-17T07:04:58.6805666Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:04:58.6806061Z env: 2025-07-17T07:04:58.6806283Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:04:58.6806539Z JOB_ID: 46154839619 2025-07-17T07:04:58.6806951Z JOB_NAME: linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T07:04:58.6807434Z WORKFLOW_NAME: pull 2025-07-17T07:04:58.6807693Z WORKFLOW_RUN_ID: 16337959907 2025-07-17T07:04:58.6808018Z MONITOR_LOG_INTERVAL: 5 2025-07-17T07:04:58.6808287Z MONITOR_DATA_COLLECT_INTERVAL: 1 2025-07-17T07:04:58.6808584Z ##[endgroup] 2025-07-17T07:04:59.7215296Z Defaulting to user installation because normal site-packages is not writeable 2025-07-17T07:05:00.2460050Z Collecting psutil==5.9.1 2025-07-17T07:05:00.2616549Z Downloading psutil-5.9.1-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (281 kB) 2025-07-17T07:05:00.4047132Z Collecting dataclasses_json==0.6.7 2025-07-17T07:05:00.4078500Z Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB) 2025-07-17T07:05:00.4498848Z Collecting nvidia-ml-py==11.525.84 2025-07-17T07:05:00.4531322Z Downloading nvidia_ml_py-11.525.84-py3-none-any.whl (34 kB) 2025-07-17T07:05:00.5376534Z Collecting typing-inspect<1,>=0.4.0 2025-07-17T07:05:00.5406725Z Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB) 2025-07-17T07:05:00.6901671Z Collecting marshmallow<4.0.0,>=3.18.0 2025-07-17T07:05:00.6932427Z Downloading marshmallow-3.26.1-py3-none-any.whl (50 kB) 2025-07-17T07:05:00.7927995Z Collecting packaging>=17.0 2025-07-17T07:05:00.7958922Z Downloading packaging-25.0-py3-none-any.whl (66 kB) 2025-07-17T07:05:00.8920716Z Collecting typing-extensions>=3.7.4 2025-07-17T07:05:00.8960351Z Downloading typing_extensions-4.14.1-py3-none-any.whl (43 kB) 2025-07-17T07:05:00.9509235Z Collecting mypy-extensions>=0.3.0 2025-07-17T07:05:00.9539975Z Downloading mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB) 2025-07-17T07:05:01.1928736Z Installing collected packages: typing-extensions, packaging, mypy-extensions, typing-inspect, marshmallow, psutil, nvidia-ml-py, dataclasses-json 2025-07-17T07:05:01.7027934Z Successfully installed dataclasses-json-0.6.7 marshmallow-3.26.1 mypy-extensions-1.1.0 nvidia-ml-py-11.525.84 packaging-25.0 psutil-5.9.1 typing-extensions-4.14.1 typing-inspect-0.9.0 2025-07-17T07:05:01.9569360Z Prepare all required actions 2025-07-17T07:05:01.9569778Z Getting action download info 2025-07-17T07:05:02.1128837Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6) 2025-07-17T07:05:02.6378905Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093) 2025-07-17T07:05:05.3111946Z ##[group]Run ./.github/actions/download-build-artifacts 2025-07-17T07:05:05.3112308Z with: 2025-07-17T07:05:05.3112543Z name: linux-jammy-py3.13-clang12 2025-07-17T07:05:05.3112869Z s3-bucket: gha-artifacts 2025-07-17T07:05:05.3113116Z env: 2025-07-17T07:05:05.3113327Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:05.3113586Z ##[endgroup] 2025-07-17T07:05:05.3263534Z ##[group]Run seemethere/download-artifact-s3@v4 2025-07-17T07:05:05.3263881Z with: 2025-07-17T07:05:05.3264102Z name: linux-jammy-py3.13-clang12 2025-07-17T07:05:05.3264413Z s3-bucket: gha-artifacts 2025-07-17T07:05:05.3264727Z region: us-east-1 2025-07-17T07:05:05.3264957Z env: 2025-07-17T07:05:05.3265153Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:05.3265416Z ##[endgroup] 2025-07-17T07:05:06.0581051Z (node:42698) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-07-17T07:05:06.0581587Z 2025-07-17T07:05:06.0581785Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-07-17T07:05:06.0582350Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-07-17T07:05:06.0582917Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-07-17T07:05:07.5728808Z Found 1 objects with prefix pytorch/pytorch/16337959907/linux-jammy-py3.13-clang12/ 2025-07-17T07:05:07.5729579Z Starting download (1/1): 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main 2025-07-17T07:05:21.5593097Z ##[endgroup] 2025-07-17T07:05:21.5835427Z Filesystem Size Used Avail Use% Mounted on 2025-07-17T07:05:21.5835855Z devtmpfs 4.2M 0 4.2M 0% /dev 2025-07-17T07:05:21.5836227Z tmpfs 8.2G 0 8.2G 0% /dev/shm 2025-07-17T07:05:21.5836572Z tmpfs 3.3G 488k 3.3G 1% /run 2025-07-17T07:05:21.5836949Z /dev/nvme0n1p1 161G 27G 135G 17% / 2025-07-17T07:05:21.5837265Z tmpfs 8.2G 13k 8.2G 1% /tmp 2025-07-17T07:05:21.5837863Z /dev/nvme0n1p128 11M 1.4M 9.2M 13% /boot/efi 2025-07-17T07:05:21.5907493Z Prepare all required actions 2025-07-17T07:05:21.5908324Z Getting action download info 2025-07-17T07:05:21.7371102Z ##[group]Run ./.github/actions/download-td-artifacts 2025-07-17T07:05:21.7371491Z with: 2025-07-17T07:05:21.7371721Z env: 2025-07-17T07:05:21.7371963Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:21.7372212Z ##[endgroup] 2025-07-17T07:05:21.7491897Z ##[group]Run seemethere/download-artifact-s3@v4 2025-07-17T07:05:21.7492254Z with: 2025-07-17T07:05:21.7492471Z name: td_results 2025-07-17T07:05:21.7492701Z s3-bucket: gha-artifacts 2025-07-17T07:05:21.7492972Z region: us-east-1 2025-07-17T07:05:21.7493199Z env: 2025-07-17T07:05:21.7493400Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:21.7493664Z ##[endgroup] 2025-07-17T07:05:22.2054686Z (node:42719) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-07-17T07:05:22.2055545Z 2025-07-17T07:05:22.2055966Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-07-17T07:05:22.2056944Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-07-17T07:05:22.2057936Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-07-17T07:05:22.3002544Z Found 1 objects with prefix pytorch/pytorch/16337959907/td_results/ 2025-07-17T07:05:22.3003689Z Starting download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/td_results.json 2025-07-17T07:05:22.3806396Z Finished download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/td_results.json 2025-07-17T07:05:22.3812702Z Artifact download has finished successfully 2025-07-17T07:05:22.4110512Z ##[group]Run mkdir -p .additional_ci_files 2025-07-17T07:05:22.4110892Z mkdir -p .additional_ci_files 2025-07-17T07:05:22.4111335Z mv td_results.json .additional_ci_files/td_results.json || true 2025-07-17T07:05:22.4118002Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:05:22.4118396Z env: 2025-07-17T07:05:22.4118640Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:22.4118895Z ##[endgroup] 2025-07-17T07:05:22.4505090Z ##[group]Run .github/scripts/parse_ref.py 2025-07-17T07:05:22.4505486Z .github/scripts/parse_ref.py 2025-07-17T07:05:22.4512310Z shell: /usr/bin/bash -e {0} 2025-07-17T07:05:22.4512596Z env: 2025-07-17T07:05:22.4512976Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:22.4513228Z ##[endgroup] 2025-07-17T07:05:22.4981807Z Setting output branch=main 2025-07-17T07:05:22.5121280Z Prepare all required actions 2025-07-17T07:05:22.5121699Z Getting action download info 2025-07-17T07:05:22.6374525Z ##[group]Run ./.github/actions/filter-test-configs 2025-07-17T07:05:22.6374888Z with: 2025-07-17T07:05:22.6375287Z github-token: *** 2025-07-17T07:05:22.6378213Z test-matrix: {"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "linux.2xlarge"}]} 2025-07-17T07:05:22.6381334Z job-name: linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T07:05:22.6381816Z env: 2025-07-17T07:05:22.6382022Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:22.6382296Z ##[endgroup] 2025-07-17T07:05:22.6495137Z ##[group]Run nick-fields/retry@v3.0.0 2025-07-17T07:05:22.6495455Z with: 2025-07-17T07:05:22.6495659Z shell: bash 2025-07-17T07:05:22.6495886Z timeout_minutes: 10 2025-07-17T07:05:22.6496133Z max_attempts: 5 2025-07-17T07:05:22.6496362Z retry_wait_seconds: 30 2025-07-17T07:05:22.6497177Z command: set -eux # PyYAML 6.0 doesn't work with MacOS x86 anymore # This must run on Python-3.7 (AmazonLinux2) so can't use request=3.32.2 python3 -m pip install requests==2.27.1 pyyaml==6.0.1 2025-07-17T07:05:22.6498060Z polling_interval_seconds: 1 2025-07-17T07:05:22.6498344Z warning_on_retry: true 2025-07-17T07:05:22.6498596Z continue_on_error: false 2025-07-17T07:05:22.6498851Z env: 2025-07-17T07:05:22.6499061Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:22.6499500Z GITHUB_TOKEN: *** 2025-07-17T07:05:22.6499719Z ##[endgroup] 2025-07-17T07:05:22.8373878Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.1 2025-07-17T07:05:23.0760928Z Defaulting to user installation because normal site-packages is not writeable 2025-07-17T07:05:23.2285058Z Collecting requests==2.27.1 2025-07-17T07:05:23.2434784Z Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB) 2025-07-17T07:05:23.4005238Z Collecting pyyaml==6.0.1 2025-07-17T07:05:23.4044726Z Downloading PyYAML-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (738 kB) 2025-07-17T07:05:23.4276031Z Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3.9/site-packages (from requests==2.27.1) (1.25.10) 2025-07-17T07:05:23.4723777Z Collecting certifi>=2017.4.17 2025-07-17T07:05:23.4756539Z Downloading certifi-2025.7.14-py3-none-any.whl (162 kB) 2025-07-17T07:05:23.4828238Z Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3.9/site-packages (from requests==2.27.1) (2.10) 2025-07-17T07:05:23.8041661Z Collecting charset-normalizer~=2.0.0 2025-07-17T07:05:23.8076584Z Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB) 2025-07-17T07:05:23.8948541Z Installing collected packages: charset-normalizer, certifi, requests, pyyaml 2025-07-17T07:05:24.0147965Z Successfully installed certifi-2025.7.14 charset-normalizer-2.0.12 pyyaml-6.0.1 requests-2.27.1 2025-07-17T07:05:24.7264746Z Command completed after 1 attempt(s). 2025-07-17T07:05:24.7321925Z ##[group]Run set -x 2025-07-17T07:05:24.7322199Z set -x 2025-07-17T07:05:24.7322429Z  2025-07-17T07:05:24.7322803Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-07-17T07:05:24.7323447Z # in runner workspace 2025-07-17T07:05:24.7323992Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py" 2025-07-17T07:05:24.7330267Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:05:24.7330641Z env: 2025-07-17T07:05:24.7330863Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:24.7331130Z ##[endgroup] 2025-07-17T07:05:24.7357145Z + python3 /home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py 2025-07-17T07:05:24.7537699Z Setting output branch=main 2025-07-17T07:05:24.7597757Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}" 2025-07-17T07:05:24.7598185Z echo "Workflow: ${GITHUB_WORKFLOW}" 2025-07-17T07:05:24.7598519Z echo "Job name: ${JOB_NAME}" 2025-07-17T07:05:24.7598822Z  2025-07-17T07:05:24.7599209Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-07-17T07:05:24.7599721Z # in runner workspace 2025-07-17T07:05:24.7600162Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \ 2025-07-17T07:05:24.7600653Z  --workflow "${GITHUB_WORKFLOW}" \ 2025-07-17T07:05:24.7600993Z  --job-name "${JOB_NAME}" \ 2025-07-17T07:05:24.7603943Z  --test-matrix "{"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "linux.2xlarge"}]}" \ 2025-07-17T07:05:24.7607011Z  --selected-test-configs "" \ 2025-07-17T07:05:24.7607359Z  --pr-number "${PR_NUMBER}" \ 2025-07-17T07:05:24.7607674Z  --tag "${TAG}" \ 2025-07-17T07:05:24.7607978Z  --event-name "${EVENT_NAME}" \ 2025-07-17T07:05:24.7608315Z  --schedule "${SCHEDULE}" \ 2025-07-17T07:05:24.7608621Z  --branch "${HEAD_BRANCH}" 2025-07-17T07:05:24.7615018Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:05:24.7615407Z env: 2025-07-17T07:05:24.7615614Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:24.7616117Z GITHUB_TOKEN: *** 2025-07-17T07:05:24.7616530Z JOB_NAME: linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T07:05:24.7617030Z PR_NUMBER: 2025-07-17T07:05:24.7617240Z TAG: 2025-07-17T07:05:24.7617469Z EVENT_NAME: push 2025-07-17T07:05:24.7617714Z SCHEDULE: 2025-07-17T07:05:24.7617919Z HEAD_BRANCH: main 2025-07-17T07:05:24.7618150Z ##[endgroup] 2025-07-17T07:05:24.7642221Z Workflow: pull 2025-07-17T07:05:24.7642666Z Job name: linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T07:05:24.9583500Z Setting output keep-going=True 2025-07-17T07:05:24.9584209Z Setting output ci-verbose-test-logs=False 2025-07-17T07:05:24.9584933Z Setting output ci-test-showlocals=False 2025-07-17T07:05:24.9585643Z Setting output ci-no-test-timeout=False 2025-07-17T07:05:24.9586282Z Setting output ci-no-td=False 2025-07-17T07:05:24.9586893Z Setting output ci-td-distributed=False 2025-07-17T07:05:24.9587557Z Setting output is-unstable=False 2025-07-17T07:05:24.9588174Z Setting output reenabled-issues= 2025-07-17T07:05:24.9595482Z Setting output test-matrix={"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "linux.2xlarge"}]} 2025-07-17T07:05:24.9601361Z Setting output is-test-matrix-empty=False 2025-07-17T07:05:24.9733797Z ##[group]Run echo "Filtered matrix:" 2025-07-17T07:05:24.9734182Z echo "Filtered matrix:" 2025-07-17T07:05:24.9737130Z echo "{"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "linux.2xlarge"}]}" 2025-07-17T07:05:24.9740033Z  2025-07-17T07:05:24.9740242Z echo 2025-07-17T07:05:24.9740511Z echo "Is the current job unstable? False" 2025-07-17T07:05:24.9740853Z  2025-07-17T07:05:24.9741059Z echo 2025-07-17T07:05:24.9741303Z echo "Is keep-going label set? True" 2025-07-17T07:05:24.9741626Z  2025-07-17T07:05:24.9741828Z echo 2025-07-17T07:05:24.9742048Z echo "Reenabled issues? " 2025-07-17T07:05:24.9748000Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:05:24.9748399Z env: 2025-07-17T07:05:24.9748607Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:24.9748871Z ##[endgroup] 2025-07-17T07:05:24.9772659Z Filtered matrix: 2025-07-17T07:05:24.9776984Z {include: [{config: default, shard: 1, num_shards: 5, runner: linux.4xlarge}, {config: default, shard: 2, num_shards: 5, runner: linux.4xlarge}, {config: default, shard: 3, num_shards: 5, runner: linux.4xlarge}, {config: default, shard: 4, num_shards: 5, runner: linux.4xlarge}, {config: default, shard: 5, num_shards: 5, runner: linux.4xlarge}, {config: crossref, shard: 1, num_shards: 2, runner: linux.2xlarge}, {config: crossref, shard: 2, num_shards: 2, runner: linux.2xlarge}, {config: dynamo_wrapped, shard: 1, num_shards: 3, runner: linux.2xlarge}, {config: dynamo_wrapped, shard: 2, num_shards: 3, runner: linux.2xlarge}, {config: dynamo_wrapped, shard: 3, num_shards: 3, runner: linux.2xlarge}, {config: einops, shard: 1, num_shards: 1, runner: linux.2xlarge}]} 2025-07-17T07:05:24.9779739Z 2025-07-17T07:05:24.9779862Z Is the current job unstable? False 2025-07-17T07:05:24.9780081Z 2025-07-17T07:05:24.9780187Z Is keep-going label set? True 2025-07-17T07:05:24.9780372Z 2025-07-17T07:05:24.9780476Z Reenabled issues? 2025-07-17T07:05:24.9847005Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-07-17T07:05:24.9847543Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-07-17T07:05:24.9853028Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:05:24.9853538Z env: 2025-07-17T07:05:24.9853766Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:24.9854038Z JOB_TIMEOUT: 600 2025-07-17T07:05:24.9854261Z ##[endgroup] 2025-07-17T07:05:24.9909662Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-07-17T07:05:24.9910196Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-07-17T07:05:24.9910652Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-07-17T07:05:24.9916045Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T07:05:24.9916429Z env: 2025-07-17T07:05:24.9916645Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:24.9916898Z ##[endgroup] 2025-07-17T07:05:25.0017938Z ##[group]Run set -x 2025-07-17T07:05:25.0018286Z set -x 2025-07-17T07:05:25.0018501Z  2025-07-17T07:05:25.0018811Z if [[ $TEST_CONFIG == 'multigpu' ]]; then 2025-07-17T07:05:25.0019339Z  TEST_COMMAND=.ci/pytorch/multigpu-test.sh 2025-07-17T07:05:25.0019753Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then 2025-07-17T07:05:25.0020126Z  TEST_COMMAND=.ci/onnx/test.sh 2025-07-17T07:05:25.0020436Z else 2025-07-17T07:05:25.0020691Z  TEST_COMMAND=.ci/pytorch/test.sh 2025-07-17T07:05:25.0020997Z fi 2025-07-17T07:05:25.0021231Z  2025-07-17T07:05:25.0021507Z # Leaving 1GB for the runner and other things 2025-07-17T07:05:25.0022097Z TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo) 2025-07-17T07:05:25.0023007Z # https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap 2025-07-17T07:05:25.0023788Z # comes from https://github.com/pytorch/test-infra/pull/6058 2025-07-17T07:05:25.0024325Z TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3)) 2025-07-17T07:05:25.0024774Z  2025-07-17T07:05:25.0025039Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-07-17T07:05:25.0025403Z  SHM_OPTS= 2025-07-17T07:05:25.0025673Z  JENKINS_USER= 2025-07-17T07:05:25.0026096Z  # ensure that docker container cleanly exits in 12 hours 2025-07-17T07:05:25.0026598Z  # if for some reason cleanup action doesn't stop container 2025-07-17T07:05:25.0027012Z  # when job is cancelled 2025-07-17T07:05:25.0027336Z  DOCKER_SHELL_CMD="sleep 12h" 2025-07-17T07:05:25.0027634Z else 2025-07-17T07:05:25.0027893Z  SHM_OPTS="--shm-size=${SHM_SIZE}" 2025-07-17T07:05:25.0028244Z  JENKINS_USER="--user jenkins" 2025-07-17T07:05:25.0028559Z  DOCKER_SHELL_CMD= 2025-07-17T07:05:25.0028829Z fi 2025-07-17T07:05:25.0029047Z  2025-07-17T07:05:25.0029384Z # detached container should get cleaned up by teardown_ec2_linux 2025-07-17T07:05:25.0029936Z # TODO: Stop building test binaries as part of the build phase 2025-07-17T07:05:25.0030570Z # Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice 2025-07-17T07:05:25.0031123Z # shellcheck disable=SC2086,SC2090 2025-07-17T07:05:25.0031456Z container_name=$(docker run \ 2025-07-17T07:05:25.0031771Z  ${GPU_FLAG:-} \ 2025-07-17T07:05:25.0032079Z  ${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \ 2025-07-17T07:05:25.0032421Z  -e BUILD_ENVIRONMENT \ 2025-07-17T07:05:25.0032754Z  -e PR_NUMBER \ 2025-07-17T07:05:25.0033028Z  -e GITHUB_ACTIONS \ 2025-07-17T07:05:25.0033320Z  -e GITHUB_REPOSITORY \ 2025-07-17T07:05:25.0033629Z  -e GITHUB_WORKFLOW \ 2025-07-17T07:05:25.0033916Z  -e GITHUB_JOB \ 2025-07-17T07:05:25.0034194Z  -e GITHUB_RUN_ID \ 2025-07-17T07:05:25.0034471Z  -e GITHUB_RUN_NUMBER \ 2025-07-17T07:05:25.0034771Z  -e GITHUB_RUN_ATTEMPT \ 2025-07-17T07:05:25.0035242Z  -e JOB_ID \ 2025-07-17T07:05:25.0035532Z  -e JOB_NAME \ 2025-07-17T07:05:25.0035787Z  -e BASE_SHA \ 2025-07-17T07:05:25.0036044Z  -e BRANCH \ 2025-07-17T07:05:25.0036282Z  -e SHA1 \ 2025-07-17T07:05:25.0036537Z  -e AWS_DEFAULT_REGION \ 2025-07-17T07:05:25.0036833Z  -e IN_WHEEL_TEST \ 2025-07-17T07:05:25.0037115Z  -e SHARD_NUMBER \ 2025-07-17T07:05:25.0037380Z  -e TEST_CONFIG \ 2025-07-17T07:05:25.0037657Z  -e NUM_TEST_SHARDS \ 2025-07-17T07:05:25.0037946Z  -e REENABLED_ISSUES \ 2025-07-17T07:05:25.0038243Z  -e CONTINUE_THROUGH_ERROR \ 2025-07-17T07:05:25.0038654Z  -e VERBOSE_TEST_LOGS \ 2025-07-17T07:05:25.0038960Z  -e TEST_SHOWLOCALS \ 2025-07-17T07:05:25.0039241Z  -e NO_TEST_TIMEOUT \ 2025-07-17T07:05:25.0039525Z  -e NO_TD \ 2025-07-17T07:05:25.0039786Z  -e TD_DISTRIBUTED \ 2025-07-17T07:05:25.0040079Z  -e PR_LABELS \ 2025-07-17T07:05:25.0040369Z  -e MAX_JOBS="$(nproc --ignore=2)" \ 2025-07-17T07:05:25.0040716Z  -e SCCACHE_BUCKET \ 2025-07-17T07:05:25.0041009Z  -e SCCACHE_REGION \ 2025-07-17T07:05:25.0041279Z  -e XLA_CUDA \ 2025-07-17T07:05:25.0041571Z  -e XLA_CLANG_CACHE_S3_BUCKET_NAME \ 2025-07-17T07:05:25.0041940Z  -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \ 2025-07-17T07:05:25.0042303Z  -e PYTORCH_TEST_RERUN_DISABLED_TESTS \ 2025-07-17T07:05:25.0042686Z  -e SKIP_SCCACHE_INITIALIZATION=1 \ 2025-07-17T07:05:25.0043032Z  -e HUGGING_FACE_HUB_TOKEN \ 2025-07-17T07:05:25.0043373Z  -e SCRIBE_GRAPHQL_ACCESS_TOKEN \ 2025-07-17T07:05:25.0043693Z  -e DASHBOARD_TAG \ 2025-07-17T07:05:25.0043984Z  -e ARTIFACTS_FILE_SUFFIX \ 2025-07-17T07:05:25.0044355Z  --memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \ 2025-07-17T07:05:25.0044769Z  --memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \ 2025-07-17T07:05:25.0045276Z  --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \ 2025-07-17T07:05:25.0045685Z  --security-opt seccomp=unconfined \ 2025-07-17T07:05:25.0046037Z  --cap-add=SYS_PTRACE \ 2025-07-17T07:05:25.0046323Z  --ipc=host \ 2025-07-17T07:05:25.0046585Z  ${SHM_OPTS} \ 2025-07-17T07:05:25.0046844Z  --tty \ 2025-07-17T07:05:25.0047069Z  --detach \ 2025-07-17T07:05:25.0047335Z  --name="${container_name}" \ 2025-07-17T07:05:25.0047657Z  ${JENKINS_USER} \ 2025-07-17T07:05:25.0048001Z  -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \ 2025-07-17T07:05:25.0048410Z  -w /var/lib/jenkins/workspace \ 2025-07-17T07:05:25.0048730Z  "${DOCKER_IMAGE}" \ 2025-07-17T07:05:25.0048999Z  ${DOCKER_SHELL_CMD} 2025-07-17T07:05:25.0049266Z ) 2025-07-17T07:05:25.0049552Z # Propagate download.pytorch.org IP to container 2025-07-17T07:05:25.0050234Z grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts" 2025-07-17T07:05:25.0050956Z echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}" 2025-07-17T07:05:25.0051370Z  2025-07-17T07:05:25.0051634Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-07-17T07:05:25.0052228Z  docker exec -t "${container_name}" sh -c "python3 -m pip install -r .ci/docker/requirements-ci.txt" 2025-07-17T07:05:25.0052748Z fi 2025-07-17T07:05:25.0052960Z  2025-07-17T07:05:25.0053462Z docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}" 2025-07-17T07:05:25.0059012Z shell: /usr/bin/bash -e {0} 2025-07-17T07:05:25.0059283Z env: 2025-07-17T07:05:25.0059498Z GIT_DEFAULT_BRANCH: main 2025-07-17T07:05:25.0059807Z BUILD_ENVIRONMENT: linux-jammy-py3.13-clang12 2025-07-17T07:05:25.0060245Z PR_NUMBER: 2025-07-17T07:05:25.0060491Z GITHUB_REPOSITORY: pytorch/pytorch 2025-07-17T07:05:25.0060792Z GITHUB_WORKFLOW: pull 2025-07-17T07:05:25.0061046Z GITHUB_JOB: test 2025-07-17T07:05:25.0061283Z GITHUB_RUN_ID: 16337959907 2025-07-17T07:05:25.0061558Z GITHUB_RUN_NUMBER: 336806 2025-07-17T07:05:25.0061820Z GITHUB_RUN_ATTEMPT: 1 2025-07-17T07:05:25.0062063Z JOB_ID: 46154839619 2025-07-17T07:05:25.0062475Z JOB_NAME: linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T07:05:25.0062935Z BRANCH: main 2025-07-17T07:05:25.0063213Z SHA1: a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:05:25.0063591Z BASE_SHA: a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:05:25.0064027Z TEST_CONFIG: dynamo_wrapped 2025-07-17T07:05:25.0064324Z SHARD_NUMBER: 2 2025-07-17T07:05:25.0064592Z NUM_TEST_SHARDS: 3 2025-07-17T07:05:25.0064824Z REENABLED_ISSUES: 2025-07-17T07:05:25.0065087Z CONTINUE_THROUGH_ERROR: True 2025-07-17T07:05:25.0065383Z VERBOSE_TEST_LOGS: False 2025-07-17T07:05:25.0065651Z TEST_SHOWLOCALS: False 2025-07-17T07:05:25.0065901Z NO_TEST_TIMEOUT: False 2025-07-17T07:05:25.0066150Z NO_TD: False 2025-07-17T07:05:25.0066387Z TD_DISTRIBUTED: False 2025-07-17T07:05:25.0066688Z SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2 2025-07-17T07:05:25.0067092Z SCCACHE_REGION: us-east-1 2025-07-17T07:05:25.0067363Z SHM_SIZE: 1g 2025-07-17T07:05:25.0068086Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:05:25.0068896Z XLA_CUDA: 2025-07-17T07:05:25.0069261Z XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla 2025-07-17T07:05:25.0069733Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0 2025-07-17T07:05:25.0070263Z PYTORCH_TEST_RERUN_DISABLED_TESTS: 0 2025-07-17T07:05:25.0070614Z DASHBOARD_TAG: 2025-07-17T07:05:25.0071044Z HUGGING_FACE_HUB_TOKEN: *** 2025-07-17T07:05:25.0071467Z SCRIBE_GRAPHQL_ACCESS_TOKEN: *** 2025-07-17T07:05:25.0071901Z ARTIFACTS_FILE_SUFFIX: test-dynamo_wrapped-2-3-linux.2xlarge_46154839619 2025-07-17T07:05:25.0072348Z ##[endgroup] 2025-07-17T07:05:25.0094780Z + [[ dynamo_wrapped == \m\u\l\t\i\g\p\u ]] 2025-07-17T07:05:25.0095153Z + [[ linux-jammy-py3.13-clang12 == *onnx* ]] 2025-07-17T07:05:25.0095498Z + TEST_COMMAND=.ci/pytorch/test.sh 2025-07-17T07:05:25.0097981Z ++ awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo 2025-07-17T07:05:25.0189769Z + TOTAL_AVAILABLE_MEMORY_IN_GB='14.244 ' 2025-07-17T07:05:25.0190328Z + TOTAL_MEMORY_WITH_SWAP=17 2025-07-17T07:05:25.0190897Z + [[ linux-jammy-py3.13-clang12 == *\s\3\9\0\x* ]] 2025-07-17T07:05:25.0191258Z + SHM_OPTS=--shm-size=1g 2025-07-17T07:05:25.0191534Z + JENKINS_USER='--user jenkins' 2025-07-17T07:05:25.0191816Z + DOCKER_SHELL_CMD= 2025-07-17T07:05:25.0198863Z +++ nproc --ignore=2 2025-07-17T07:05:25.0222293Z ++ docker run -e BUILD_ENVIRONMENT -e PR_NUMBER -e GITHUB_ACTIONS -e GITHUB_REPOSITORY -e GITHUB_WORKFLOW -e GITHUB_JOB -e GITHUB_RUN_ID -e GITHUB_RUN_NUMBER -e GITHUB_RUN_ATTEMPT -e JOB_ID -e JOB_NAME -e BASE_SHA -e BRANCH -e SHA1 -e AWS_DEFAULT_REGION -e IN_WHEEL_TEST -e SHARD_NUMBER -e TEST_CONFIG -e NUM_TEST_SHARDS -e REENABLED_ISSUES -e CONTINUE_THROUGH_ERROR -e VERBOSE_TEST_LOGS -e TEST_SHOWLOCALS -e NO_TEST_TIMEOUT -e NO_TD -e TD_DISTRIBUTED -e PR_LABELS -e MAX_JOBS=6 -e SCCACHE_BUCKET -e SCCACHE_REGION -e XLA_CUDA -e XLA_CLANG_CACHE_S3_BUCKET_NAME -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK -e PYTORCH_TEST_RERUN_DISABLED_TESTS -e SKIP_SCCACHE_INITIALIZATION=1 -e HUGGING_FACE_HUB_TOKEN -e SCRIBE_GRAPHQL_ACCESS_TOKEN -e DASHBOARD_TAG -e ARTIFACTS_FILE_SUFFIX --memory=14g --memory-swap=17g --env-file=/tmp/github_env_16337959907 --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --ipc=host --shm-size=1g --tty --detach --name= --user jenkins -v /home/ec2-user/actions-runner/_work/pytorch/pytorch:/var/lib/jenkins/workspace -w /var/lib/jenkins/workspace 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T07:05:30.2115759Z + container_name=987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T07:05:30.2120223Z + grep download.pytorch.org /etc/hosts 2025-07-17T07:05:30.2122238Z + docker exec -i 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 sudo bash -c '/bin/cat >> /etc/hosts' 2025-07-17T07:05:30.3741133Z + echo DOCKER_CONTAINER_ID=987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T07:05:30.3742281Z + [[ linux-jammy-py3.13-clang12 == *\s\3\9\0\x* ]] 2025-07-17T07:05:30.3745386Z ++ echo dist/torch-2.9.0a0+gita38f433-cp313-cp313-linux_x86_64.whl 2025-07-17T07:05:30.3748612Z + docker exec -t 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 sh -c 'python3 -m pip install dist/torch-2.9.0a0+gita38f433-cp313-cp313-linux_x86_64.whl[opt-einsum] && .ci/pytorch/test.sh' 2025-07-17T07:05:30.9375753Z Processing ./dist/torch-2.9.0a0+gita38f433-cp313-cp313-linux_x86_64.whl (from torch==2.9.0a0+gita38f433) 2025-07-17T07:05:31.4730372Z Requirement already satisfied: filelock in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+gita38f433->torch==2.9.0a0+gita38f433) (3.18.0) 2025-07-17T07:05:31.4733684Z Requirement already satisfied: typing-extensions>=4.10.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+gita38f433->torch==2.9.0a0+gita38f433) (4.14.1) 2025-07-17T07:05:31.4738895Z Requirement already satisfied: setuptools in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+gita38f433->torch==2.9.0a0+gita38f433) (80.9.0) 2025-07-17T07:05:31.4742716Z Requirement already satisfied: sympy>=1.13.3 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+gita38f433->torch==2.9.0a0+gita38f433) (1.13.3) 2025-07-17T07:05:31.4745815Z Requirement already satisfied: networkx in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+gita38f433->torch==2.9.0a0+gita38f433) (2.8.8) 2025-07-17T07:05:31.4750130Z Requirement already satisfied: jinja2 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+gita38f433->torch==2.9.0a0+gita38f433) (3.1.6) 2025-07-17T07:05:31.4753382Z Requirement already satisfied: fsspec in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+gita38f433->torch==2.9.0a0+gita38f433) (2025.5.1) 2025-07-17T07:05:31.4768281Z Requirement already satisfied: opt-einsum>=3.3 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+gita38f433->torch==2.9.0a0+gita38f433) (3.3.0) 2025-07-17T07:05:31.4778979Z Requirement already satisfied: numpy>=1.7 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from opt-einsum>=3.3->torch==2.9.0a0+gita38f433->torch==2.9.0a0+gita38f433) (2.1.2) 2025-07-17T07:05:31.4824544Z Requirement already satisfied: mpmath<1.4,>=1.1.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from sympy>=1.13.3->torch==2.9.0a0+gita38f433->torch==2.9.0a0+gita38f433) (1.3.0) 2025-07-17T07:05:31.4943420Z Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from jinja2->torch==2.9.0a0+gita38f433->torch==2.9.0a0+gita38f433) (3.0.2) 2025-07-17T07:05:31.7003330Z Installing collected packages: torch 2025-07-17T07:05:43.4001182Z Successfully installed torch-2.9.0a0+gita38f433 2025-07-17T07:05:43.4738468Z + export TERM=vt100 2025-07-17T07:05:43.4738771Z + TERM=vt100 2025-07-17T07:05:43.4740602Z ++ dirname .ci/pytorch/test.sh 2025-07-17T07:05:43.4759172Z + source .ci/pytorch/common.sh 2025-07-17T07:05:43.4766154Z +++ dirname .ci/pytorch/common.sh 2025-07-17T07:05:43.4773688Z ++ source .ci/pytorch/common_utils.sh 2025-07-17T07:05:43.4779012Z +++ declare -f -t trap_add 2025-07-17T07:05:43.4783057Z ++ set -ex -o pipefail 2025-07-17T07:05:43.4783358Z ++ [[ linux-jammy-py3.13-clang12 == *rocm* ]] 2025-07-17T07:05:43.4783689Z ++ BUILD_TEST_LIBTORCH=0 2025-07-17T07:05:43.4786629Z ++ dirname .ci/pytorch/test.sh 2025-07-17T07:05:43.4793459Z + source .ci/pytorch/common-build.sh 2025-07-17T07:05:43.4798212Z ++ [[ linux-jammy-py3.13-clang12 != *win-* ]] 2025-07-17T07:05:43.4804517Z ++++ dirname .ci/pytorch/common-build.sh 2025-07-17T07:05:43.4811657Z +++ cd .ci/pytorch 2025-07-17T07:05:43.4811954Z +++ pwd -P 2025-07-17T07:05:43.4814218Z ++ script_dir=/var/lib/jenkins/workspace/.ci/pytorch 2025-07-17T07:05:43.4814654Z ++ [[ linux-jammy-py3.13-clang12 == *-pch* ]] 2025-07-17T07:05:43.4814981Z ++ which sccache 2025-07-17T07:05:43.4834562Z ++ [[ -z ossci-compiler-cache-circleci-v2 ]] 2025-07-17T07:05:43.4834959Z ++ sccache --stop-server 2025-07-17T07:05:43.4889240Z ++ true 2025-07-17T07:05:43.4889599Z ++ rm -f /var/lib/jenkins/sccache_error.log 2025-07-17T07:05:43.4908948Z ++ trap_add sccache_epilogue EXIT 2025-07-17T07:05:43.4909301Z ++ trap_add_cmd=sccache_epilogue 2025-07-17T07:05:43.4909587Z ++ shift 2025-07-17T07:05:43.4909801Z ++ for trap_add_name in "$@" 2025-07-17T07:05:43.4915305Z ++++ trap -p EXIT 2025-07-17T07:05:43.4918268Z +++ eval 'extract_trap_cmd ' 2025-07-17T07:05:43.4918724Z ++++ extract_trap_cmd 2025-07-17T07:05:43.4918967Z ++++ printf '%s\n' '' 2025-07-17T07:05:43.4919289Z +++ printf '%s\n' sccache_epilogue 2025-07-17T07:05:43.4921174Z ++ trap -- ' 2025-07-17T07:05:43.4921576Z sccache_epilogue' EXIT 2025-07-17T07:05:43.4921955Z ++ [[ -n 1 ]] 2025-07-17T07:05:43.4922476Z ++ echo 'Skipping sccache server initialization, setting environment variables' 2025-07-17T07:05:43.4923165Z Skipping sccache server initialization, setting environment variables 2025-07-17T07:05:43.4923613Z ++ export SCCACHE_IDLE_TIMEOUT=0 2025-07-17T07:05:43.4923912Z ++ SCCACHE_IDLE_TIMEOUT=0 2025-07-17T07:05:43.4924287Z ++ export SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-07-17T07:05:43.4924733Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-07-17T07:05:43.4925222Z ++ export RUST_LOG=sccache::server=error 2025-07-17T07:05:43.4925560Z ++ RUST_LOG=sccache::server=error 2025-07-17T07:05:43.4925843Z ++ sccache --zero-stats 2025-07-17T07:05:43.5883754Z Statistics zeroed. 2025-07-17T07:05:43.5887778Z ++ which ccache 2025-07-17T07:05:43.5903110Z + [[ linux-jammy-py3.13-clang12 != *rocm* ]] 2025-07-17T07:05:43.5903560Z + [[ linux-jammy-py3.13-clang12 != *s390x* ]] 2025-07-17T07:05:43.5903920Z + [[ -d /var/lib/jenkins/workspace ]] 2025-07-17T07:05:43.5906493Z ++ stat -c %u /var/lib/jenkins/workspace 2025-07-17T07:05:43.5952316Z + WORKSPACE_ORIGINAL_OWNER_ID=1000 2025-07-17T07:05:43.5952689Z + trap_add cleanup_workspace EXIT 2025-07-17T07:05:43.5953005Z + trap_add_cmd=cleanup_workspace 2025-07-17T07:05:43.5953289Z + shift 2025-07-17T07:05:43.5953500Z + for trap_add_name in "$@" 2025-07-17T07:05:43.5959383Z +++ trap -p EXIT 2025-07-17T07:05:43.5962141Z ++ eval 'extract_trap_cmd trap -- '\'' 2025-07-17T07:05:43.5962619Z sccache_epilogue'\'' EXIT' 2025-07-17T07:05:43.5962991Z +++ extract_trap_cmd trap -- ' 2025-07-17T07:05:43.5963336Z sccache_epilogue' EXIT 2025-07-17T07:05:43.5963657Z +++ printf '%s\n' ' 2025-07-17T07:05:43.5964064Z sccache_epilogue' 2025-07-17T07:05:43.5964512Z ++ printf '%s\n' cleanup_workspace 2025-07-17T07:05:43.5965580Z + trap -- ' 2025-07-17T07:05:43.5965938Z sccache_epilogue 2025-07-17T07:05:43.5966330Z cleanup_workspace' EXIT 2025-07-17T07:05:43.5966833Z + sudo chown -R jenkins /var/lib/jenkins/workspace 2025-07-17T07:05:44.2423712Z + git config --global --add safe.directory /var/lib/jenkins/workspace 2025-07-17T07:05:44.2624864Z + echo 'Environment variables:' 2025-07-17T07:05:44.2625171Z Environment variables: 2025-07-17T07:05:44.2625418Z + env 2025-07-17T07:05:44.2645061Z GITHUB_WORKSPACE=/home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-07-17T07:05:44.2645931Z CONTINUE_THROUGH_ERROR=True 2025-07-17T07:05:44.2646474Z BUILD_ENVIRONMENT=linux-jammy-py3.13-clang12 2025-07-17T07:05:44.2647050Z HOSTNAME=987bbea70184 2025-07-17T07:05:44.2648025Z GITHUB_PATH=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/add_path_c3d888da-79c3-4be5-a490-11ed378bf3ae 2025-07-17T07:05:44.2649095Z GITHUB_ACTION=__run_2 2025-07-17T07:05:44.2649588Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-07-17T07:05:44.2649897Z GITHUB_RUN_NUMBER=336806 2025-07-17T07:05:44.2650161Z TEST_CONFIG=dynamo_wrapped 2025-07-17T07:05:44.2650455Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-07-17T07:05:44.2650789Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-07-17T07:05:44.2651116Z SCCACHE_IDLE_TIMEOUT=0 2025-07-17T07:05:44.2651671Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-07-17T07:05:44.2652035Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-07-17T07:05:44.2652432Z GITHUB_REF_TYPE=branch 2025-07-17T07:05:44.2652747Z TORCH_CUDA_ARCH_LIST=Maxwell 2025-07-17T07:05:44.2653069Z BASE_SHA=a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:05:44.2653514Z XLA_CUDA= 2025-07-17T07:05:44.2653862Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-07-17T07:05:44.2654371Z HUGGING_FACE_HUB_TOKEN=*** 2025-07-17T07:05:44.2655947Z *** 2025-07-17T07:05:44.2656176Z GITHUB_REPOSITORY_ID=65600975 2025-07-17T07:05:44.2656479Z GITHUB_ACTIONS=true 2025-07-17T07:05:44.2656804Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-07-17T07:05:44.2657248Z SHA1=a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:05:44.2657641Z GITHUB_SHA=a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:05:44.2658222Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/pull.yml@refs/heads/main 2025-07-17T07:05:44.2658700Z UCC_HOME=/usr 2025-07-17T07:05:44.2659000Z VERBOSE_TEST_LOGS=False 2025-07-17T07:05:44.2659251Z GITHUB_REF=refs/heads/main 2025-07-17T07:05:44.2659529Z SHARD_NUMBER=2 2025-07-17T07:05:44.2659804Z GITHUB_REF_PROTECTED=true 2025-07-17T07:05:44.2660058Z HOME=/var/lib/jenkins 2025-07-17T07:05:44.2660392Z GITHUB_API_URL=https://api.github.com 2025-07-17T07:05:44.2660739Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-07-17T07:05:44.2661031Z UCX_COMMIT= 2025-07-17T07:05:44.2661289Z USE_SYSTEM_NCCL=1 2025-07-17T07:05:44.2661522Z NUM_TEST_SHARDS=3 2025-07-17T07:05:44.2661737Z UCX_HOME=/usr 2025-07-17T07:05:44.2662373Z GITHUB_STATE=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/save_state_c3d888da-79c3-4be5-a490-11ed378bf3ae 2025-07-17T07:05:44.2663313Z JOB_NAME=linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T07:05:44.2664117Z GITHUB_ENV=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_env_c3d888da-79c3-4be5-a490-11ed378bf3ae 2025-07-17T07:05:44.2664998Z GITHUB_EVENT_PATH=/home/ec2-user/actions-runner/_work/_temp/_github_workflow/event.json 2025-07-17T07:05:44.2665512Z GITHUB_EVENT_NAME=push 2025-07-17T07:05:44.2665825Z DASHBOARD_TAG= 2025-07-17T07:05:44.2666040Z GITHUB_RUN_ID=16337959907 2025-07-17T07:05:44.2666321Z INSTALLED_OPENBLAS= 2025-07-17T07:05:44.2666989Z GITHUB_STEP_SUMMARY=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/step_summary_c3d888da-79c3-4be5-a490-11ed378bf3ae 2025-07-17T07:05:44.2667724Z GITHUB_ACTOR=pytorchmergebot 2025-07-17T07:05:44.2667986Z PR_NUMBER= 2025-07-17T07:05:44.2668195Z DESIRED_CUDA= 2025-07-17T07:05:44.2668419Z GITHUB_RUN_ATTEMPT=1 2025-07-17T07:05:44.2668664Z ANACONDA_PYTHON_VERSION=3.13 2025-07-17T07:05:44.2669009Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-07-17T07:05:44.2669360Z TERM=vt100 2025-07-17T07:05:44.2669565Z INSTALLED_VISION=yes 2025-07-17T07:05:44.2669804Z BRANCH=main 2025-07-17T07:05:44.2670225Z SCCACHE_REGION=us-east-1 2025-07-17T07:05:44.2670497Z OPENSSL_ROOT_DIR=/opt/openssl 2025-07-17T07:05:44.2670787Z CUDA_PATH=/usr/local/cuda 2025-07-17T07:05:44.2671320Z GITHUB_ACTION_PATH=/home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-07-17T07:05:44.2671922Z GITHUB_SERVER_URL=https://github.com 2025-07-17T07:05:44.2672281Z UCC_COMMIT= 2025-07-17T07:05:44.2672497Z REENABLED_ISSUES= 2025-07-17T07:05:44.2672722Z DOCS= 2025-07-17T07:05:44.2672915Z SHLVL=1 2025-07-17T07:05:44.2673113Z MAX_JOBS=6 2025-07-17T07:05:44.2673329Z GITHUB_ACTOR_ID=97764156 2025-07-17T07:05:44.2673661Z GITHUB_WORKFLOW_SHA=a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:05:44.2674055Z GITHUB_REF_NAME=main 2025-07-17T07:05:44.2674441Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-07-17T07:05:44.2675045Z GITHUB_JOB=test 2025-07-17T07:05:44.2675277Z NO_TEST_TIMEOUT=False 2025-07-17T07:05:44.2675534Z TD_DISTRIBUTED=False 2025-07-17T07:05:44.2675790Z GITHUB_REPOSITORY=pytorch/pytorch 2025-07-17T07:05:44.2676107Z GITHUB_RETENTION_DAYS=90 2025-07-17T07:05:44.2676377Z OPENSSL_DIR=/opt/openssl 2025-07-17T07:05:44.2676636Z GITHUB_ACTION_REPOSITORY= 2025-07-17T07:05:44.2677506Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-07-17T07:05:44.2678348Z GITHUB_BASE_REF= 2025-07-17T07:05:44.2678581Z INSTALLED_ACL= 2025-07-17T07:05:44.2679087Z ARTIFACTS_FILE_SUFFIX=test-dynamo_wrapped-2-3-linux.2xlarge_46154839619 2025-07-17T07:05:44.2679536Z CI=true 2025-07-17T07:05:44.2679763Z GITHUB_REPOSITORY_OWNER=pytorch 2025-07-17T07:05:44.2680096Z RUST_LOG=sccache::server=error 2025-07-17T07:05:44.2680377Z JOB_ID=46154839619 2025-07-17T07:05:44.2680613Z GITHUB_HEAD_REF= 2025-07-17T07:05:44.2680861Z GITHUB_ACTION_REF= 2025-07-17T07:05:44.2681156Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-07-17T07:05:44.2681514Z TEST_SHOWLOCALS=False 2025-07-17T07:05:44.2681754Z GITHUB_WORKFLOW=pull 2025-07-17T07:05:44.2682021Z DEBIAN_FRONTEND=noninteractive 2025-07-17T07:05:44.2682702Z GITHUB_OUTPUT=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_output_c3d888da-79c3-4be5-a490-11ed378bf3ae 2025-07-17T07:05:44.2683358Z NO_TD=False 2025-07-17T07:05:44.2683575Z SKIP_SCCACHE_INITIALIZATION=1 2025-07-17T07:05:44.2683884Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-07-17T07:05:44.2684194Z _=/usr/bin/env 2025-07-17T07:05:44.2684505Z ++ python -c 'import site; print(site.getsitepackages()[0])' 2025-07-17T07:05:44.2855823Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch 2025-07-17T07:05:44.2856960Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin 2025-07-17T07:05:44.2857985Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib 2025-07-17T07:05:44.2858991Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/test 2025-07-17T07:05:44.2859526Z + BUILD_DIR=build 2025-07-17T07:05:44.2859780Z + BUILD_RENAMED_DIR=build_renamed 2025-07-17T07:05:44.2860070Z + BUILD_BIN_DIR=build/bin 2025-07-17T07:05:44.2860331Z + SHARD_NUMBER=2 2025-07-17T07:05:44.2860566Z + NUM_TEST_SHARDS=3 2025-07-17T07:05:44.2860813Z + export TORCH_SERIALIZATION_DEBUG=1 2025-07-17T07:05:44.2861134Z + TORCH_SERIALIZATION_DEBUG=1 2025-07-17T07:05:44.2861466Z + export VALGRIND=ON 2025-07-17T07:05:44.2861698Z + VALGRIND=ON 2025-07-17T07:05:44.2861967Z + [[ linux-jammy-py3.13-clang12 == *clang9* ]] 2025-07-17T07:05:44.2862380Z + [[ linux-jammy-py3.13-clang12 == *xpu* ]] 2025-07-17T07:05:44.2862719Z + [[ linux-jammy-py3.13-clang12 == *s390x* ]] 2025-07-17T07:05:44.2863034Z + [[ 0 == \1 ]] 2025-07-17T07:05:44.2863250Z + [[ True == \1 ]] 2025-07-17T07:05:44.2863511Z + [[ linux-jammy-py3.13-clang12 != *bazel* ]] 2025-07-17T07:05:44.2863865Z ++ realpath build/custom_test_artifacts 2025-07-17T07:05:44.2881579Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/workspace/build/custom_test_artifacts 2025-07-17T07:05:44.2882112Z + [[ -n '' ]] 2025-07-17T07:05:44.2882343Z + echo 'Environment variables' 2025-07-17T07:05:44.2882633Z Environment variables 2025-07-17T07:05:44.2882878Z + env 2025-07-17T07:05:44.2891105Z GITHUB_WORKSPACE=/home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-07-17T07:05:44.2892552Z CONTINUE_THROUGH_ERROR=True 2025-07-17T07:05:44.2892951Z BUILD_ENVIRONMENT=linux-jammy-py3.13-clang12 2025-07-17T07:05:44.2893297Z HOSTNAME=987bbea70184 2025-07-17T07:05:44.2893912Z GITHUB_PATH=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/add_path_c3d888da-79c3-4be5-a490-11ed378bf3ae 2025-07-17T07:05:44.2894551Z GITHUB_ACTION=__run_2 2025-07-17T07:05:44.2894817Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-07-17T07:05:44.2895129Z GITHUB_RUN_NUMBER=336806 2025-07-17T07:05:44.2895564Z TEST_CONFIG=dynamo_wrapped 2025-07-17T07:05:44.2895886Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-07-17T07:05:44.2896225Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-07-17T07:05:44.2896530Z SCCACHE_IDLE_TIMEOUT=0 2025-07-17T07:05:44.2897025Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-07-17T07:05:44.2897339Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-07-17T07:05:44.2897662Z GITHUB_REF_TYPE=branch 2025-07-17T07:05:44.2897912Z TORCH_CUDA_ARCH_LIST=Maxwell 2025-07-17T07:05:44.2898232Z BASE_SHA=a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:05:44.2898565Z XLA_CUDA= 2025-07-17T07:05:44.2898779Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-07-17T07:05:44.2899191Z HUGGING_FACE_HUB_TOKEN=*** 2025-07-17T07:05:44.2899602Z *** 2025-07-17T07:05:44.2899820Z GITHUB_REPOSITORY_ID=65600975 2025-07-17T07:05:44.2900088Z GITHUB_ACTIONS=true 2025-07-17T07:05:44.2900384Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-07-17T07:05:44.2900774Z SHA1=a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:05:44.2901140Z GITHUB_SHA=a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:05:44.2901658Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/pull.yml@refs/heads/main 2025-07-17T07:05:44.2902128Z UCC_HOME=/usr 2025-07-17T07:05:44.2902353Z TORCH_SERIALIZATION_DEBUG=1 2025-07-17T07:05:44.2902634Z VERBOSE_TEST_LOGS=False 2025-07-17T07:05:44.2902906Z GITHUB_REF=refs/heads/main 2025-07-17T07:05:44.2903157Z SHARD_NUMBER=2 2025-07-17T07:05:44.2903393Z GITHUB_REF_PROTECTED=true 2025-07-17T07:05:44.2903657Z HOME=/var/lib/jenkins 2025-07-17T07:05:44.2903925Z GITHUB_API_URL=https://api.github.com 2025-07-17T07:05:44.2904259Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-07-17T07:05:44.2904555Z UCX_COMMIT= 2025-07-17T07:05:44.2904772Z USE_SYSTEM_NCCL=1 2025-07-17T07:05:44.2904990Z NUM_TEST_SHARDS=3 2025-07-17T07:05:44.2905216Z UCX_HOME=/usr 2025-07-17T07:05:44.2905795Z GITHUB_STATE=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/save_state_c3d888da-79c3-4be5-a490-11ed378bf3ae 2025-07-17T07:05:44.2906633Z JOB_NAME=linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T07:05:44.2907432Z GITHUB_ENV=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_env_c3d888da-79c3-4be5-a490-11ed378bf3ae 2025-07-17T07:05:44.2908266Z GITHUB_EVENT_PATH=/home/ec2-user/actions-runner/_work/_temp/_github_workflow/event.json 2025-07-17T07:05:44.2908769Z GITHUB_EVENT_NAME=push 2025-07-17T07:05:44.2909024Z DASHBOARD_TAG= 2025-07-17T07:05:44.2909259Z GITHUB_RUN_ID=16337959907 2025-07-17T07:05:44.2909524Z INSTALLED_OPENBLAS= 2025-07-17T07:05:44.2910146Z GITHUB_STEP_SUMMARY=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/step_summary_c3d888da-79c3-4be5-a490-11ed378bf3ae 2025-07-17T07:05:44.2910865Z GITHUB_ACTOR=pytorchmergebot 2025-07-17T07:05:44.2911146Z PR_NUMBER= 2025-07-17T07:05:44.2911347Z DESIRED_CUDA= 2025-07-17T07:05:44.2911577Z GITHUB_RUN_ATTEMPT=1 2025-07-17T07:05:44.2911822Z VALGRIND=ON 2025-07-17T07:05:44.2912043Z ANACONDA_PYTHON_VERSION=3.13 2025-07-17T07:05:44.2912393Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-07-17T07:05:44.2912751Z TERM=vt100 2025-07-17T07:05:44.2912954Z INSTALLED_VISION=yes 2025-07-17T07:05:44.2913192Z BRANCH=main 2025-07-17T07:05:44.2913414Z SCCACHE_REGION=us-east-1 2025-07-17T07:05:44.2913675Z OPENSSL_ROOT_DIR=/opt/openssl 2025-07-17T07:05:44.2913959Z CUDA_PATH=/usr/local/cuda 2025-07-17T07:05:44.2914488Z GITHUB_ACTION_PATH=/home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-07-17T07:05:44.2915087Z GITHUB_SERVER_URL=https://github.com 2025-07-17T07:05:44.2915375Z UCC_COMMIT= 2025-07-17T07:05:44.2915589Z REENABLED_ISSUES= 2025-07-17T07:05:44.2915811Z DOCS= 2025-07-17T07:05:44.2915993Z SHLVL=1 2025-07-17T07:05:44.2916193Z MAX_JOBS=6 2025-07-17T07:05:44.2916411Z GITHUB_ACTOR_ID=97764156 2025-07-17T07:05:44.2916744Z GITHUB_WORKFLOW_SHA=a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T07:05:44.2917133Z GITHUB_REF_NAME=main 2025-07-17T07:05:44.2917516Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-07-17T07:05:44.2918028Z GITHUB_JOB=test 2025-07-17T07:05:44.2918262Z NO_TEST_TIMEOUT=False 2025-07-17T07:05:44.2918514Z TD_DISTRIBUTED=False 2025-07-17T07:05:44.2918770Z GITHUB_REPOSITORY=pytorch/pytorch 2025-07-17T07:05:44.2919078Z GITHUB_RETENTION_DAYS=90 2025-07-17T07:05:44.2919345Z OPENSSL_DIR=/opt/openssl 2025-07-17T07:05:44.2919604Z GITHUB_ACTION_REPOSITORY= 2025-07-17T07:05:44.2920411Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-07-17T07:05:44.2921236Z GITHUB_BASE_REF= 2025-07-17T07:05:44.2921467Z INSTALLED_ACL= 2025-07-17T07:05:44.2921893Z ARTIFACTS_FILE_SUFFIX=test-dynamo_wrapped-2-3-linux.2xlarge_46154839619 2025-07-17T07:05:44.2922331Z CI=true 2025-07-17T07:05:44.2922553Z GITHUB_REPOSITORY_OWNER=pytorch 2025-07-17T07:05:44.2922866Z RUST_LOG=sccache::server=error 2025-07-17T07:05:44.2923139Z JOB_ID=46154839619 2025-07-17T07:05:44.2923368Z GITHUB_HEAD_REF= 2025-07-17T07:05:44.2923588Z GITHUB_ACTION_REF= 2025-07-17T07:05:44.2923880Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-07-17T07:05:44.2924241Z TEST_SHOWLOCALS=False 2025-07-17T07:05:44.2924487Z GITHUB_WORKFLOW=pull 2025-07-17T07:05:44.2924756Z DEBIAN_FRONTEND=noninteractive 2025-07-17T07:05:44.2925557Z GITHUB_OUTPUT=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_output_c3d888da-79c3-4be5-a490-11ed378bf3ae 2025-07-17T07:05:44.2926226Z NO_TD=False 2025-07-17T07:05:44.2926449Z SKIP_SCCACHE_INITIALIZATION=1 2025-07-17T07:05:44.2926763Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-07-17T07:05:44.2927083Z _=/usr/bin/env 2025-07-17T07:05:44.2927314Z + echo 'Testing pytorch' 2025-07-17T07:05:44.2927581Z Testing pytorch 2025-07-17T07:05:44.2927824Z + export LANG=C.UTF-8 2025-07-17T07:05:44.2928060Z + LANG=C.UTF-8 2025-07-17T07:05:44.2930300Z + PR_NUMBER= 2025-07-17T07:05:44.2930774Z + [[ dynamo_wrapped == \d\e\f\a\u\l\t ]] 2025-07-17T07:05:44.2931378Z + [[ dynamo_wrapped == \d\i\s\t\r\i\b\u\t\e\d ]] 2025-07-17T07:05:44.2932013Z + [[ dynamo_wrapped == \s\l\o\w ]] 2025-07-17T07:05:44.2932672Z + [[ linux-jammy-py3.13-clang12 == *slow-gradcheck* ]] 2025-07-17T07:05:44.2933325Z + [[ linux-jammy-py3.13-clang12 == *cuda* ]] 2025-07-17T07:05:44.2933896Z + [[ linux-jammy-py3.13-clang12 == *rocm* ]] 2025-07-17T07:05:44.2934478Z + [[ linux-jammy-py3.13-clang12 == *xpu* ]] 2025-07-17T07:05:44.2934940Z + [[ dynamo_wrapped == *crossref* ]] 2025-07-17T07:05:44.2935259Z + [[ linux-jammy-py3.13-clang12 == *rocm* ]] 2025-07-17T07:05:44.2935604Z + [[ linux-jammy-py3.13-clang12 == *xpu* ]] 2025-07-17T07:05:44.2935955Z + [[ linux-jammy-py3.13-clang12 != *-bazel-* ]] 2025-07-17T07:05:44.2936297Z + pip_install ninja==1.10.2 2025-07-17T07:05:44.2936679Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-07-17T07:05:44.2937156Z + python3 -m pip install --progress-bar off ninja==1.10.2 2025-07-17T07:05:44.7387825Z Collecting ninja==1.10.2 2025-07-17T07:05:44.7532283Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB) 2025-07-17T07:05:44.7638401Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB) 2025-07-17T07:05:44.9426987Z Installing collected packages: ninja 2025-07-17T07:05:44.9427417Z Attempting uninstall: ninja 2025-07-17T07:05:44.9460947Z Found existing installation: ninja 1.11.1.3 2025-07-17T07:05:44.9482121Z Uninstalling ninja-1.11.1.3: 2025-07-17T07:05:44.9534199Z Successfully uninstalled ninja-1.11.1.3 2025-07-17T07:05:44.9771723Z Successfully installed ninja-1.10.2 2025-07-17T07:05:45.0426908Z + export PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-07-17T07:05:45.0428602Z + PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-07-17T07:05:45.0429881Z + [[ linux-jammy-py3.13-clang12 == *aarch64* ]] 2025-07-17T07:05:45.0430271Z + [[ linux-jammy-py3.13-clang12 == *asan* ]] 2025-07-17T07:05:45.0430715Z + [[ linux-jammy-py3.13-clang12 == *-debug* ]] 2025-07-17T07:05:45.0431206Z + [[ linux-jammy-py3.13-clang12 != *-bazel-* ]] 2025-07-17T07:05:45.0431887Z + echo 'We are not in debug mode: linux-jammy-py3.13-clang12. Expect the assertion to pass' 2025-07-17T07:05:45.0432578Z We are not in debug mode: linux-jammy-py3.13-clang12. Expect the assertion to pass 2025-07-17T07:05:45.0433112Z + cd test 2025-07-17T07:05:45.0433513Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)' 2025-07-17T07:05:46.3840448Z + [[ dynamo_wrapped == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]] 2025-07-17T07:05:46.3840897Z + [[ dynamo_wrapped == \n\o\g\p\u\_\A\V\X\5\1\2 ]] 2025-07-17T07:05:46.3841335Z + [[ dynamo_wrapped == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]] 2025-07-17T07:05:46.3844331Z + DYNAMO_BENCHMARK_FLAGS=() 2025-07-17T07:05:46.3845085Z + [[ dynamo_wrapped == *pr_time_benchmarks* ]] 2025-07-17T07:05:46.3845570Z + [[ dynamo_wrapped == *dynamo_eager* ]] 2025-07-17T07:05:46.3845909Z + [[ dynamo_wrapped == *aot_eager* ]] 2025-07-17T07:05:46.3846244Z + [[ dynamo_wrapped == *aot_inductor* ]] 2025-07-17T07:05:46.3846587Z + [[ dynamo_wrapped == *max_autotune_inductor* ]] 2025-07-17T07:05:46.3846940Z + [[ dynamo_wrapped == *inductor* ]] 2025-07-17T07:05:46.3847251Z + [[ dynamo_wrapped == *dynamic* ]] 2025-07-17T07:05:46.3847546Z + [[ dynamo_wrapped == *cpu* ]] 2025-07-17T07:05:46.3847867Z + DYNAMO_BENCHMARK_FLAGS+=(--device cuda) 2025-07-17T07:05:46.3868107Z + [[ linux-jammy-py3.13-clang12 == *libtorch* ]] 2025-07-17T07:05:46.3868493Z + [[ linux-jammy-py3.13-clang12 == *-bazel-* ]] 2025-07-17T07:05:46.3871926Z + cd test 2025-07-17T07:05:46.3872803Z + python -c 'import torch; print(torch.__config__.show())' 2025-07-17T07:05:47.4479620Z PyTorch built with: 2025-07-17T07:05:47.4479910Z - GCC 4.2 2025-07-17T07:05:47.4480163Z - C++ Version: 201703 2025-07-17T07:05:47.4480407Z - clang 12.0.1 2025-07-17T07:05:47.4480969Z - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-07-17T07:05:47.4481714Z - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-07-17T07:05:47.4482149Z - OpenMP 201811 2025-07-17T07:05:47.4482415Z - LAPACK is enabled (usually provided by MKL) 2025-07-17T07:05:47.4482759Z - NNPACK is enabled 2025-07-17T07:05:47.4483028Z - CPU capability usage: AVX512 2025-07-17T07:05:47.4488529Z - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=a38f433be2e94a64b095a44ba39879d02d0c2316, CXX_COMPILER=/opt/cache/bin/clang++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON -DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=braced-scalar-init -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wvla-extension -Wsuggest-override -Wnewline-eof -Winconsistent-missing-override -Winconsistent-missing-destructor-override -Wno-pass-failed -Wno-error=old-style-cast -Wconstant-conversion -Qunused-arguments -faligned-new -Werror -fno-math-errno -fno-trapping-math -Werror=format, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.9.0, USE_CUDA=OFF, USE_CUDNN=OFF, USE_CUSPARSELT=OFF, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, 2025-07-17T07:05:47.4494082Z 2025-07-17T07:05:47.6983578Z + cd test 2025-07-17T07:05:47.6983997Z + python -c 'import torch; print(torch.__config__.parallel_info())' 2025-07-17T07:05:48.7610895Z ATen/Parallel: 2025-07-17T07:05:48.7611370Z at::get_num_threads() : 4 2025-07-17T07:05:48.7611805Z at::get_num_interop_threads() : 4 2025-07-17T07:05:48.7612213Z OpenMP 201811 2025-07-17T07:05:48.7612574Z omp_get_max_threads() : 4 2025-07-17T07:05:48.7613415Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-07-17T07:05:48.7614343Z mkl_get_max_threads() : 4 2025-07-17T07:05:48.7614883Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-07-17T07:05:48.7615545Z std::thread::hardware_concurrency() : 8 2025-07-17T07:05:48.7616006Z Environment variables: 2025-07-17T07:05:48.7616746Z OMP_NUM_THREADS : [not set] 2025-07-17T07:05:48.7617157Z MKL_NUM_THREADS : [not set] 2025-07-17T07:05:48.7617567Z ATen parallel backend: OpenMP 2025-07-17T07:05:48.7617838Z 2025-07-17T07:05:49.0066932Z + [[ dynamo_wrapped == *numpy_2* ]] 2025-07-17T07:05:49.0067691Z + [[ linux-jammy-py3.13-clang12 == *aarch64* ]] 2025-07-17T07:05:49.0068154Z + [[ dynamo_wrapped == *backward* ]] 2025-07-17T07:05:49.0068470Z + [[ dynamo_wrapped == *xla* ]] 2025-07-17T07:05:49.0068763Z + [[ dynamo_wrapped == *executorch* ]] 2025-07-17T07:05:49.0069102Z + [[ dynamo_wrapped == \j\i\t\_\l\e\g\a\c\y ]] 2025-07-17T07:05:49.0069480Z + [[ linux-jammy-py3.13-clang12 == *libtorch* ]] 2025-07-17T07:05:49.0069827Z + [[ dynamo_wrapped == distributed ]] 2025-07-17T07:05:49.0070346Z + [[ dynamo_wrapped == *operator_benchmark* ]] 2025-07-17T07:05:49.0070719Z + [[ dynamo_wrapped == *inductor_distributed* ]] 2025-07-17T07:05:49.0071070Z + [[ dynamo_wrapped == *inductor-halide* ]] 2025-07-17T07:05:49.0071480Z + [[ dynamo_wrapped == *inductor-triton-cpu* ]] 2025-07-17T07:05:49.0072051Z + [[ dynamo_wrapped == *inductor-micro-benchmark* ]] 2025-07-17T07:05:49.0072430Z + [[ dynamo_wrapped == *huggingface* ]] 2025-07-17T07:05:49.0072742Z + [[ dynamo_wrapped == *timm* ]] 2025-07-17T07:05:49.0073046Z + [[ dynamo_wrapped == cachebench ]] 2025-07-17T07:05:49.0073416Z + [[ dynamo_wrapped == verify_cachebench ]] 2025-07-17T07:05:49.0073757Z + [[ dynamo_wrapped == *torchbench* ]] 2025-07-17T07:05:49.0074101Z + [[ dynamo_wrapped == *inductor_cpp_wrapper* ]] 2025-07-17T07:05:49.0074451Z + [[ dynamo_wrapped == *inductor* ]] 2025-07-17T07:05:49.0074768Z + [[ dynamo_wrapped == *einops* ]] 2025-07-17T07:05:49.0075086Z + [[ dynamo_wrapped == *dynamo_wrapped* ]] 2025-07-17T07:05:49.0075406Z + install_torchvision 2025-07-17T07:05:49.0075654Z + local orig_preload 2025-07-17T07:05:49.0075914Z + local commit 2025-07-17T07:05:49.0076153Z ++ get_pinned_commit vision 2025-07-17T07:05:49.0076449Z ++ cat .github/ci_commit_pins/vision.txt 2025-07-17T07:05:49.0099857Z + commit=966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-07-17T07:05:49.0100540Z + orig_preload= 2025-07-17T07:05:49.0100979Z + '[' -n '' ']' 2025-07-17T07:05:49.0101554Z + pip_install --no-use-pep517 git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-07-17T07:05:49.0112663Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-07-17T07:05:49.0113565Z + python3 -m pip install --progress-bar off --no-use-pep517 git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-07-17T07:05:49.3378944Z Collecting git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-07-17T07:05:49.3383518Z Cloning https://github.com/pytorch/vision.git (to revision 966da7e46f65d6d49df3e31214470a4fe5cc8e66) to /tmp/pip-req-build-oppardgn 2025-07-17T07:05:49.3549257Z Running command git clone --filter=blob:none --quiet https://github.com/pytorch/vision.git /tmp/pip-req-build-oppardgn 2025-07-17T07:05:51.2084636Z Running command git rev-parse -q --verify 'sha^966da7e46f65d6d49df3e31214470a4fe5cc8e66' 2025-07-17T07:05:51.2104882Z Running command git fetch -q https://github.com/pytorch/vision.git 966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-07-17T07:05:51.3239546Z Running command git checkout -q 966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-07-17T07:05:51.6118407Z Resolved https://github.com/pytorch/vision.git to commit 966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-07-17T07:05:53.5843442Z Preparing metadata (setup.py) ... [?25l- \ | done 2025-07-17T07:05:53.5864076Z [?25hRequirement already satisfied: numpy in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torchvision==0.22.0a0+966da7e) (2.1.2) 2025-07-17T07:05:53.5867766Z Requirement already satisfied: torch in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torchvision==0.22.0a0+966da7e) (2.9.0a0+gita38f433) 2025-07-17T07:05:53.5872927Z Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torchvision==0.22.0a0+966da7e) (11.0.0) 2025-07-17T07:05:53.5930605Z Requirement already satisfied: filelock in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch->torchvision==0.22.0a0+966da7e) (3.18.0) 2025-07-17T07:05:53.5935506Z Requirement already satisfied: typing-extensions>=4.10.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch->torchvision==0.22.0a0+966da7e) (4.14.1) 2025-07-17T07:05:53.5943677Z Requirement already satisfied: setuptools in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch->torchvision==0.22.0a0+966da7e) (80.9.0) 2025-07-17T07:05:53.5948592Z Requirement already satisfied: sympy>=1.13.3 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch->torchvision==0.22.0a0+966da7e) (1.13.3) 2025-07-17T07:05:53.5953427Z Requirement already satisfied: networkx in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch->torchvision==0.22.0a0+966da7e) (2.8.8) 2025-07-17T07:05:53.5956576Z Requirement already satisfied: jinja2 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch->torchvision==0.22.0a0+966da7e) (3.1.6) 2025-07-17T07:05:53.5960199Z Requirement already satisfied: fsspec in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch->torchvision==0.22.0a0+966da7e) (2025.5.1) 2025-07-17T07:05:53.5975551Z Requirement already satisfied: mpmath<1.4,>=1.1.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from sympy>=1.13.3->torch->torchvision==0.22.0a0+966da7e) (1.3.0) 2025-07-17T07:05:53.6091001Z Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from jinja2->torch->torchvision==0.22.0a0+966da7e) (3.0.2) 2025-07-17T07:05:53.6178867Z Building wheels for collected packages: torchvision 2025-07-17T07:05:53.6229734Z  DEPRECATION: Building 'torchvision' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'torchvision'. Discussion can be found at https://github.com/pypa/pip/issues/6334 2025-07-17T07:07:31.4663716Z  Building wheel for torchvision (setup.py) ... [?25l- \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ done 2025-07-17T07:07:31.4665225Z [?25h Created wheel for torchvision: filename=torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl size=1199170 sha256=1cf06cdd5d9e0a7071a48396002e850d672cc85543af8e0b57021e15611d01b0 2025-07-17T07:07:31.4666514Z Stored in directory: /var/lib/jenkins/.cache/pip/wheels/89/53/07/16d05bff0990e585bfa232438657da6e5e4f6d0cea71bd3e09 2025-07-17T07:07:31.4667193Z Successfully built torchvision 2025-07-17T07:07:31.6109871Z Installing collected packages: torchvision 2025-07-17T07:07:32.0701630Z Successfully installed torchvision-0.22.0a0+966da7e 2025-07-17T07:07:32.1686469Z + '[' -n '' ']' 2025-07-17T07:07:32.1686851Z + test_dynamo_wrapped_shard 2 2025-07-17T07:07:32.1687374Z + [[ -z 3 ]] 2025-07-17T07:07:32.1687875Z + python tools/dynamo/verify_dynamo.py 2025-07-17T07:07:33.2756370Z Python version: 3.13.5 2025-07-17T07:07:33.2757200Z `torch` version: 2.9.0a0+gita38f433 2025-07-17T07:07:33.2757498Z CUDA version: None 2025-07-17T07:07:33.2757865Z ROCM version: None 2025-07-17T07:07:33.2758013Z 2025-07-17T07:07:33.2758644Z /var/lib/jenkins/workspace/tools/dynamo/verify_dynamo.py:220: UserWarning: Dynamo not yet supported in Python 3.13. Skipping check. 2025-07-17T07:07:33.2759659Z warnings.warn("Dynamo not yet supported in Python 3.13. Skipping check.") 2025-07-17T07:07:33.2760187Z All required checks passed 2025-07-17T07:07:33.5217621Z + python tools/dynamo/gb_id_mapping.py verify 2025-07-17T07:07:38.2349441Z All unimplemented_v2 calls match the registry. 2025-07-17T07:07:38.6403688Z + python test/run_test.py --dynamo --exclude-inductor-tests --exclude-jit-executor --exclude-distributed-tests --exclude-torch-export-tests --exclude-aot-dispatch-tests --shard 2 3 --verbose --upload-artifacts-while-running 2025-07-17T07:07:41.1728505Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T07:07:41.1730092Z import pkg_resources 2025-07-17T07:07:42.8007241Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-07-17T07:07:42.8554770Z Ignoring disabled issues: [''] 2025-07-17T07:07:42.8826566Z Found test times from artifacts 2025-07-17T07:07:42.9876048Z Found test times from artifacts 2025-07-17T07:07:42.9913760Z Running all tests 2025-07-17T07:07:43.0074592Z Running parallel tests on 3 processes 2025-07-17T07:07:43.0084679Z Name: tests to run (est. time: 125.09min) 2025-07-17T07:07:43.0085238Z Serial tests (14): 2025-07-17T07:07:43.0085739Z test_reductions 1/6 2025-07-17T07:07:43.0086220Z test_reductions 3/6 2025-07-17T07:07:43.0086495Z test_reductions 5/6 2025-07-17T07:07:43.0086749Z doctests 1/1 2025-07-17T07:07:43.0086992Z test_namedtuple_return_api 1/1 2025-07-17T07:07:43.0087287Z test_nn 1/4 2025-07-17T07:07:43.0087512Z test_nn 3/4 2025-07-17T07:07:43.0087733Z test_spectral_ops 1/1 2025-07-17T07:07:43.0088026Z distributions/test_distributions 1/3 2025-07-17T07:07:43.0088371Z distributions/test_distributions 3/3 2025-07-17T07:07:43.0088738Z test_cpp_extensions_open_device_registration 1/1 2025-07-17T07:07:43.0089119Z test_transformers_privateuse1 1/1 2025-07-17T07:07:43.0089433Z test_openreg 1/1 2025-07-17T07:07:43.0089664Z test_fx 1/1 2025-07-17T07:07:43.0089968Z Parallel tests (161): 2025-07-17T07:07:43.0090263Z dynamo/test_activation_checkpointing 1/1 2025-07-17T07:07:43.0090617Z dynamo/test_precompile_context 1/1 2025-07-17T07:07:43.0090937Z test_quantization 9/9 2025-07-17T07:07:43.0091186Z test_linalg 4/5 2025-07-17T07:07:43.0091420Z test_linalg 5/5 2025-07-17T07:07:43.0091677Z dynamo/cpython/3_13/test_list 1/1 2025-07-17T07:07:43.0091974Z functorch/test_vmap 1/4 2025-07-17T07:07:43.0092253Z test_nestedtensor 1/1 2025-07-17T07:07:43.0092520Z test_binary_ufuncs 1/4 2025-07-17T07:07:43.0092777Z test_binary_ufuncs 2/4 2025-07-17T07:07:43.0093041Z test_foreach 1/1 2025-07-17T07:07:43.0093322Z dynamo/cpython/3_13/test_generator_stop 1/1 2025-07-17T07:07:43.0093706Z dynamo/cpython/3_13/test_exception_variations 1/1 2025-07-17T07:07:43.0094092Z dynamo/cpython/3_13/test_int_literal 1/1 2025-07-17T07:07:43.0094427Z dynamo/cpython/3_13/test_with 1/1 2025-07-17T07:07:43.0094763Z dynamo/cpython/3_13/test_numeric_tower 1/1 2025-07-17T07:07:43.0095112Z dynamo/cpython/3_13/test_ordered_dict 1/1 2025-07-17T07:07:43.0095473Z dynamo/cpython/3_13/test_baseexception 1/1 2025-07-17T07:07:43.0095815Z dynamo/cpython/3_13/test_int 1/1 2025-07-17T07:07:43.0096122Z dynamo/cpython/3_13/test_itertools 1/1 2025-07-17T07:07:43.0097147Z dynamo/cpython/3_13/test_userlist 1/1 2025-07-17T07:07:43.0097480Z dynamo/cpython/3_13/test_cmath 1/1 2025-07-17T07:07:43.0097791Z dynamo/cpython/3_13/test_math 1/1 2025-07-17T07:07:43.0098112Z dynamo/cpython/3_13/test_operator 1/1 2025-07-17T07:07:43.0098446Z dynamo/cpython/3_13/test_userdict 1/1 2025-07-17T07:07:43.0098759Z dynamo/cpython/3_13/test_set 1/1 2025-07-17T07:07:43.0099095Z dynamo/cpython/3_13/test_iter 1/1 2025-07-17T07:07:43.0099399Z dynamo/cpython/3_13/test_bool 1/1 2025-07-17T07:07:43.0099712Z dynamo/cpython/3_13/test_sort 1/1 2025-07-17T07:07:43.0100027Z dynamo/cpython/3_13/test_float 1/1 2025-07-17T07:07:43.0100331Z dynamo/cpython/3_13/test_dict 1/1 2025-07-17T07:07:43.0100755Z dynamo/cpython/3_13/test_complex 1/1 2025-07-17T07:07:43.0101092Z dynamo/cpython/3_13/test_tuple 1/1 2025-07-17T07:07:43.0101383Z test_package 1/1 2025-07-17T07:07:43.0101630Z test_decomp 1/1 2025-07-17T07:07:43.0101873Z test_autoload 1/1 2025-07-17T07:07:43.0102127Z test_utils_config_module 1/1 2025-07-17T07:07:43.0102419Z test_mkl_verbose 1/1 2025-07-17T07:07:43.0102697Z dynamo/test_deque_reconstruct 1/1 2025-07-17T07:07:43.0103002Z test_license 1/1 2025-07-17T07:07:43.0103240Z test_mkldnn_verbose 1/1 2025-07-17T07:07:43.0103584Z dynamo/cpython/3_13/test_unittest/test_assertions 1/1 2025-07-17T07:07:43.0103976Z test_comparison_utils 1/1 2025-07-17T07:07:43.0104235Z test_ops 1/1 2025-07-17T07:07:43.0104482Z typing/test_python_operators 1/1 2025-07-17T07:07:43.0104801Z torch_np/test_nep50_examples 1/1 2025-07-17T07:07:43.0105088Z test_ops_jit 1/1 2025-07-17T07:07:43.0105354Z dynamo/test_skip_guard_eval_unsafe 1/1 2025-07-17T07:07:43.0105686Z functorch/test_ac_logging 1/1 2025-07-17T07:07:43.0105967Z test_custom_ops 1/1 2025-07-17T07:07:43.0106224Z dynamo/test_interop 1/1 2025-07-17T07:07:43.0106502Z dynamo/test_resume 1/1 2025-07-17T07:07:43.0106757Z dynamo/test_sdpa 1/1 2025-07-17T07:07:43.0107025Z dynamo/test_utils 1/1 2025-07-17T07:07:43.0107301Z profiler/test_kineto 1/1 2025-07-17T07:07:43.0107576Z test_fx_experimental 1/1 2025-07-17T07:07:43.0107866Z dynamo/test_pre_dispatch 1/1 2025-07-17T07:07:43.0108355Z cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 2025-07-17T07:07:43.0108827Z dynamo/test_dynamic_shapes 1/1 2025-07-17T07:07:43.0109120Z dynamo/test_functions 1/1 2025-07-17T07:07:43.0109403Z dynamo/test_after_aot 1/1 2025-07-17T07:07:43.0109672Z test_optim 2/3 2025-07-17T07:07:43.0109893Z test_optim 3/3 2025-07-17T07:07:43.0110136Z test_per_overload_api 1/1 2025-07-17T07:07:43.0110422Z test_expanded_weights 1/1 2025-07-17T07:07:43.0110698Z lazy/test_bindings 1/1 2025-07-17T07:07:43.0111012Z dynamo/test_cudagraphs_expandable_segments 1/1 2025-07-17T07:07:43.0111373Z test_native_functions 1/1 2025-07-17T07:07:43.0111638Z test_type_hints 1/1 2025-07-17T07:07:43.0111896Z dynamo/test_export 1/1 2025-07-17T07:07:43.0112171Z test_import_stats 1/1 2025-07-17T07:07:43.0112425Z test_module_tracker 1/1 2025-07-17T07:07:43.0112695Z test_fx_passes 1/1 2025-07-17T07:07:43.0112954Z dynamo/test_unittest 1/1 2025-07-17T07:07:43.0113230Z test_logging 1/1 2025-07-17T07:07:43.0113464Z torch_np/test_basic 1/1 2025-07-17T07:07:43.0113744Z 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nn/test_load_state_dict 1/1 2025-07-17T07:07:43.0135338Z test_indexing 1/1 2025-07-17T07:07:43.0135628Z torch_np/numpy_tests/lib/test_index_tricks 1/1 2025-07-17T07:07:43.0136004Z torch_np/numpy_tests/core/test_dlpack 1/1 2025-07-17T07:07:43.0136359Z torch_np/numpy_tests/lib/test_arraypad 1/1 2025-07-17T07:07:43.0136698Z lazy/test_debug_util 1/1 2025-07-17T07:07:43.0136996Z test_xnnpack_integration 1/1 2025-07-17T07:07:43.0137272Z test_sparse_csr 1/2 2025-07-17T07:07:43.0137529Z test_unary_ufuncs 3/3 2025-07-17T07:07:43.0137897Z nn/test_init 1/1 2025-07-17T07:07:43.0138136Z test_function_schema 1/1 2025-07-17T07:07:43.0138455Z torch_np/numpy_tests/core/test_scalar_ctors 1/1 2025-07-17T07:07:43.0138803Z test_sparse 1/2 2025-07-17T07:07:43.0139039Z torch_np/test_reductions 1/1 2025-07-17T07:07:43.0139347Z profiler/test_profiler_tree 1/1 2025-07-17T07:07:43.0139658Z test_type_promotion 1/1 2025-07-17T07:07:43.0139943Z dynamo/test_python_autograd 1/1 2025-07-17T07:07:43.0140243Z Name: excluded (est. time: 0.0min) 2025-07-17T07:07:43.0140536Z Serial tests (0): 2025-07-17T07:07:43.0140780Z Parallel tests (0): 2025-07-17T07:07:43.0141183Z Running test_reductions 1/6 ... [2025-07-17 07:07:43.011834] 2025-07-17T07:07:43.0141596Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T07:07:43.0142647Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_reductions.py', '--shard-id=1', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:07:43.012189] 2025-07-17T07:31:34.9804246Z 2025-07-17T07:31:34.9805548Z test_reductions 1/6 was successful, full logs can be found in artifacts with path test/test-reports/test_reductions_1.6_5736ebc8c30378de_.log 2025-07-17T07:31:35.0305028Z Running 773 items in this shard: test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_amin_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_aminmax_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_argminmax_large_axis_cpu, test/test_reductions.py::TestReductionsCPU::test_argminmax_multiple_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_bincount_cpu, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_uint8, 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test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_sum_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_var_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_var_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_mean_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_mean_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_nansum_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_nansum_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_nansum_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_prod_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_std_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_sum_cpu_int16, 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test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_std_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_sum_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_all_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_all_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_amin_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_amin_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_amin_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_any_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_argmax_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_argmax_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_argmin_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_argmin_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_count_nonzero_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_linalg_vector_norm_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_linalg_vector_norm_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_amin_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_amin_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_argmax_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_logsumexp_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_mean_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_prod_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_prod_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_std_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_sum_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_sum_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_sum_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_sum_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_sum_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_mean_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_mean_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_std_correction_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_std_mean_correction_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_std_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_std_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_all_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_cpu_device_mismatch_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_dim_reduction_uint8_overflow_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_tensor_compare_ops_argmax_argmix_kthvalue_dim_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_var_large_input_cpu, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_float64 2025-07-17T07:31:35.0713985Z 2025-07-17T07:31:35.4506551Z Uploading artifacts took 0.47 seconds 2025-07-17T07:31:35.4509268Z Running test_reductions 3/6 ... [2025-07-17 07:31:35.450741] 2025-07-17T07:31:35.4509743Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T07:31:35.4513510Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_reductions.py', '--shard-id=3', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:31:35.451096] 2025-07-17T07:34:02.2327296Z 2025-07-17T07:34:02.2328508Z test_reductions 3/6 was successful, full logs can be found in artifacts with path test/test-reports/test_reductions_3.6_01e195621fb2bf91_.log 2025-07-17T07:34:02.2637429Z Running 796 items in this shard: test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_all_issue117215_cpu, test/test_reductions.py::TestReductionsCPU::test_amax_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_amin_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_int32, 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test/test_reductions.py::TestReductionsCPU::test_ref_small_input_argmin_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_argmin_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_count_nonzero_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_count_nonzero_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_amax_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_argmax_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_argmax_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_argmin_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_argmin_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_argmin_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_mean_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_std_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_var_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_masked_var_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_mean_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_mean_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_nanmean_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_prod_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_prod_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_prod_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_ref_small_input_var_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_amin_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_argmax_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_argmax_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_prod_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_prod_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_prod_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_std_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_std_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_sum_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_sum_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_var_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_var_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_var_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_var_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_var_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_all_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_amax_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_amax_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_amin_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_any_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_any_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_any_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_count_nonzero_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_mean_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_mean_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_sum_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_sum_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_sum_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_var_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_var_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_var_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_all_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_all_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_all_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_amin_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_amin_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_any_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_any_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_any_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_argmax_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_argmax_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_argmin_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_count_nonzero_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_count_nonzero_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_amax_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_amax_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_amax_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_amin_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_argmax_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_argmax_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_argmin_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_argmin_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_argmin_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_argmin_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_logsumexp_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_logsumexp_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_logsumexp_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_mean_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_mean_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_prod_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_std_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_std_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_std_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_sum_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nanmean_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_std_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_sum_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_integer_upcast_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_noncontig_lowp_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_sum_out_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_var_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_float32 2025-07-17T07:34:02.2936297Z 2025-07-17T07:34:02.2936517Z Running test_reductions 5/6 ... [2025-07-17 07:34:02.234255] 2025-07-17T07:34:02.2936919Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T07:34:02.2937962Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_reductions.py', '--shard-id=5', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:34:02.234611] 2025-07-17T07:36:39.0686568Z 2025-07-17T07:36:39.0687401Z test_reductions 5/6 was successful, full logs can be found in artifacts with path test/test-reports/test_reductions_5.6_c46efa44d2f9a6cd_.log 2025-07-17T07:36:39.0984103Z Running 769 items in this shard: test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_all_any_with_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_amax_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_amax_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_amin_amax_some_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_amin_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_aminmax_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_aminmax_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_argminmax_axis_with_dim_one_cpu, test/test_reductions.py::TestReductionsCPU::test_argminmax_multiple_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_argminmax_multiple_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_sum_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_any_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_all_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_prod_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_masked_amin_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_prod_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_var_unbiased_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty__refs_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty__refs_prod_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty_all_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty_amax_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty_keepdim__refs_all_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty_keepdim_amin_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty_keepdim_linalg_vector_norm_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty_keepdim_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty_keepdim_sum_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty_keepdim_var_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_empty_var_unbiased_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi__refs_linalg_vector_norm_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_all_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_count_nonzero_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_duplicate__refs_count_nonzero_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_duplicate_count_nonzero_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_duplicate_masked_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_duplicate_masked_norm_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_duplicate_var_unbiased_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_keepdim__refs_amin_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_keepdim_count_nonzero_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_keepdim_masked_amin_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_keepdim_nansum_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_multi_keepdim_std_cpu, 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test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_mean_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_prod_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_prod_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_std_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_std_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_std_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_sum_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_reference_masked_masked_sum_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_all_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_all_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_all_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_amax_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_amax_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_amax_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_amax_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_amin_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_amin_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_count_nonzero_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_count_nonzero_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_prod_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_std_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_std_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_std_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_sum_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype__refs_var_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_all_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_all_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_amax_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_amax_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_amin_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_result_dtype_amin_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_any_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_result_dtype_any_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_argmax_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_argmax_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_argmin_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_argmin_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_linalg_vector_norm_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_linalg_vector_norm_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_amax_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_amin_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_amin_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_argmax_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_argmax_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_argmin_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_argmin_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_logsumexp_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_logsumexp_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_mean_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_mean_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_norm_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_prod_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_prod_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_prod_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_prod_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_sum_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_mean_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nanmean_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_std_correction_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_std_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_var_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_complex64 2025-07-17T07:36:39.1270369Z 2025-07-17T07:36:39.1270545Z Running doctests 1/1 ... [2025-07-17 07:36:39.069952] 2025-07-17T07:36:39.1591714Z Start doctest_module('/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch') 2025-07-17T07:36:39.1594637Z Listing tests 2025-07-17T07:36:39.3747069Z msg = Cannot scrape callname=Tensor.dim_order in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py line=1493. 2025-07-17T07:36:39.3748013Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.3748416Z 2025-07-17T07:36:39.3748560Z dim_order(ambiguity_check=False) -> tuple 2025-07-17T07:36:39.3748789Z 2025-07-17T07:36:39.3749021Z Returns the uniquely determined tuple of int describing the dim order or 2025-07-17T07:36:39.3749487Z physical layout of :attr:`self`. 2025-07-17T07:36:39.3749696Z 2025-07-17T07:36:39.3749963Z The dim order represents how dimensions are laid out in memory of dense tensors, 2025-07-17T07:36:39.3750497Z starting from the outermost to the innermost dimension. 2025-07-17T07:36:39.3750788Z 2025-07-17T07:36:39.3750972Z Note that the dim order may not always be uniquely determined. 2025-07-17T07:36:39.3751663Z If `ambiguity_check` is True, this function raises a RuntimeError when the dim order cannot be uniquely determined; 2025-07-17T07:36:39.3752565Z If `ambiguity_check` is a list of memory formats, this function raises a RuntimeError when tensor can not be interpreted 2025-07-17T07:36:39.3753333Z into exactly one of the given memory formats, or it cannot be uniquely determined. 2025-07-17T07:36:39.3754035Z If `ambiguity_check` is False, it will return one of legal dim order(s) without checking its uniqueness. 2025-07-17T07:36:39.3754589Z Otherwise, it will raise TypeError. 2025-07-17T07:36:39.3754797Z 2025-07-17T07:36:39.3755133Z Args: 2025-07-17T07:36:39.3755562Z ambiguity_check (bool or List[torch.memory_format]): The check method for ambiguity of dim order. 2025-07-17T07:36:39.3756010Z 2025-07-17T07:36:39.3756131Z Examples:: 2025-07-17T07:36:39.3756256Z 2025-07-17T07:36:39.3756380Z >>> torch.empty((2, 3, 5, 7)).dim_order() 2025-07-17T07:36:39.3756673Z (0, 1, 2, 3) 2025-07-17T07:36:39.3756967Z >>> torch.empty((2, 3, 5, 7)).transpose(1, 2).dim_order() 2025-07-17T07:36:39.3757329Z (0, 2, 1, 3) 2025-07-17T07:36:39.3757673Z >>> torch.empty((2, 3, 5, 7), memory_format=torch.channels_last).dim_order() 2025-07-17T07:36:39.3758070Z (0, 2, 3, 1) 2025-07-17T07:36:39.3758422Z >>> torch.empty((1, 2, 3, 4)).dim_order() 2025-07-17T07:36:39.3758730Z (0, 1, 2, 3) 2025-07-17T07:36:39.3758938Z >>> try: 2025-07-17T07:36:39.3759239Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check=True) 2025-07-17T07:36:39.3759637Z ... except RuntimeError as e: 2025-07-17T07:36:39.3759916Z ... print(e) 2025-07-17T07:36:39.3760385Z The tensor does not have unique dim order, or cannot map to exact one of the given memory formats. 2025-07-17T07:36:39.3760933Z >>> torch.empty((1, 2, 3, 4)).dim_order( 2025-07-17T07:36:39.3761353Z ... ambiguity_check=[torch.contiguous_format, torch.channels_last] 2025-07-17T07:36:39.3761807Z ... ) # It can be mapped to contiguous format 2025-07-17T07:36:39.3762131Z (0, 1, 2, 3) 2025-07-17T07:36:39.3762353Z >>> try: 2025-07-17T07:36:39.3762645Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check="ILLEGAL") 2025-07-17T07:36:39.3763049Z ... except TypeError as e: 2025-07-17T07:36:39.3763328Z ... print(e) 2025-07-17T07:36:39.3763696Z The ambiguity_check argument must be a bool or a list of memory formats. 2025-07-17T07:36:39.3764055Z 2025-07-17T07:36:39.3764141Z .. warning:: 2025-07-17T07:36:39.3764464Z The dim_order tensor API is experimental and subject to change. 2025-07-17T07:36:39.3764773Z 2025-07-17T07:36:39.3765025Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.3765491Z 2025-07-17T07:36:39.4287416Z msg = Cannot scrape callname=meshgrid in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=446. 2025-07-17T07:36:39.4288507Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.4289156Z Creates grids of coordinates specified by the 1D inputs in `attr`:tensors. 2025-07-17T07:36:39.4289511Z 2025-07-17T07:36:39.4289722Z This is helpful when you want to visualize data over some 2025-07-17T07:36:39.4290165Z range of inputs. See below for a plotting example. 2025-07-17T07:36:39.4290443Z 2025-07-17T07:36:39.4290604Z Given :math:`N` 1D tensors :math:`T_0 \ldots T_{N-1}` as 2025-07-17T07:36:39.4291074Z inputs with corresponding sizes :math:`S_0 \ldots S_{N-1}`, 2025-07-17T07:36:39.4291567Z this creates :math:`N` N-dimensional tensors :math:`G_0 \ldots 2025-07-17T07:36:39.4292031Z G_{N-1}`, each with shape :math:`(S_0, ..., S_{N-1})` where 2025-07-17T07:36:39.4292489Z the output :math:`G_i` is constructed by expanding :math:`T_i` 2025-07-17T07:36:39.4292896Z to the result shape. 2025-07-17T07:36:39.4293072Z 2025-07-17T07:36:39.4293186Z .. note:: 2025-07-17T07:36:39.4293480Z 0D inputs are treated equivalently to 1D inputs of a 2025-07-17T07:36:39.4293849Z single element. 2025-07-17T07:36:39.4294018Z 2025-07-17T07:36:39.4294114Z .. warning:: 2025-07-17T07:36:39.4294455Z `torch.meshgrid(*tensors)` currently has the same behavior 2025-07-17T07:36:39.4294959Z as calling `numpy.meshgrid(*arrays, indexing='ij')`. 2025-07-17T07:36:39.4295229Z 2025-07-17T07:36:39.4304065Z In the future `torch.meshgrid` will transition to 2025-07-17T07:36:39.4304751Z `indexing='xy'` as the default. 2025-07-17T07:36:39.4304995Z 2025-07-17T07:36:39.4305198Z https://github.com/pytorch/pytorch/issues/50276 tracks 2025-07-17T07:36:39.4306118Z this issue with the goal of migrating to NumPy's behavior. 2025-07-17T07:36:39.4306501Z 2025-07-17T07:36:39.4306677Z .. seealso:: 2025-07-17T07:36:39.4306827Z 2025-07-17T07:36:39.4307070Z :func:`torch.cartesian_prod` has the same effect but it 2025-07-17T07:36:39.4307549Z collects the data in a tensor of vectors. 2025-07-17T07:36:39.4307789Z 2025-07-17T07:36:39.4307888Z Args: 2025-07-17T07:36:39.4308335Z tensors (list of Tensor): list of scalars or 1 dimensional tensors. Scalars will be 2025-07-17T07:36:39.4309147Z treated as tensors of size :math:`(1,)` automatically 2025-07-17T07:36:39.4309708Z 2025-07-17T07:36:39.4309999Z indexing: (str, optional): the indexing mode, either "xy" 2025-07-17T07:36:39.4310723Z or "ij", defaults to "ij". See warning for future changes. 2025-07-17T07:36:39.4311219Z 2025-07-17T07:36:39.4311525Z If "xy" is selected, the first dimension corresponds 2025-07-17T07:36:39.4312023Z to the cardinality of the second input and the second 2025-07-17T07:36:39.4312472Z dimension corresponds to the cardinality of the first 2025-07-17T07:36:39.4312849Z input. 2025-07-17T07:36:39.4313001Z 2025-07-17T07:36:39.4313146Z If "ij" is selected, the dimensions are in the same 2025-07-17T07:36:39.4313544Z order as the cardinality of the inputs. 2025-07-17T07:36:39.4313782Z 2025-07-17T07:36:39.4313882Z Returns: 2025-07-17T07:36:39.4314177Z seq (sequence of Tensors): If the input has :math:`N` 2025-07-17T07:36:39.4314617Z tensors of size :math:`S_0 \ldots S_{N-1}``, then the 2025-07-17T07:36:39.4315074Z output will also have :math:`N` tensors, where each tensor 2025-07-17T07:36:39.4315494Z is of shape :math:`(S_0, ..., S_{N-1})`. 2025-07-17T07:36:39.4315723Z 2025-07-17T07:36:39.4315823Z Example:: 2025-07-17T07:36:39.4315971Z 2025-07-17T07:36:39.4316080Z >>> x = torch.tensor([1, 2, 3]) 2025-07-17T07:36:39.4316402Z >>> y = torch.tensor([4, 5, 6]) 2025-07-17T07:36:39.4316610Z 2025-07-17T07:36:39.4316798Z Observe the element-wise pairings across the grid, (1, 4), 2025-07-17T07:36:39.4317233Z (1, 5), ..., (3, 6). This is the same thing as the 2025-07-17T07:36:39.4317584Z cartesian product. 2025-07-17T07:36:39.4317930Z >>> grid_x, grid_y = torch.meshgrid(x, y, indexing='ij') 2025-07-17T07:36:39.4318278Z >>> grid_x 2025-07-17T07:36:39.4318533Z tensor([[1, 1, 1], 2025-07-17T07:36:39.4318812Z [2, 2, 2], 2025-07-17T07:36:39.4319063Z [3, 3, 3]]) 2025-07-17T07:36:39.4319325Z >>> grid_y 2025-07-17T07:36:39.4319571Z tensor([[4, 5, 6], 2025-07-17T07:36:39.4319824Z [4, 5, 6], 2025-07-17T07:36:39.4320093Z [4, 5, 6]]) 2025-07-17T07:36:39.4320264Z 2025-07-17T07:36:39.4320444Z This correspondence can be seen when these grids are 2025-07-17T07:36:39.4320820Z stacked properly. 2025-07-17T07:36:39.4321203Z >>> torch.equal(torch.cat(tuple(torch.dstack([grid_x, grid_y]))), 2025-07-17T07:36:39.4321655Z ... torch.cartesian_prod(x, y)) 2025-07-17T07:36:39.4321981Z True 2025-07-17T07:36:39.4322113Z 2025-07-17T07:36:39.4322287Z `torch.meshgrid` is commonly used to produce a grid for 2025-07-17T07:36:39.4322665Z plotting. 2025-07-17T07:36:39.4322956Z >>> # xdoctest: +REQUIRES(module:matplotlib) 2025-07-17T07:36:39.4323318Z >>> # xdoctest: +REQUIRES(env:DOCTEST_SHOW) 2025-07-17T07:36:39.4323685Z >>> import matplotlib.pyplot as plt 2025-07-17T07:36:39.4324051Z >>> xs = torch.linspace(-5, 5, steps=100) 2025-07-17T07:36:39.4324405Z >>> ys = torch.linspace(-5, 5, steps=100) 2025-07-17T07:36:39.4324895Z >>> x, y = torch.meshgrid(xs, ys, indexing='xy') 2025-07-17T07:36:39.4325273Z >>> z = torch.sin(torch.sqrt(x * x + y * y)) 2025-07-17T07:36:39.4325744Z >>> ax = plt.axes(projection='3d') 2025-07-17T07:36:39.4326114Z >>> ax.plot_surface(x.numpy(), y.numpy(), z.numpy()) 2025-07-17T07:36:39.4326478Z >>> plt.show() 2025-07-17T07:36:39.4326643Z 2025-07-17T07:36:39.4326781Z .. image:: ../_static/img/meshgrid.png 2025-07-17T07:36:39.4327089Z :width: 512 2025-07-17T07:36:39.4327256Z 2025-07-17T07:36:39.4327340Z 2025-07-17T07:36:39.4327785Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.4328155Z 2025-07-17T07:36:39.4328704Z msg = Cannot scrape callname=_unique_impl in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=842. 2025-07-17T07:36:39.4329573Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.4330341Z unique(input, sorted=True, return_inverse=False, return_counts=False, dim=None) -> tuple[Tensor, Tensor, Tensor] 2025-07-17T07:36:39.4330835Z 2025-07-17T07:36:39.4330984Z Returns the unique elements of the input tensor. 2025-07-17T07:36:39.4331254Z 2025-07-17T07:36:39.4331541Z .. note:: This function is different from :func:`torch.unique_consecutive` in the sense that 2025-07-17T07:36:39.4332160Z this function also eliminates non-consecutive duplicate values. 2025-07-17T07:36:39.4332480Z 2025-07-17T07:36:39.4332718Z .. note:: Currently in the CUDA implementation and the CPU implementation, 2025-07-17T07:36:39.4333345Z `torch.unique` always sort the tensor at the beginning regardless of the `sort` argument. 2025-07-17T07:36:39.4334036Z Sorting could be slow, so if your input tensor is already sorted, it is recommended to use 2025-07-17T07:36:39.4334621Z :func:`torch.unique_consecutive` which avoids the sorting. 2025-07-17T07:36:39.4334913Z 2025-07-17T07:36:39.4335008Z Args: 2025-07-17T07:36:39.4335228Z input (Tensor): the input tensor 2025-07-17T07:36:39.4335661Z sorted (bool): Whether to sort the unique elements in ascending order 2025-07-17T07:36:39.4336102Z before returning as output. 2025-07-17T07:36:39.4336512Z return_inverse (bool): Whether to also return the indices for where 2025-07-17T07:36:39.4337129Z elements in the original input ended up in the returned unique list. 2025-07-17T07:36:39.4337685Z return_counts (bool): Whether to also return the counts for each unique 2025-07-17T07:36:39.4338111Z element. 2025-07-17T07:36:39.4338459Z dim (int, optional): the dimension to operate upon. If ``None``, the 2025-07-17T07:36:39.4338986Z unique of the flattened input is returned. Otherwise, each of the 2025-07-17T07:36:39.4339514Z tensors indexed by the given dimension is treated as one of the 2025-07-17T07:36:39.4340041Z elements to apply the unique operation upon. See examples for more 2025-07-17T07:36:39.4340481Z details. Default: ``None`` 2025-07-17T07:36:39.4340699Z 2025-07-17T07:36:39.4340781Z Returns: 2025-07-17T07:36:39.4341204Z (Tensor, Tensor (optional), Tensor (optional)): A tensor or a tuple of tensors containing 2025-07-17T07:36:39.4341605Z 2025-07-17T07:36:39.4341792Z - **output** (*Tensor*): the output list of unique scalar elements. 2025-07-17T07:36:39.4342246Z - **inverse_indices** (*Tensor*): (optional) if 2025-07-17T07:36:39.4342693Z :attr:`return_inverse` is True, there will be an additional 2025-07-17T07:36:39.4343184Z returned tensor (same shape as input) representing the indices 2025-07-17T07:36:39.4343707Z for where elements in the original input map to in the output; 2025-07-17T07:36:39.4344207Z otherwise, this function will only return a single tensor. 2025-07-17T07:36:39.4344692Z - **counts** (*Tensor*): (optional) if 2025-07-17T07:36:39.4345090Z :attr:`return_counts` is True, there will be an additional 2025-07-17T07:36:39.4345573Z returned tensor (same shape as output or output.size(dim), 2025-07-17T07:36:39.4346065Z if dim was specified) representing the number of occurrences 2025-07-17T07:36:39.4346473Z for each unique value or tensor. 2025-07-17T07:36:39.4346712Z 2025-07-17T07:36:39.4346803Z Example:: 2025-07-17T07:36:39.4346943Z 2025-07-17T07:36:39.4347151Z >>> output = torch.unique(torch.tensor([1, 3, 2, 3], dtype=torch.long)) 2025-07-17T07:36:39.4347573Z >>> output 2025-07-17T07:36:39.4347851Z tensor([1, 2, 3]) 2025-07-17T07:36:39.4348031Z 2025-07-17T07:36:39.4348154Z >>> output, inverse_indices = torch.unique( 2025-07-17T07:36:39.4348632Z ... torch.tensor([1, 3, 2, 3], dtype=torch.long), sorted=True, return_inverse=True) 2025-07-17T07:36:39.4349064Z >>> output 2025-07-17T07:36:39.4349296Z tensor([1, 2, 3]) 2025-07-17T07:36:39.4349561Z >>> inverse_indices 2025-07-17T07:36:39.4349830Z tensor([0, 2, 1, 2]) 2025-07-17T07:36:39.4350001Z 2025-07-17T07:36:39.4350125Z >>> output, inverse_indices = torch.unique( 2025-07-17T07:36:39.4350601Z ... torch.tensor([[1, 3], [2, 3]], dtype=torch.long), sorted=True, return_inverse=True) 2025-07-17T07:36:39.4351084Z >>> output 2025-07-17T07:36:39.4351305Z tensor([1, 2, 3]) 2025-07-17T07:36:39.4351568Z >>> inverse_indices 2025-07-17T07:36:39.4351834Z tensor([[0, 2], 2025-07-17T07:36:39.4352065Z [1, 2]]) 2025-07-17T07:36:39.4352233Z 2025-07-17T07:36:39.4352330Z >>> a = torch.tensor([ 2025-07-17T07:36:39.4352595Z ... [ 2025-07-17T07:36:39.4352844Z ... [1, 1, 0, 0], 2025-07-17T07:36:39.4353122Z ... [1, 1, 0, 0], 2025-07-17T07:36:39.4353394Z ... [0, 0, 1, 1], 2025-07-17T07:36:39.4353664Z ... ], 2025-07-17T07:36:39.4353873Z ... [ 2025-07-17T07:36:39.4354099Z ... [0, 0, 1, 1], 2025-07-17T07:36:39.4354375Z ... [0, 0, 1, 1], 2025-07-17T07:36:39.4354633Z ... [1, 1, 1, 1], 2025-07-17T07:36:39.4354897Z ... ], 2025-07-17T07:36:39.4355119Z ... [ 2025-07-17T07:36:39.4355333Z ... [1, 1, 0, 0], 2025-07-17T07:36:39.4355606Z ... [1, 1, 0, 0], 2025-07-17T07:36:39.4355878Z ... [0, 0, 1, 1], 2025-07-17T07:36:39.4356131Z ... ], 2025-07-17T07:36:39.4356357Z ... ]) 2025-07-17T07:36:39.4356483Z 2025-07-17T07:36:39.4356712Z >>> # If we call `torch.unique(a, dim=0)`, each of the tensors `a[idx, :, :]` 2025-07-17T07:36:39.4357258Z >>> # will be compared. We can see that `a[0, :, :]` and `a[2, :, :]` match 2025-07-17T07:36:39.4357709Z >>> # each other, so one of them will be removed. 2025-07-17T07:36:39.4358069Z >>> (a[0, :, :] == a[2, :, :]).all() 2025-07-17T07:36:39.4358375Z tensor(True) 2025-07-17T07:36:39.4358636Z >>> a_unique_dim0 = torch.unique(a, dim=0) 2025-07-17T07:36:39.4358969Z >>> a_unique_dim0 2025-07-17T07:36:39.4359244Z tensor([[[0, 0, 1, 1], 2025-07-17T07:36:39.4359500Z [0, 0, 1, 1], 2025-07-17T07:36:39.4359762Z [1, 1, 1, 1]], 2025-07-17T07:36:39.4360028Z [[1, 1, 0, 0], 2025-07-17T07:36:39.4360277Z [1, 1, 0, 0], 2025-07-17T07:36:39.4360539Z [0, 0, 1, 1]]]) 2025-07-17T07:36:39.4360712Z 2025-07-17T07:36:39.4360940Z >>> # Notice which sub-tensors from `a` match with the sub-tensors from 2025-07-17T07:36:39.4361358Z >>> # `a_unique_dim0`: 2025-07-17T07:36:39.4361664Z >>> (a_unique_dim0[0, :, :] == a[1, :, :]).all() 2025-07-17T07:36:39.4361986Z tensor(True) 2025-07-17T07:36:39.4362261Z >>> (a_unique_dim0[1, :, :] == a[0, :, :]).all() 2025-07-17T07:36:39.4362643Z tensor(True) 2025-07-17T07:36:39.4362800Z 2025-07-17T07:36:39.4362997Z >>> # For `torch.unique(a, dim=1)`, each of the tensors `a[:, idx, :]` are 2025-07-17T07:36:39.4363508Z >>> # compared. `a[:, 0, :]` and `a[:, 1, :]` match each other, so one of 2025-07-17T07:36:39.4363896Z >>> # them will be removed. 2025-07-17T07:36:39.4364200Z >>> (a[:, 0, :] == a[:, 1, :]).all() 2025-07-17T07:36:39.4364505Z tensor(True) 2025-07-17T07:36:39.4364746Z >>> torch.unique(a, dim=1) 2025-07-17T07:36:39.4365037Z tensor([[[0, 0, 1, 1], 2025-07-17T07:36:39.4365373Z [1, 1, 0, 0]], 2025-07-17T07:36:39.4365713Z [[1, 1, 1, 1], 2025-07-17T07:36:39.4365963Z [0, 0, 1, 1]], 2025-07-17T07:36:39.4366225Z [[0, 0, 1, 1], 2025-07-17T07:36:39.4366485Z [1, 1, 0, 0]]]) 2025-07-17T07:36:39.4366656Z 2025-07-17T07:36:39.4366860Z >>> # For `torch.unique(a, dim=2)`, the tensors `a[:, :, idx]` are compared. 2025-07-17T07:36:39.4367351Z >>> # `a[:, :, 0]` and `a[:, :, 1]` match each other. Also, `a[:, :, 2]` and 2025-07-17T07:36:39.4367802Z >>> # `a[:, :, 3]` match each other as well. So in this case, two of the 2025-07-17T07:36:39.4368195Z >>> # sub-tensors will be removed. 2025-07-17T07:36:39.4368519Z >>> (a[:, :, 0] == a[:, :, 1]).all() 2025-07-17T07:36:39.4368815Z tensor(True) 2025-07-17T07:36:39.4369065Z >>> (a[:, :, 2] == a[:, :, 3]).all() 2025-07-17T07:36:39.4369349Z tensor(True) 2025-07-17T07:36:39.4369599Z >>> torch.unique(a, dim=2) 2025-07-17T07:36:39.4369890Z tensor([[[0, 1], 2025-07-17T07:36:39.4370352Z [0, 1], 2025-07-17T07:36:39.4370596Z [1, 0]], 2025-07-17T07:36:39.4370847Z [[1, 0], 2025-07-17T07:36:39.4371074Z [1, 0], 2025-07-17T07:36:39.4371317Z [1, 1]], 2025-07-17T07:36:39.4371562Z [[0, 1], 2025-07-17T07:36:39.4371794Z [0, 1], 2025-07-17T07:36:39.4372036Z [1, 0]]]) 2025-07-17T07:36:39.4372282Z 2025-07-17T07:36:39.4372634Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.4373013Z 2025-07-17T07:36:39.4474777Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=560. 2025-07-17T07:36:39.4476316Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.4476820Z 2025-07-17T07:36:39.4477036Z Load a model from a github repo or a local directory. 2025-07-17T07:36:39.4477429Z 2025-07-17T07:36:39.4477695Z Note: Loading a model is the typical use case, but this can also be used to 2025-07-17T07:36:39.4478453Z for loading other objects such as tokenizers, loss functions, etc. 2025-07-17T07:36:39.4478787Z 2025-07-17T07:36:39.4478950Z If ``source`` is 'github', ``repo_or_dir`` is expected to be 2025-07-17T07:36:39.4479405Z of the form ``repo_owner/repo_name[:ref]`` with an optional 2025-07-17T07:36:39.4479775Z ref (a tag or a branch). 2025-07-17T07:36:39.4479955Z 2025-07-17T07:36:39.4480120Z If ``source`` is 'local', ``repo_or_dir`` is expected to be a 2025-07-17T07:36:39.4480506Z path to a local directory. 2025-07-17T07:36:39.4480679Z 2025-07-17T07:36:39.4480772Z Args: 2025-07-17T07:36:39.4481029Z repo_or_dir (str): If ``source`` is 'github', 2025-07-17T07:36:39.4481661Z this should correspond to a github repo with format ``repo_owner/repo_name[:ref]`` with 2025-07-17T07:36:39.4482476Z an optional ref (tag or branch), for example 'pytorch/vision:0.10'. If ``ref`` is not specified, 2025-07-17T07:36:39.4483150Z the default branch is assumed to be ``main`` if it exists, and otherwise ``master``. 2025-07-17T07:36:39.4483734Z If ``source`` is 'local' then it should be a path to a local directory. 2025-07-17T07:36:39.4484245Z model (str): the name of a callable (entrypoint) defined in the 2025-07-17T07:36:39.4484829Z repo/dir's ``hubconf.py``. 2025-07-17T07:36:39.4485219Z *args (optional): the corresponding args for callable ``model``. 2025-07-17T07:36:39.4485857Z source (str, optional): 'github' or 'local'. Specifies how 2025-07-17T07:36:39.4486514Z ``repo_or_dir`` is to be interpreted. Default is 'github'. 2025-07-17T07:36:39.4487082Z trust_repo (bool, str or None): ``"check"``, ``True``, ``False`` or ``None``. 2025-07-17T07:36:39.4487976Z This parameter was introduced in v1.12 and helps ensuring that users 2025-07-17T07:36:39.4488450Z only run code from repos that they trust. 2025-07-17T07:36:39.4488687Z 2025-07-17T07:36:39.4488997Z - If ``False``, a prompt will ask the user whether the repo should 2025-07-17T07:36:39.4489384Z be trusted. 2025-07-17T07:36:39.4489729Z - If ``True``, the repo will be added to the trusted list and loaded 2025-07-17T07:36:39.4490167Z without requiring explicit confirmation. 2025-07-17T07:36:39.4490574Z - If ``"check"``, the repo will be checked against the list of 2025-07-17T07:36:39.4491074Z trusted repos in the cache. If it is not present in that list, the 2025-07-17T07:36:39.4491602Z behaviour will fall back onto the ``trust_repo=False`` option. 2025-07-17T07:36:39.4492100Z - If ``None``: this will raise a warning, inviting the user to set 2025-07-17T07:36:39.4492579Z ``trust_repo`` to either ``False``, ``True`` or ``"check"``. This 2025-07-17T07:36:39.4493087Z is only present for backward compatibility and will be removed in 2025-07-17T07:36:39.4493499Z v2.0. 2025-07-17T07:36:39.4493631Z 2025-07-17T07:36:39.4493887Z Default is ``None`` and will eventually change to ``"check"`` in v2.0. 2025-07-17T07:36:39.4494406Z force_reload (bool, optional): whether to force a fresh download of 2025-07-17T07:36:39.4494920Z the github repo unconditionally. Does not have any effect if 2025-07-17T07:36:39.4495360Z ``source = 'local'``. Default is ``False``. 2025-07-17T07:36:39.4495799Z verbose (bool, optional): If ``False``, mute messages about hitting 2025-07-17T07:36:39.4496314Z local caches. Note that the message about first download cannot be 2025-07-17T07:36:39.4496809Z muted. Does not have any effect if ``source = 'local'``. 2025-07-17T07:36:39.4497193Z Default is ``True``. 2025-07-17T07:36:39.4497654Z skip_validation (bool, optional): if ``False``, torchhub will check that the branch or commit 2025-07-17T07:36:39.4498355Z specified by the ``github`` argument properly belongs to the repo owner. This will make 2025-07-17T07:36:39.4499032Z requests to the GitHub API; you can specify a non-default GitHub token by setting the 2025-07-17T07:36:39.4499602Z ``GITHUB_TOKEN`` environment variable. Default is ``False``. 2025-07-17T07:36:39.4500105Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-07-17T07:36:39.4500450Z 2025-07-17T07:36:39.4500534Z Returns: 2025-07-17T07:36:39.4500841Z The output of the ``model`` callable when called with the given 2025-07-17T07:36:39.4501235Z ``*args`` and ``**kwargs``. 2025-07-17T07:36:39.4501429Z 2025-07-17T07:36:39.4501515Z Example: 2025-07-17T07:36:39.4501771Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-07-17T07:36:39.4502116Z >>> # from a github repo 2025-07-17T07:36:39.4502384Z >>> repo = "pytorch/vision" 2025-07-17T07:36:39.4502716Z >>> model = torch.hub.load( 2025-07-17T07:36:39.4503087Z ... repo, "resnet50", weights="ResNet50_Weights.IMAGENET1K_V1" 2025-07-17T07:36:39.4503459Z ... ) 2025-07-17T07:36:39.4503683Z >>> # from a local directory 2025-07-17T07:36:39.4504001Z >>> path = "/some/local/path/pytorch/vision" 2025-07-17T07:36:39.4504328Z >>> # xdoctest: +SKIP 2025-07-17T07:36:39.4504740Z >>> model = torch.hub.load(path, "resnet50", weights="ResNet50_Weights.DEFAULT") 2025-07-17T07:36:39.4505243Z 2025-07-17T07:36:39.4505509Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.4505872Z 2025-07-17T07:36:39.4506332Z msg = Cannot scrape callname=_load_local in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=652. 2025-07-17T07:36:39.4507147Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.4507536Z 2025-07-17T07:36:39.4507708Z Load a model from a local directory with a ``hubconf.py``. 2025-07-17T07:36:39.4508002Z 2025-07-17T07:36:39.4508080Z Args: 2025-07-17T07:36:39.4508380Z hubconf_dir (str): path to a local directory that contains a 2025-07-17T07:36:39.4508760Z ``hubconf.py``. 2025-07-17T07:36:39.4509158Z model (str): name of an entrypoint defined in the directory's 2025-07-17T07:36:39.4509555Z ``hubconf.py``. 2025-07-17T07:36:39.4509899Z *args (optional): the corresponding args for callable ``model``. 2025-07-17T07:36:39.4510423Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-07-17T07:36:39.4510757Z 2025-07-17T07:36:39.4510855Z Returns: 2025-07-17T07:36:39.4511124Z a single model with corresponding pretrained weights. 2025-07-17T07:36:39.4511409Z 2025-07-17T07:36:39.4511507Z Example: 2025-07-17T07:36:39.4511750Z >>> # xdoctest: +SKIP("stub local path") 2025-07-17T07:36:39.4512105Z >>> path = "/some/local/path/pytorch/vision" 2025-07-17T07:36:39.4512427Z >>> model = _load_local( 2025-07-17T07:36:39.4512692Z ... path, 2025-07-17T07:36:39.4512923Z ... "resnet50", 2025-07-17T07:36:39.4513204Z ... weights="ResNet50_Weights.IMAGENET1K_V1", 2025-07-17T07:36:39.4513536Z ... ) 2025-07-17T07:36:39.4513653Z 2025-07-17T07:36:39.4513912Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.4514279Z 2025-07-17T07:36:39.4514771Z msg = Cannot scrape callname=download_url_to_file in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=691. 2025-07-17T07:36:39.4515622Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.4516144Z Download object at the given URL to a local path. 2025-07-17T07:36:39.4516396Z 2025-07-17T07:36:39.4516489Z Args: 2025-07-17T07:36:39.4516720Z url (str): URL of the object to download 2025-07-17T07:36:39.4517182Z dst (str): Full path where object will be saved, e.g. ``/tmp/temporary_file`` 2025-07-17T07:36:39.4517871Z hash_prefix (str, optional): If not None, the SHA256 downloaded file should start with ``hash_prefix``. 2025-07-17T07:36:39.4518416Z Default: None 2025-07-17T07:36:39.4518825Z progress (bool, optional): whether or not to display a progress bar to stderr 2025-07-17T07:36:39.4519295Z Default: True 2025-07-17T07:36:39.4519458Z 2025-07-17T07:36:39.4519555Z Example: 2025-07-17T07:36:39.4519836Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-07-17T07:36:39.4520224Z >>> # xdoctest: +REQUIRES(POSIX) 2025-07-17T07:36:39.4520564Z >>> torch.hub.download_url_to_file( 2025-07-17T07:36:39.4521008Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth", 2025-07-17T07:36:39.4521450Z ... "/tmp/temporary_file", 2025-07-17T07:36:39.4521743Z ... ) 2025-07-17T07:36:39.4521865Z 2025-07-17T07:36:39.4521957Z 2025-07-17T07:36:39.4522306Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.4522685Z 2025-07-17T07:36:39.4523177Z msg = Cannot scrape callname=load_state_dict_from_url in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=816. 2025-07-17T07:36:39.4524052Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.4524568Z Loads the Torch serialized object at the given URL. 2025-07-17T07:36:39.4524835Z 2025-07-17T07:36:39.4525011Z If downloaded file is a zip file, it will be automatically 2025-07-17T07:36:39.4525566Z decompressed. 2025-07-17T07:36:39.4525705Z 2025-07-17T07:36:39.4525930Z If the object is already present in `model_dir`, it's deserialized and 2025-07-17T07:36:39.4526337Z returned. 2025-07-17T07:36:39.4526681Z The default value of ``model_dir`` is ``/checkpoints`` where 2025-07-17T07:36:39.4527206Z ``hub_dir`` is the directory returned by :func:`~torch.hub.get_dir`. 2025-07-17T07:36:39.4527510Z 2025-07-17T07:36:39.4527603Z Args: 2025-07-17T07:36:39.4527829Z url (str): URL of the object to download 2025-07-17T07:36:39.4528258Z model_dir (str, optional): directory in which to save the object 2025-07-17T07:36:39.4528980Z map_location (optional): a function or a dict specifying how to remap storage locations (see torch.load) 2025-07-17T07:36:39.4529691Z progress (bool, optional): whether or not to display a progress bar to stderr. 2025-07-17T07:36:39.4530163Z Default: True 2025-07-17T07:36:39.4530650Z check_hash(bool, optional): If True, the filename part of the URL should follow the naming convention 2025-07-17T07:36:39.4531316Z ``filename-.ext`` where ```` is the first eight or more 2025-07-17T07:36:39.4531871Z digits of the SHA256 hash of the contents of the file. The hash is used to 2025-07-17T07:36:39.4532405Z ensure unique names and to verify the contents of the file. 2025-07-17T07:36:39.4532806Z Default: False 2025-07-17T07:36:39.4533310Z file_name (str, optional): name for the downloaded file. Filename from ``url`` will be used if not set. 2025-07-17T07:36:39.4534091Z weights_only(bool, optional): If True, only weights will be loaded and no complex pickled objects. 2025-07-17T07:36:39.4534794Z Recommended for untrusted sources. See :func:`~torch.load` for more details. 2025-07-17T07:36:39.4535171Z 2025-07-17T07:36:39.4535268Z Example: 2025-07-17T07:36:39.4535519Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-07-17T07:36:39.4535915Z >>> state_dict = torch.hub.load_state_dict_from_url( 2025-07-17T07:36:39.4536393Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth" 2025-07-17T07:36:39.4536795Z ... ) 2025-07-17T07:36:39.4536929Z 2025-07-17T07:36:39.4537005Z 2025-07-17T07:36:39.4537369Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.4537733Z 2025-07-17T07:36:39.4566290Z msg = Cannot scrape callname=Library.fallback in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=374. 2025-07-17T07:36:39.4567141Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:39.4567756Z Registers the function implementation as the fallback for the given key. 2025-07-17T07:36:39.4568123Z 2025-07-17T07:36:39.4568336Z This function only works for a library with global namespace ("_"). 2025-07-17T07:36:39.4568668Z 2025-07-17T07:36:39.4568766Z Args: 2025-07-17T07:36:39.4569167Z fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel` 2025-07-17T07:36:39.4569678Z to register a fallthrough. 2025-07-17T07:36:39.4570395Z dispatch_key: dispatch key that the input function should be registered for. By default, it uses 2025-07-17T07:36:39.4570998Z the dispatch key that the library was created with. 2025-07-17T07:36:39.4571663Z with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument 2025-07-17T07:36:39.4572485Z to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls. 2025-07-17T07:36:39.4572921Z 2025-07-17T07:36:39.4573035Z Example:: 2025-07-17T07:36:39.4573172Z 2025-07-17T07:36:39.4573291Z >>> my_lib = Library("_", "IMPL") 2025-07-17T07:36:39.4573629Z >>> def fallback_kernel(op, *args, **kwargs): 2025-07-17T07:36:39.4574141Z >>> # Handle all autocast ops generically 2025-07-17T07:36:39.4574488Z >>> # ... 2025-07-17T07:36:39.4574779Z >>> my_lib.fallback(fallback_kernel, "Autocast") 2025-07-17T07:36:39.4575122Z 2025-07-17T07:36:39.4575879Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7)) 2025-07-17T07:36:39.4576618Z 2025-07-17T07:36:39.4576758Z my_lib.fallback(fallback_kernel, "Autocast") 2025-07-17T07:36:39.4577069Z ^ 2025-07-17T07:36:39.4646441Z msg = Cannot scrape callname=register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=933. 2025-07-17T07:36:39.4648174Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:39.4649288Z Register a FakeTensor implementation ("fake impl") for this operator. 2025-07-17T07:36:39.4649951Z 2025-07-17T07:36:39.4650410Z Also sometimes known as a "meta kernel", "abstract impl". 2025-07-17T07:36:39.4650970Z 2025-07-17T07:36:39.4651417Z An "FakeTensor implementation" specifies the behavior of this operator on 2025-07-17T07:36:39.4652477Z Tensors that carry no data ("FakeTensor"). Given some input Tensors with 2025-07-17T07:36:39.4653521Z certain properties (sizes/strides/storage_offset/device), it specifies 2025-07-17T07:36:39.4654432Z what the properties of the output Tensors are. 2025-07-17T07:36:39.4654917Z 2025-07-17T07:36:39.4655349Z The FakeTensor implementation has the same signature as the operator. 2025-07-17T07:36:39.4656385Z It is run for both FakeTensors and meta tensors. To write a FakeTensor 2025-07-17T07:36:39.4657419Z implementation, assume that all Tensor inputs to the operator are 2025-07-17T07:36:39.4658419Z regular CPU/CUDA/Meta tensors, but they do not have storage, and 2025-07-17T07:36:39.4659393Z you are trying to return regular CPU/CUDA/Meta tensor(s) as output. 2025-07-17T07:36:39.4660451Z The FakeTensor implementation must consist of only PyTorch operations 2025-07-17T07:36:39.4661450Z (and may not directly access the storage or data of any input or 2025-07-17T07:36:39.4662151Z intermediate Tensors). 2025-07-17T07:36:39.4662455Z 2025-07-17T07:36:39.4662686Z This API may be used as a decorator (see examples). 2025-07-17T07:36:39.4663117Z 2025-07-17T07:36:39.4663412Z For a detailed guide on custom ops, please see 2025-07-17T07:36:39.4664327Z https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html 2025-07-17T07:36:39.4665016Z 2025-07-17T07:36:39.4665163Z Args: 2025-07-17T07:36:39.4665805Z op_name: Operator name (along with the overload) or OpOverload object. 2025-07-17T07:36:39.4666655Z func: Fake tensor implementation. 2025-07-17T07:36:39.4667397Z lib (Optional[Library]): Library to register the fake tensor to. 2025-07-17T07:36:39.4668297Z allow_override: Flag controlling if we want to override an 2025-07-17T07:36:39.4669186Z existing registered fake impl. This is by default off, 2025-07-17T07:36:39.4670236Z and will error you're trying to register a fake impl to 2025-07-17T07:36:39.4671115Z an operator that already has a fake impl. This also only 2025-07-17T07:36:39.4671963Z applies if the custom operator was not created via 2025-07-17T07:36:39.4672822Z torch.library.custom_op, as overriding and existing fake 2025-07-17T07:36:39.4673598Z impl is already allowed. 2025-07-17T07:36:39.4674023Z 2025-07-17T07:36:39.4674183Z Examples: 2025-07-17T07:36:39.4674593Z >>> import torch 2025-07-17T07:36:39.4675063Z >>> import numpy as np 2025-07-17T07:36:39.4675578Z >>> from torch import Tensor 2025-07-17T07:36:39.4676074Z >>> 2025-07-17T07:36:39.4676598Z >>> # Example 1: an operator without data-dependent output shape 2025-07-17T07:36:39.4677784Z >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=()) 2025-07-17T07:36:39.4678769Z >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-07-17T07:36:39.4679735Z >>> raise NotImplementedError("Implementation goes here") 2025-07-17T07:36:39.4680431Z >>> 2025-07-17T07:36:39.4680961Z >>> @torch.library.register_fake("mylib::custom_linear") 2025-07-17T07:36:39.4681648Z >>> def _(x, weight, bias): 2025-07-17T07:36:39.4682194Z >>> assert x.dim() == 2 2025-07-17T07:36:39.4682774Z >>> assert weight.dim() == 2 2025-07-17T07:36:39.4683516Z >>> assert bias.dim() == 1 2025-07-17T07:36:39.4684156Z >>> assert x.shape[1] == weight.shape[1] 2025-07-17T07:36:39.4684815Z >>> assert weight.shape[0] == bias.shape[0] 2025-07-17T07:36:39.4685590Z >>> assert x.device == weight.device 2025-07-17T07:36:39.4686157Z >>> 2025-07-17T07:36:39.4686580Z >>> return (x @ weight.t()) + bias 2025-07-17T07:36:39.4687141Z >>> 2025-07-17T07:36:39.4687674Z >>> with torch._subclasses.fake_tensor.FakeTensorMode(): 2025-07-17T07:36:39.4688429Z >>> x = torch.randn(2, 3) 2025-07-17T07:36:39.4688958Z >>> w = torch.randn(3, 3) 2025-07-17T07:36:39.4689506Z >>> b = torch.randn(3) 2025-07-17T07:36:39.4690054Z >>> y = torch.ops.mylib.custom_linear(x, w, b) 2025-07-17T07:36:39.4690669Z >>> 2025-07-17T07:36:39.4691071Z >>> assert y.shape == (2, 3) 2025-07-17T07:36:39.4691594Z >>> 2025-07-17T07:36:39.4692119Z >>> # Example 2: an operator with data-dependent output shape 2025-07-17T07:36:39.4693077Z >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=()) 2025-07-17T07:36:39.4693930Z >>> def custom_nonzero(x: Tensor) -> Tensor: 2025-07-17T07:36:39.4694555Z >>> x_np = x.numpy(force=True) 2025-07-17T07:36:39.4695191Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-07-17T07:36:39.4695877Z >>> return torch.tensor(res, device=x.device) 2025-07-17T07:36:39.4696468Z >>> 2025-07-17T07:36:39.4696996Z >>> @torch.library.register_fake("mylib::custom_nonzero") 2025-07-17T07:36:39.4697675Z >>> def _(x): 2025-07-17T07:36:39.4698204Z >>> # Number of nonzero-elements is data-dependent. 2025-07-17T07:36:39.4698950Z >>> # Since we cannot peek at the data in an fake impl, 2025-07-17T07:36:39.4699727Z >>> # we use the ctx object to construct a new symint that 2025-07-17T07:36:39.4700458Z >>> # represents the data-dependent size. 2025-07-17T07:36:39.4701097Z >>> ctx = torch.library.get_ctx() 2025-07-17T07:36:39.4701714Z >>> nnz = ctx.new_dynamic_size() 2025-07-17T07:36:39.4702298Z >>> shape = [nnz, x.dim()] 2025-07-17T07:36:39.4702926Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-07-17T07:36:39.4703584Z >>> return result 2025-07-17T07:36:39.4704051Z >>> 2025-07-17T07:36:39.4704564Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-07-17T07:36:39.4705216Z >>> 2025-07-17T07:36:39.4705620Z >>> x = torch.tensor([0, 1, 2, 3, 4, 0]) 2025-07-17T07:36:39.4706477Z >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x) 2025-07-17T07:36:39.4707350Z >>> trace.print_readable() 2025-07-17T07:36:39.4707858Z >>> 2025-07-17T07:36:39.4708493Z >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x)) 2025-07-17T07:36:39.4709147Z 2025-07-17T07:36:39.4709278Z 2025-07-17T07:36:39.4710475Z Original Error: IndentationError('expected an indented block after function definition on line 37', ('', 38, 1, '_._ = None\n', 38, 2)) 2025-07-17T07:36:39.4711746Z 2025-07-17T07:36:39.4711893Z _._ = None 2025-07-17T07:36:39.4712260Z ^ 2025-07-17T07:36:39.4713480Z msg = Cannot scrape callname=register_autograd in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1068. 2025-07-17T07:36:39.4715280Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.4716273Z Register a backward formula for this custom op. 2025-07-17T07:36:39.4716748Z 2025-07-17T07:36:39.4717142Z In order for an operator to work with autograd, you need to register 2025-07-17T07:36:39.4717908Z a backward formula: 2025-07-17T07:36:39.4718585Z 1. You must tell us how to compute gradients during the backward pass 2025-07-17T07:36:39.4719414Z by providing us a "backward" function. 2025-07-17T07:36:39.4720302Z 2. If you need any values from the forward to compute gradients, you can 2025-07-17T07:36:39.4721132Z use `setup_context` to save values for backward. 2025-07-17T07:36:39.4721600Z 2025-07-17T07:36:39.4722024Z ``backward`` runs during the backward pass. It accepts ``(ctx, *grads)``: 2025-07-17T07:36:39.4723053Z - ``grads`` is one or more gradients. The number of gradients matches 2025-07-17T07:36:39.4723858Z the number of outputs of the operator. 2025-07-17T07:36:39.4724697Z The ``ctx`` object is `the same ctx object `_ used by 2025-07-17T07:36:39.4725889Z :class:`torch.autograd.Function`. The semantics of ``backward_fn`` are the 2025-07-17T07:36:39.4726861Z same as :meth:`torch.autograd.Function.backward`. 2025-07-17T07:36:39.4727353Z 2025-07-17T07:36:39.4727752Z ``setup_context(ctx, inputs, output)`` runs during the forward pass. 2025-07-17T07:36:39.4728796Z Please save quantities needed for backward onto the ``ctx`` object via 2025-07-17T07:36:39.4729889Z either :meth:`torch.autograd.function.FunctionCtx.save_for_backward` 2025-07-17T07:36:39.4730906Z or assigning them as attributes of ``ctx``. If your custom op has 2025-07-17T07:36:39.4731846Z kwarg-only arguments, we expect the signature of ``setup_context`` 2025-07-17T07:36:39.4732780Z to be ``setup_context(ctx, inputs, keyword_only_inputs, output)``. 2025-07-17T07:36:39.4733372Z 2025-07-17T07:36:39.4733783Z Both ``setup_context_fn`` and ``backward_fn`` must be traceable. That is, 2025-07-17T07:36:39.4734815Z they may not directly access :meth:`torch.Tensor.data_ptr` and they must 2025-07-17T07:36:39.4735857Z not depend on or mutate global state. If you need a non-traceable backward, 2025-07-17T07:36:39.4736934Z you can make it a separate custom_op that you call inside ``backward_fn``. 2025-07-17T07:36:39.4737578Z 2025-07-17T07:36:39.4738002Z If you need different autograd behavior on different devices, then we 2025-07-17T07:36:39.4739068Z recommend creating two different custom operators, one for each device 2025-07-17T07:36:39.4740151Z that needs different behavior, and switching between them at runtime. 2025-07-17T07:36:39.4740787Z 2025-07-17T07:36:39.4740950Z Examples: 2025-07-17T07:36:39.4741336Z >>> import torch 2025-07-17T07:36:39.4741815Z >>> import numpy as np 2025-07-17T07:36:39.4742349Z >>> from torch import Tensor 2025-07-17T07:36:39.4742845Z >>> 2025-07-17T07:36:39.4743364Z >>> @torch.library.custom_op("mylib::numpy_sin", mutates_args=()) 2025-07-17T07:36:39.4744042Z >>> def numpy_sin(x: Tensor) -> Tensor: 2025-07-17T07:36:39.4744633Z >>> x_np = x.cpu().numpy() 2025-07-17T07:36:39.4745152Z >>> y_np = np.sin(x_np) 2025-07-17T07:36:39.4745745Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-07-17T07:36:39.4746350Z >>> 2025-07-17T07:36:39.4746827Z >>> def setup_context(ctx, inputs, output) -> Tensor: 2025-07-17T07:36:39.4747485Z >>> x, = inputs 2025-07-17T07:36:39.4747998Z >>> ctx.save_for_backward(x) 2025-07-17T07:36:39.4748531Z >>> 2025-07-17T07:36:39.4748943Z >>> def backward(ctx, grad): 2025-07-17T07:36:39.4749483Z >>> x, = ctx.saved_tensors 2025-07-17T07:36:39.4750042Z >>> return grad * x.cos() 2025-07-17T07:36:39.4750675Z >>> 2025-07-17T07:36:39.4751084Z >>> torch.library.register_autograd( 2025-07-17T07:36:39.4751831Z ... "mylib::numpy_sin", backward, setup_context=setup_context 2025-07-17T07:36:39.4752515Z ... ) 2025-07-17T07:36:39.4752874Z >>> 2025-07-17T07:36:39.4753298Z >>> x = torch.randn(3, requires_grad=True) 2025-07-17T07:36:39.4753876Z >>> y = numpy_sin(x) 2025-07-17T07:36:39.4754484Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-07-17T07:36:39.4755212Z >>> assert torch.allclose(grad_x, x.cos()) 2025-07-17T07:36:39.4755763Z >>> 2025-07-17T07:36:39.4756287Z >>> # Example with a keyword-only arg 2025-07-17T07:36:39.4757072Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-07-17T07:36:39.4757881Z >>> def numpy_mul(x: Tensor, *, val: float) -> Tensor: 2025-07-17T07:36:39.4758529Z >>> x_np = x.cpu().numpy() 2025-07-17T07:36:39.4759071Z >>> y_np = x_np * val 2025-07-17T07:36:39.4759670Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-07-17T07:36:39.4760308Z >>> 2025-07-17T07:36:39.4760918Z >>> def setup_context(ctx, inputs, keyword_only_inputs, output) -> Tensor: 2025-07-17T07:36:39.4761769Z >>> ctx.val = keyword_only_inputs["val"] 2025-07-17T07:36:39.4762328Z >>> 2025-07-17T07:36:39.4762719Z >>> def backward(ctx, grad): 2025-07-17T07:36:39.4763270Z >>> return grad * ctx.val 2025-07-17T07:36:39.4763780Z >>> 2025-07-17T07:36:39.4764195Z >>> torch.library.register_autograd( 2025-07-17T07:36:39.4764960Z ... "mylib::numpy_mul", backward, setup_context=setup_context 2025-07-17T07:36:39.4765743Z ... ) 2025-07-17T07:36:39.4766062Z >>> 2025-07-17T07:36:39.4766494Z >>> x = torch.randn(3, requires_grad=True) 2025-07-17T07:36:39.4767105Z >>> y = numpy_mul(x, val=3.14) 2025-07-17T07:36:39.4767772Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-07-17T07:36:39.4768623Z >>> assert torch.allclose(grad_x, torch.full_like(x, 3.14)) 2025-07-17T07:36:39.4769149Z 2025-07-17T07:36:39.4769305Z 2025-07-17T07:36:39.4770138Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.4770827Z 2025-07-17T07:36:39.4771753Z msg = Cannot scrape callname=opcheck in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1482. 2025-07-17T07:36:39.4773326Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.4774439Z Given an operator and some sample arguments, tests if the operator is 2025-07-17T07:36:39.4775238Z registered correctly. 2025-07-17T07:36:39.4775548Z 2025-07-17T07:36:39.4775927Z That is, when you use the torch.library/TORCH_LIBRARY APIs to create a 2025-07-17T07:36:39.4776999Z custom op, you specified metadata (e.g. mutability info) about the custom op 2025-07-17T07:36:39.4778101Z and these APIs require that the functions you pass them satisfy certain 2025-07-17T07:36:39.4779164Z properties (e.g. no data pointer access in the fake/meta/abstract kernel) 2025-07-17T07:36:39.4780067Z ``opcheck`` tests these metadata and properties. 2025-07-17T07:36:39.4780562Z 2025-07-17T07:36:39.4780762Z Concretely, we test the following: 2025-07-17T07:36:39.4781161Z 2025-07-17T07:36:39.4781490Z - test_schema: If the schema matches the implementation of 2025-07-17T07:36:39.4782397Z the operator. For example: if the schema specifies a Tensor is mutated, 2025-07-17T07:36:39.4783396Z then we check the implementation mutates the Tensor. If the schema 2025-07-17T07:36:39.4784368Z specifies that we return a new Tensor, then we check that the 2025-07-17T07:36:39.4785321Z implementation returns a new Tensor (instead of an existing one or 2025-07-17T07:36:39.4786126Z a view of an existing one). 2025-07-17T07:36:39.4787138Z - test_autograd_registration: If the operator supports training 2025-07-17T07:36:39.4788108Z (autograd): we check that its autograd formula is registered via 2025-07-17T07:36:39.4789091Z torch.library.register_autograd or a manual registration to one 2025-07-17T07:36:39.4790209Z or more DispatchKey::Autograd keys. Any other DispatchKey-based 2025-07-17T07:36:39.4791021Z registrations may lead to undefined behavior. 2025-07-17T07:36:39.4791798Z - test_faketensor: If the operator has a FakeTensor kernel 2025-07-17T07:36:39.4792632Z (and if it is correct). The FakeTensor kernel is necessary ( 2025-07-17T07:36:39.4793686Z but not sufficient) for the operator to work with PyTorch compilation 2025-07-17T07:36:39.4794715Z APIs (torch.compile/export/FX). We check that a FakeTensor kernel 2025-07-17T07:36:39.4795683Z (also sometimes known as a meta kernel) was registered for the 2025-07-17T07:36:39.4796609Z operator and that it is correct. This test takes the result of 2025-07-17T07:36:39.4797568Z running the operator on real tensors and the result of running 2025-07-17T07:36:39.4798494Z the operator on FakeTensors and checks that they have the same 2025-07-17T07:36:39.4799315Z Tensor metadata (sizes/strides/dtype/device/etc). 2025-07-17T07:36:39.4800158Z - test_aot_dispatch_dynamic: If the operator has correct behavior 2025-07-17T07:36:39.4801070Z with PyTorch compilation APIs (torch.compile/export/FX). 2025-07-17T07:36:39.4802036Z This checks that the outputs (and gradients, if applicable) are the 2025-07-17T07:36:39.4802918Z same under eager-mode PyTorch and torch.compile. 2025-07-17T07:36:39.4803777Z This test is a superset of ``test_faketensor`` and is an e2e test; 2025-07-17T07:36:39.4804640Z other things it tests are that the operator supports 2025-07-17T07:36:39.4805609Z functionalization and that the backward pass (if it exists) also 2025-07-17T07:36:39.4806452Z supports FakeTensor and functionalization. 2025-07-17T07:36:39.4806908Z 2025-07-17T07:36:39.4807266Z For best results, please call ``opcheck`` multiple times with a 2025-07-17T07:36:39.4808179Z representative set of inputs. If your operator supports 2025-07-17T07:36:39.4809145Z autograd, please use ``opcheck`` with inputs with ``requires_grad = True``; 2025-07-17T07:36:39.4810223Z if your operator supports multiple devices (e.g. CPU and CUDA), please 2025-07-17T07:36:39.4811156Z use ``opcheck`` with inputs on all supported devices. 2025-07-17T07:36:39.4811638Z 2025-07-17T07:36:39.4811780Z Args: 2025-07-17T07:36:39.4812303Z op: The operator. Must either be a function decorated with 2025-07-17T07:36:39.4813203Z :func:`torch.library.custom_op` or an OpOverload/OpOverloadPacket 2025-07-17T07:36:39.4814074Z found in torch.ops.* (e.g. torch.ops.aten.sin, torch.ops.mylib.foo) 2025-07-17T07:36:39.4814877Z args: The args to the operator 2025-07-17T07:36:39.4815562Z kwargs: The kwargs to the operator 2025-07-17T07:36:39.4816306Z test_utils: Tests that we should run. Default: all of them. 2025-07-17T07:36:39.4817066Z Example: ("test_schema", "test_faketensor") 2025-07-17T07:36:39.4817875Z raise_exception: If we should raise an exception on the first 2025-07-17T07:36:39.4818748Z error. If False, we will return a dict with information 2025-07-17T07:36:39.4819473Z on if each test passed or not. 2025-07-17T07:36:39.4820337Z rtol (Optional[float]): Relative tolerance for floating point comparisons. 2025-07-17T07:36:39.4821244Z If specified ``atol`` must also be specified. 2025-07-17T07:36:39.4822030Z If omitted, default values based on the ``dtype`` are selected 2025-07-17T07:36:39.4822874Z (see the table in :func:`torch.testing.assert_close`). 2025-07-17T07:36:39.4823914Z atol (Optional[float]): Absolute tolerance for floating point comparisons. 2025-07-17T07:36:39.4824836Z If specified ``rtol`` must also be specified. 2025-07-17T07:36:39.4825805Z If omitted, default values based on the ``dtype`` are selected 2025-07-17T07:36:39.4826657Z (see the table in :func:`torch.testing.assert_close`). 2025-07-17T07:36:39.4827176Z 2025-07-17T07:36:39.4827343Z .. warning:: 2025-07-17T07:36:39.4827593Z 2025-07-17T07:36:39.4827992Z opcheck and :func:`torch.autograd.gradcheck` test different things; 2025-07-17T07:36:39.4828969Z opcheck tests if your usage of torch.library APIs is correct while 2025-07-17T07:36:39.4829982Z :func:`torch.autograd.gradcheck` tests if your autograd formula is 2025-07-17T07:36:39.4831087Z mathematically correct. Use both to test custom ops that support 2025-07-17T07:36:39.4831887Z gradient computation. 2025-07-17T07:36:39.4832353Z 2025-07-17T07:36:39.4832502Z Example: 2025-07-17T07:36:39.4832744Z 2025-07-17T07:36:39.4832984Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:39.4833826Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-07-17T07:36:39.4834641Z >>> def numpy_mul(x: Tensor, y: float) -> Tensor: 2025-07-17T07:36:39.4835292Z >>> x_np = x.numpy(force=True) 2025-07-17T07:36:39.4835862Z >>> z_np = x_np * y 2025-07-17T07:36:39.4836422Z >>> return torch.from_numpy(z_np).to(x.device) 2025-07-17T07:36:39.4837027Z >>> 2025-07-17T07:36:39.4837435Z >>> @numpy_mul.register_fake 2025-07-17T07:36:39.4837977Z >>> def _(x, y): 2025-07-17T07:36:39.4838445Z >>> return torch.empty_like(x) 2025-07-17T07:36:39.4838995Z >>> 2025-07-17T07:36:39.4839419Z >>> def setup_context(ctx, inputs, output): 2025-07-17T07:36:39.4840002Z >>> y, = inputs 2025-07-17T07:36:39.4840462Z >>> ctx.y = y 2025-07-17T07:36:39.4840892Z >>> 2025-07-17T07:36:39.4841257Z >>> def backward(ctx, grad): 2025-07-17T07:36:39.4841809Z >>> return grad * ctx.y, None 2025-07-17T07:36:39.4842475Z >>> 2025-07-17T07:36:39.4843082Z >>> numpy_mul.register_autograd(backward, setup_context=setup_context) 2025-07-17T07:36:39.4843879Z >>> 2025-07-17T07:36:39.4844261Z >>> sample_inputs = [ 2025-07-17T07:36:39.4844772Z >>> (torch.randn(3), 3.14), 2025-07-17T07:36:39.4845462Z >>> (torch.randn(2, 3, device='cuda'), 2.718), 2025-07-17T07:36:39.4846165Z >>> (torch.randn(1, 10, requires_grad=True), 1.234), 2025-07-17T07:36:39.4846980Z >>> (torch.randn(64, 64, device='cuda', requires_grad=True), 90.18), 2025-07-17T07:36:39.4847678Z >>> ] 2025-07-17T07:36:39.4848049Z >>> 2025-07-17T07:36:39.4848445Z >>> for args in sample_inputs: 2025-07-17T07:36:39.4849044Z >>> torch.library.opcheck(numpy_mul, args) 2025-07-17T07:36:39.4849486Z 2025-07-17T07:36:39.4849623Z 2025-07-17T07:36:39.4850265Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.4850946Z 2025-07-17T07:36:39.5211443Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py line=1285. 2025-07-17T07:36:39.5212473Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.5213245Z load(f, map_location=None, pickle_module=pickle, *, weights_only=True, mmap=None, **pickle_load_args) 2025-07-17T07:36:39.5213728Z 2025-07-17T07:36:39.5213919Z Loads an object saved with :func:`torch.save` from a file. 2025-07-17T07:36:39.5214284Z 2025-07-17T07:36:39.5214534Z :func:`torch.load` uses Python's unpickling facilities but treats storages, 2025-07-17T07:36:39.5215198Z which underlie tensors, specially. They are first deserialized on the 2025-07-17T07:36:39.5215826Z CPU and are then moved to the device they were saved from. If this fails 2025-07-17T07:36:39.5216443Z (e.g. because the run time system doesn't have certain devices), an exception 2025-07-17T07:36:39.5217322Z is raised. However, storages can be dynamically remapped to an alternative 2025-07-17T07:36:39.5217853Z set of devices using the :attr:`map_location` argument. 2025-07-17T07:36:39.5218215Z 2025-07-17T07:36:39.5218452Z If :attr:`map_location` is a callable, it will be called once for each serialized 2025-07-17T07:36:39.5219126Z storage with two arguments: storage and location. The storage argument 2025-07-17T07:36:39.5219757Z will be the initial deserialization of the storage, residing on the CPU. 2025-07-17T07:36:39.5220349Z Each serialized storage has a location tag associated with it which 2025-07-17T07:36:39.5221051Z identifies the device it was saved from, and this tag is the second 2025-07-17T07:36:39.5221716Z argument passed to :attr:`map_location`. The builtin location tags are ``'cpu'`` 2025-07-17T07:36:39.5222375Z for CPU tensors and ``'cuda:device_id'`` (e.g. ``'cuda:2'``) for CUDA tensors. 2025-07-17T07:36:39.5222987Z :attr:`map_location` should return either ``None`` or a storage. If 2025-07-17T07:36:39.5223617Z :attr:`map_location` returns a storage, it will be used as the final deserialized 2025-07-17T07:36:39.5224232Z object, already moved to the right device. Otherwise, :func:`torch.load` will 2025-07-17T07:36:39.5224911Z fall back to the default behavior, as if :attr:`map_location` wasn't specified. 2025-07-17T07:36:39.5225353Z 2025-07-17T07:36:39.5225585Z If :attr:`map_location` is a :class:`torch.device` object or a string containing 2025-07-17T07:36:39.5226236Z a device tag, it indicates the location where all tensors should be loaded. 2025-07-17T07:36:39.5226615Z 2025-07-17T07:36:39.5226959Z Otherwise, if :attr:`map_location` is a dict, it will be used to remap location tags 2025-07-17T07:36:39.5227595Z appearing in the file (keys), to ones that specify where to put the 2025-07-17T07:36:39.5228017Z storages (values). 2025-07-17T07:36:39.5228171Z 2025-07-17T07:36:39.5228475Z User extensions can register their own location tags and tagging and 2025-07-17T07:36:39.5229110Z deserialization methods using :func:`torch.serialization.register_package`. 2025-07-17T07:36:39.5229520Z 2025-07-17T07:36:39.5229762Z See :ref:`layout-control` for more advanced tools to manipulate a checkpoint. 2025-07-17T07:36:39.5230208Z 2025-07-17T07:36:39.5230291Z Args: 2025-07-17T07:36:39.5230797Z f: a file-like object (has to implement :meth:`read`, :meth:`readline`, :meth:`tell`, and :meth:`seek`), 2025-07-17T07:36:39.5231410Z or a string or os.PathLike object containing a file name 2025-07-17T07:36:39.5232080Z map_location: a function, :class:`torch.device`, string or a dict specifying how to remap storage 2025-07-17T07:36:39.5232709Z locations 2025-07-17T07:36:39.5233151Z pickle_module: module used for unpickling metadata and objects (has to 2025-07-17T07:36:39.5233661Z match the :attr:`pickle_module` used to serialize file) 2025-07-17T07:36:39.5234241Z weights_only: Indicates whether unpickler should be restricted to 2025-07-17T07:36:39.5234798Z loading only tensors, primitive types, dictionaries 2025-07-17T07:36:39.5235285Z and any types added via :func:`torch.serialization.add_safe_globals`. 2025-07-17T07:36:39.5235833Z See :ref:`weights-only` for more details. 2025-07-17T07:36:39.5236479Z mmap: Indicates whether the file should be mapped rather than loading all the storages into memory. 2025-07-17T07:36:39.5237344Z Typically, tensor storages in the file will first be moved from disk to CPU memory, after which they 2025-07-17T07:36:39.5238196Z are moved to the location that they were tagged with when saving, or specified by ``map_location``. This 2025-07-17T07:36:39.5239053Z second step is a no-op if the final location is CPU. When the ``mmap`` flag is set, instead of copying the 2025-07-17T07:36:39.5239901Z tensor storages from disk to CPU memory in the first step, ``f`` is mapped, which means tensor storages 2025-07-17T07:36:39.5240689Z will be lazily loaded when their data is accessed. 2025-07-17T07:36:39.5241250Z pickle_load_args: (Python 3 only) optional keyword arguments passed over to 2025-07-17T07:36:39.5241915Z :func:`pickle_module.load` and :func:`pickle_module.Unpickler`, e.g., 2025-07-17T07:36:39.5242365Z :attr:`errors=...`. 2025-07-17T07:36:39.5242573Z 2025-07-17T07:36:39.5242723Z .. warning:: 2025-07-17T07:36:39.5243065Z :func:`torch.load()` unless `weights_only` parameter is set to `True`, 2025-07-17T07:36:39.5243727Z uses ``pickle`` module implicitly, which is known to be insecure. 2025-07-17T07:36:39.5244394Z It is possible to construct malicious pickle data which will execute arbitrary code 2025-07-17T07:36:39.5245081Z during unpickling. Never load data that could have come from an untrusted 2025-07-17T07:36:39.5245871Z source in an unsafe mode, or that could have been tampered with. **Only load data you trust**. 2025-07-17T07:36:39.5246302Z 2025-07-17T07:36:39.5246391Z .. note:: 2025-07-17T07:36:39.5246854Z When you call :func:`torch.load()` on a file which contains GPU tensors, those tensors 2025-07-17T07:36:39.5247556Z will be loaded to GPU by default. You can call ``torch.load(.., map_location='cpu')`` 2025-07-17T07:36:39.5248279Z and then :meth:`load_state_dict` to avoid GPU RAM surge when loading a model checkpoint. 2025-07-17T07:36:39.5248670Z 2025-07-17T07:36:39.5248814Z .. note:: 2025-07-17T07:36:39.5249248Z By default, we decode byte strings as ``utf-8``. This is to avoid a common error 2025-07-17T07:36:39.5249839Z case ``UnicodeDecodeError: 'ascii' codec can't decode byte 0x...`` 2025-07-17T07:36:39.5250461Z when loading files saved by Python 2 in Python 3. If this default 2025-07-17T07:36:39.5251040Z is incorrect, you may use an extra :attr:`encoding` keyword argument to specify how 2025-07-17T07:36:39.5251726Z these objects should be loaded, e.g., :attr:`encoding='latin1'` decodes them 2025-07-17T07:36:39.5252337Z to strings using ``latin1`` encoding, and :attr:`encoding='bytes'` keeps them 2025-07-17T07:36:39.5252923Z as byte arrays which can be decoded later with ``byte_array.decode(...)``. 2025-07-17T07:36:39.5253268Z 2025-07-17T07:36:39.5253365Z Example: 2025-07-17T07:36:39.5253685Z >>> # xdoctest: +SKIP("undefined filepaths") 2025-07-17T07:36:39.5254069Z >>> torch.load("tensors.pt", weights_only=True) 2025-07-17T07:36:39.5254427Z # Load all tensors onto the CPU 2025-07-17T07:36:39.5254723Z >>> torch.load( 2025-07-17T07:36:39.5254979Z ... "tensors.pt", 2025-07-17T07:36:39.5255283Z ... map_location=torch.device("cpu"), 2025-07-17T07:36:39.5255610Z ... weights_only=True, 2025-07-17T07:36:39.5255887Z ... ) 2025-07-17T07:36:39.5256162Z # Load all tensors onto the CPU, using a function 2025-07-17T07:36:39.5256503Z >>> torch.load( 2025-07-17T07:36:39.5256754Z ... "tensors.pt", 2025-07-17T07:36:39.5257068Z ... map_location=lambda storage, loc: storage, 2025-07-17T07:36:39.5257490Z ... weights_only=True, 2025-07-17T07:36:39.5257760Z ... ) 2025-07-17T07:36:39.5257995Z # Load all tensors onto GPU 1 2025-07-17T07:36:39.5258297Z >>> torch.load( 2025-07-17T07:36:39.5258535Z ... "tensors.pt", 2025-07-17T07:36:39.5258876Z ... map_location=lambda storage, loc: storage.cuda(1), 2025-07-17T07:36:39.5259256Z ... weights_only=True, 2025-07-17T07:36:39.5259553Z ... ) # type: ignore[attr-defined] 2025-07-17T07:36:39.5259884Z # Map tensors from GPU 1 to GPU 0 2025-07-17T07:36:39.5260198Z >>> torch.load( 2025-07-17T07:36:39.5260436Z ... "tensors.pt", 2025-07-17T07:36:39.5260731Z ... map_location={"cuda:1": "cuda:0"}, 2025-07-17T07:36:39.5261156Z ... weights_only=True, 2025-07-17T07:36:39.5261440Z ... ) 2025-07-17T07:36:39.5261674Z # Load tensor from io.BytesIO object 2025-07-17T07:36:39.5262157Z # Loading from a buffer setting weights_only=False, warning this can be unsafe 2025-07-17T07:36:39.5262648Z >>> with open("tensor.pt", "rb") as f: 2025-07-17T07:36:39.5262979Z ... buffer = io.BytesIO(f.read()) 2025-07-17T07:36:39.5263329Z >>> torch.load(buffer, weights_only=False) 2025-07-17T07:36:39.5263717Z # Load a module with 'ascii' encoding for unpickling 2025-07-17T07:36:39.5264211Z # Loading from a module setting weights_only=False, warning this can be unsafe 2025-07-17T07:36:39.5264924Z >>> torch.load("module.pt", encoding="ascii", weights_only=False) 2025-07-17T07:36:39.5265322Z 2025-07-17T07:36:39.5265684Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.5266050Z 2025-07-17T07:36:39.5728721Z msg = Cannot scrape callname=compute_required_storage_length in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims_common/__init__.py line=1848. 2025-07-17T07:36:39.5729749Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.5730354Z Computes the minimum storage size to hold the given tensor geometry. 2025-07-17T07:36:39.5730686Z 2025-07-17T07:36:39.5730784Z Example 2025-07-17T07:36:39.5730977Z ======= 2025-07-17T07:36:39.5731104Z 2025-07-17T07:36:39.5731330Z This is the size of a newly allocated tensor's storage, in units of elements 2025-07-17T07:36:39.5731684Z 2025-07-17T07:36:39.5731784Z >>> t = torch.empty((10, 20)) 2025-07-17T07:36:39.5732239Z >>> compute_required_storage_length(t.shape, t.stride(), t.storage_offset()) 2025-07-17T07:36:39.5732671Z 200 2025-07-17T07:36:39.5732797Z 2025-07-17T07:36:39.5732897Z >>> # xdoctest: +SKIP(failing) 2025-07-17T07:36:39.5733232Z >>> t2 = torch.empty_strided((1, 2, 3), (5, 7, 11)) 2025-07-17T07:36:39.5733596Z >>> size = compute_required_storage_length( 2025-07-17T07:36:39.5733962Z ... t2.shape, t2.stride(), t2.storage_offset() 2025-07-17T07:36:39.5734291Z ... ) 2025-07-17T07:36:39.5734502Z >>> size == t.storage().size() 2025-07-17T07:36:39.5734779Z True 2025-07-17T07:36:39.5734891Z 2025-07-17T07:36:39.5735092Z A valid tensor may have a larger storage size, but never smaller 2025-07-17T07:36:39.5735403Z 2025-07-17T07:36:39.5735520Z >>> slice = torch.empty(100)[20:40] 2025-07-17T07:36:39.5735828Z >>> slice.storage().size() 2025-07-17T07:36:39.5736097Z 100 2025-07-17T07:36:39.5736205Z 2025-07-17T07:36:39.5736332Z >>> compute_required_storage_length( 2025-07-17T07:36:39.5736702Z ... slice.shape, slice.stride(), slice.storage_offset() 2025-07-17T07:36:39.5737061Z ... ) 2025-07-17T07:36:39.5737262Z 40 2025-07-17T07:36:39.5737371Z 2025-07-17T07:36:39.5737452Z 2025-07-17T07:36:39.5737813Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.5738197Z 2025-07-17T07:36:39.6278241Z msg = Cannot scrape callname=is_available in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=66. 2025-07-17T07:36:39.6279283Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:39.6279939Z Check if the current accelerator is available at runtime: it was build, all the 2025-07-17T07:36:39.6280544Z required drivers are available and at least one device is visible. 2025-07-17T07:36:39.6281081Z See :ref:`accelerator` for details. 2025-07-17T07:36:39.6281336Z 2025-07-17T07:36:39.6281507Z Returns: 2025-07-17T07:36:39.6281905Z bool: A boolean indicating if there is an available :ref:`accelerator`. 2025-07-17T07:36:39.6282365Z 2025-07-17T07:36:39.6282633Z .. note:: This API delegates to the device-specific version of `is_available`. 2025-07-17T07:36:39.6283563Z On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set, 2025-07-17T07:36:39.6284272Z this function will NOT poison fork. Otherwise, it will. For more details, see 2025-07-17T07:36:39.6284833Z :ref:`multiprocessing-poison-fork-note`. 2025-07-17T07:36:39.6285114Z 2025-07-17T07:36:39.6285223Z Example:: 2025-07-17T07:36:39.6285456Z 2025-07-17T07:36:39.6285739Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-07-17T07:36:39.6286273Z 2025-07-17T07:36:39.6287106Z Original Error: SyntaxError('invalid syntax', ('', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78)) 2025-07-17T07:36:39.6287860Z 2025-07-17T07:36:39.6288122Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-07-17T07:36:39.6288661Z ^ 2025-07-17T07:36:39.6294333Z msg = Cannot scrape callname=synchronize in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=212. 2025-07-17T07:36:39.6295245Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:39.6295823Z Wait for all kernels in all streams on the given device to complete. 2025-07-17T07:36:39.6296144Z 2025-07-17T07:36:39.6296243Z Args: 2025-07-17T07:36:39.6296669Z device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match 2025-07-17T07:36:39.6297336Z the current :ref:`accelerator` device type. If not given, 2025-07-17T07:36:39.6297886Z use :func:`torch.accelerator.current_device_index` by default. 2025-07-17T07:36:39.6298206Z 2025-07-17T07:36:39.6298544Z .. note:: This function is a no-op if the current :ref:`accelerator` is not initialized. 2025-07-17T07:36:39.6298970Z 2025-07-17T07:36:39.6299058Z Example:: 2025-07-17T07:36:39.6299203Z 2025-07-17T07:36:39.6299341Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:39.6299866Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-07-17T07:36:39.6300402Z >>> start_event = torch.Event(enable_timing=True) 2025-07-17T07:36:39.6300779Z >>> end_event = torch.Event(enable_timing=True) 2025-07-17T07:36:39.6301133Z >>> start_event.record() 2025-07-17T07:36:39.6301559Z >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator()) 2025-07-17T07:36:39.6302010Z >>> sum = torch.sum(tensor) 2025-07-17T07:36:39.6302309Z >>> end_event.record() 2025-07-17T07:36:39.6302613Z >>> torch.accelerator.synchronize() 2025-07-17T07:36:39.6303026Z >>> elapsed_time_ms = start_event.elapsed_time(end_event) 2025-07-17T07:36:39.6303377Z 2025-07-17T07:36:39.6304049Z Original Error: SyntaxError('invalid syntax', ('', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78)) 2025-07-17T07:36:39.6304722Z 2025-07-17T07:36:39.6304993Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-07-17T07:36:39.6305456Z ^ 2025-07-17T07:36:39.6548830Z msg = Cannot scrape callname=cudart in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/__init__.py line=434. 2025-07-17T07:36:39.6549675Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:39.6550163Z Retrieves the CUDA runtime API module. 2025-07-17T07:36:39.6550381Z 2025-07-17T07:36:39.6550385Z 2025-07-17T07:36:39.6550650Z This function initializes the CUDA runtime environment if it is not already 2025-07-17T07:36:39.6551250Z initialized and returns the CUDA runtime API module (_cudart). The CUDA 2025-07-17T07:36:39.6551823Z runtime API module provides access to various CUDA runtime functions. 2025-07-17T07:36:39.6552162Z 2025-07-17T07:36:39.6552263Z Args: 2025-07-17T07:36:39.6552664Z ``None`` 2025-07-17T07:36:39.6552810Z 2025-07-17T07:36:39.6552895Z Returns: 2025-07-17T07:36:39.6553170Z module: The CUDA runtime API module (_cudart). 2025-07-17T07:36:39.6553418Z 2025-07-17T07:36:39.6553510Z Raises: 2025-07-17T07:36:39.6553850Z RuntimeError: If CUDA cannot be re-initialized in a forked subprocess. 2025-07-17T07:36:39.6554557Z AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable. 2025-07-17T07:36:39.6555030Z 2025-07-17T07:36:39.6555171Z Example of CUDA operations with profiling: 2025-07-17T07:36:39.6555497Z >>> import torch 2025-07-17T07:36:39.6555888Z >>> from torch.cuda import cudart, check_error 2025-07-17T07:36:39.6556225Z >>> import os 2025-07-17T07:36:39.6556452Z >>> 2025-07-17T07:36:39.6556694Z >>> os.environ["CUDA_PROFILE"] = "1" 2025-07-17T07:36:39.6557004Z >>> 2025-07-17T07:36:39.6557267Z >>> def perform_cuda_operations_with_streams(): 2025-07-17T07:36:39.6557623Z >>> stream = torch.cuda.Stream() 2025-07-17T07:36:39.6557983Z >>> with torch.cuda.stream(stream): 2025-07-17T07:36:39.6558342Z >>> x = torch.randn(100, 100, device='cuda') 2025-07-17T07:36:39.6558692Z >>> y = torch.randn(100, 100, device='cuda') 2025-07-17T07:36:39.6559030Z >>> z = torch.mul(x, y) 2025-07-17T07:36:39.6559328Z >>> return z 2025-07-17T07:36:39.6559554Z >>> 2025-07-17T07:36:39.6559783Z >>> torch.cuda.synchronize() 2025-07-17T07:36:39.6560123Z >>> print("====== Start nsys profiling ======") 2025-07-17T07:36:39.6560508Z >>> check_error(cudart().cudaProfilerStart()) 2025-07-17T07:36:39.6560881Z >>> with torch.autograd.profiler.emit_nvtx(): 2025-07-17T07:36:39.6561283Z >>> result = perform_cuda_operations_with_streams() 2025-07-17T07:36:39.6561673Z >>> print("CUDA operations completed.") 2025-07-17T07:36:39.6562066Z >>> check_error(torch.cuda.cudart().cudaProfilerStop()) 2025-07-17T07:36:39.6562470Z >>> print("====== End nsys profiling ======") 2025-07-17T07:36:39.6562706Z 2025-07-17T07:36:39.6562912Z To run this example and save the profiling information, execute: 2025-07-17T07:36:39.6563593Z >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-07-17T07:36:39.6564062Z 2025-07-17T07:36:39.6564309Z This command profiles the CUDA operations in the provided script and saves 2025-07-17T07:36:39.6564866Z the profiling information to a file named `trace_name.prof`. 2025-07-17T07:36:39.6565482Z The `--profile-from-start off` option ensures that profiling starts only 2025-07-17T07:36:39.6565975Z after the `cudaProfilerStart` call in the script. 2025-07-17T07:36:39.6566457Z The `--csv` and `--print-summary` options format the profiling output as a 2025-07-17T07:36:39.6566930Z CSV file and print a summary, respectively. 2025-07-17T07:36:39.6567420Z The `-o` option specifies the output file name, and the `-f` option forces the 2025-07-17T07:36:39.6567927Z overwrite of the output file if it already exists. 2025-07-17T07:36:39.6568270Z 2025-07-17T07:36:39.6569038Z Original Error: SyntaxError('invalid syntax', ('', 1, 1, '$ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py\n', 1, 2)) 2025-07-17T07:36:39.6569795Z 2025-07-17T07:36:39.6570674Z $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-07-17T07:36:39.6571237Z ^ 2025-07-17T07:36:39.6717691Z msg = Cannot scrape callname=Future.then in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=101. 2025-07-17T07:36:39.6719371Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.6720102Z 2025-07-17T07:36:39.6720536Z Append the given callback function to this ``Future``, which will be run 2025-07-17T07:36:39.6721789Z when the ``Future`` is completed. Multiple callbacks can be added to 2025-07-17T07:36:39.6722729Z the same ``Future``, but the order in which they will be executed cannot 2025-07-17T07:36:39.6723663Z be guaranteed (to enforce a certain order consider chaining: 2025-07-17T07:36:39.6724592Z ``fut.then(cb1).then(cb2)``). The callback must take one argument, which 2025-07-17T07:36:39.6741189Z is the reference to this ``Future``. The callback function can use the 2025-07-17T07:36:39.6742270Z :meth:`value` method to get the value. Note that if this ``Future`` is 2025-07-17T07:36:39.6743301Z already completed, the given callback will be run immediately inline. 2025-07-17T07:36:39.6744204Z 2025-07-17T07:36:39.6744569Z If the ``Future``'s value contains tensors that reside on GPUs, the 2025-07-17T07:36:39.6745527Z callback might be invoked while the async kernels that are populating 2025-07-17T07:36:39.6746550Z those tensors haven't yet finished executing on the device. However, the 2025-07-17T07:36:39.6747602Z callback will be invoked with some dedicated streams set as current 2025-07-17T07:36:39.6748540Z (fetched from a global pool) which will be synchronized with those 2025-07-17T07:36:39.6749570Z kernels. Hence any operation performed by the callback on these tensors 2025-07-17T07:36:39.6750588Z will be scheduled on the device after the kernels complete. In other 2025-07-17T07:36:39.6751530Z words, as long as the callback doesn't switch streams, it can safely 2025-07-17T07:36:39.6752519Z manipulate the result without any additional synchronization. This is 2025-07-17T07:36:39.6753430Z similar to the non-blocking behavior of :meth:`wait`. 2025-07-17T07:36:39.6753921Z 2025-07-17T07:36:39.6754315Z Similarly, if the callback returns a value that contains tensors that 2025-07-17T07:36:39.6754909Z reside on a GPU, it can do so even if the kernels that are producing 2025-07-17T07:36:39.6755443Z these tensors are still running on the device, as long as the callback 2025-07-17T07:36:39.6755997Z didn't change streams during its execution. If one wants to change 2025-07-17T07:36:39.6756514Z streams, one must be careful to re-synchronize them with the original 2025-07-17T07:36:39.6757061Z streams, that is, those that were current when the callback was invoked. 2025-07-17T07:36:39.6757407Z 2025-07-17T07:36:39.6757488Z Args: 2025-07-17T07:36:39.6757812Z callback(``Callable``): a ``Callable`` that takes this ``Future`` as 2025-07-17T07:36:39.6758230Z the only argument. 2025-07-17T07:36:39.6758459Z 2025-07-17T07:36:39.6758542Z Returns: 2025-07-17T07:36:39.6758827Z A new ``Future`` object that holds the return value of the 2025-07-17T07:36:39.6759276Z ``callback`` and will be marked as completed when the given 2025-07-17T07:36:39.6759664Z ``callback`` finishes. 2025-07-17T07:36:39.6759845Z 2025-07-17T07:36:39.6760031Z .. note:: Note that if the callback function throws, either 2025-07-17T07:36:39.6760855Z through the original future being completed with an exception and 2025-07-17T07:36:39.6761751Z calling ``fut.wait()``, or through other code in the callback, the 2025-07-17T07:36:39.6762670Z future returned by ``then`` will be marked appropriately with the 2025-07-17T07:36:39.6763614Z encountered error. However, if this callback later completes 2025-07-17T07:36:39.6764580Z additional futures, those futures are not marked as completed with 2025-07-17T07:36:39.6765696Z an error and the user is responsible for handling completion/waiting 2025-07-17T07:36:39.6766489Z on those futures independently. 2025-07-17T07:36:39.6766882Z 2025-07-17T07:36:39.6767070Z Example:: 2025-07-17T07:36:39.6767287Z 2025-07-17T07:36:39.6767557Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-07-17T07:36:39.6768207Z >>> def callback(fut): 2025-07-17T07:36:39.6768767Z ... print(f"RPC return value is {fut.wait()}.") 2025-07-17T07:36:39.6769427Z >>> fut = torch.futures.Future() 2025-07-17T07:36:39.6770479Z >>> # The inserted callback will print the return value when 2025-07-17T07:36:39.6771198Z >>> # receiving the response from "worker1" 2025-07-17T07:36:39.6771779Z >>> cb_fut = fut.then(callback) 2025-07-17T07:36:39.6772267Z >>> chain_cb_fut = cb_fut.then( 2025-07-17T07:36:39.6772684Z ... lambda x : print(f"Chained cb done. {x.wait()}") 2025-07-17T07:36:39.6773035Z ... ) 2025-07-17T07:36:39.6773242Z >>> fut.set_result(5) 2025-07-17T07:36:39.6773510Z RPC return value is 5. 2025-07-17T07:36:39.6773780Z Chained cb done. None 2025-07-17T07:36:39.6773946Z 2025-07-17T07:36:39.6774199Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.6774750Z 2025-07-17T07:36:39.6775313Z msg = Cannot scrape callname=Future.set_result in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=211. 2025-07-17T07:36:39.6776226Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.6776609Z 2025-07-17T07:36:39.6776824Z Set the result for this ``Future``, which will mark this ``Future`` as 2025-07-17T07:36:39.6777351Z completed and trigger all attached callbacks. Note that a ``Future`` 2025-07-17T07:36:39.6777798Z cannot be marked completed twice. 2025-07-17T07:36:39.6778011Z 2025-07-17T07:36:39.6778413Z If the result contains tensors that reside on GPUs, this method can be 2025-07-17T07:36:39.6779350Z called even if the asynchronous kernels that are populating those 2025-07-17T07:36:39.6780252Z tensors haven't yet completed running on the device, provided that the 2025-07-17T07:36:39.6781288Z streams on which those kernels were enqueued are set as the current ones 2025-07-17T07:36:39.6782329Z when this method is called. Put simply, it's safe to call this method 2025-07-17T07:36:39.6783332Z immediately after launching those kernels, without any additional 2025-07-17T07:36:39.6784364Z synchronization, as long as one doesn't change streams in between. This 2025-07-17T07:36:39.6785433Z method will record events on all the relevant current streams and will 2025-07-17T07:36:39.6786428Z use them to ensure proper scheduling for all the consumers of this 2025-07-17T07:36:39.6787182Z ``Future``. 2025-07-17T07:36:39.6787415Z 2025-07-17T07:36:39.6787545Z Args: 2025-07-17T07:36:39.6788055Z result (object): the result object of this ``Future``. 2025-07-17T07:36:39.6788579Z 2025-07-17T07:36:39.6788735Z Example:: 2025-07-17T07:36:39.6788941Z 2025-07-17T07:36:39.6789189Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-07-17T07:36:39.6789842Z >>> import threading 2025-07-17T07:36:39.6790297Z >>> import time 2025-07-17T07:36:39.6790736Z >>> def slow_set_future(fut, value): 2025-07-17T07:36:39.6791281Z ... time.sleep(0.5) 2025-07-17T07:36:39.6791751Z ... fut.set_result(value) 2025-07-17T07:36:39.6792240Z >>> fut = torch.futures.Future() 2025-07-17T07:36:39.6792799Z >>> t = threading.Thread( 2025-07-17T07:36:39.6793310Z ... target=slow_set_future, 2025-07-17T07:36:39.6793835Z ... args=(fut, torch.ones(2) * 3) 2025-07-17T07:36:39.6794354Z ... ) 2025-07-17T07:36:39.6794705Z >>> t.start() 2025-07-17T07:36:39.6795110Z >>> print(fut.wait()) 2025-07-17T07:36:39.6795577Z tensor([3., 3.]) 2025-07-17T07:36:39.6796003Z >>> t.join() 2025-07-17T07:36:39.6796255Z 2025-07-17T07:36:39.6796753Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.6797459Z 2025-07-17T07:36:39.6863023Z msg = Cannot scrape callname=compile_shader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/mps/__init__.py line=145. 2025-07-17T07:36:39.6864739Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.6865872Z Compiles compute shader from source and allows one to invoke kernels 2025-07-17T07:36:39.6866754Z defined there from the comfort of Python runtime 2025-07-17T07:36:39.6867391Z Example:: 2025-07-17T07:36:39.6867639Z 2025-07-17T07:36:39.6868091Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_MPS) 2025-07-17T07:36:39.6868757Z >>> lib = torch.mps.compile_shader( 2025-07-17T07:36:39.6869892Z ... "kernel void full(device float* out, constant float& val, uint idx [[thread_position_in_grid]]) { out[idx] = val; }" 2025-07-17T07:36:39.6871211Z ... ) 2025-07-17T07:36:39.6871647Z >>> x = torch.zeros(16, device="mps") 2025-07-17T07:36:39.6872226Z >>> lib.full(x, 3.14) 2025-07-17T07:36:39.6872703Z 2025-07-17T07:36:39.6873382Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.6874078Z 2025-07-17T07:36:39.7045411Z msg = Cannot scrape callname=sum in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py line=202. 2025-07-17T07:36:39.7046287Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:39.7046834Z Return the sum of each row of the given sparse tensor. 2025-07-17T07:36:39.7047112Z 2025-07-17T07:36:39.7047352Z Returns the sum of each row of the sparse tensor :attr:`input` in the given 2025-07-17T07:36:39.7047903Z dimensions :attr:`dim`. If :attr:`dim` is a list of dimensions, 2025-07-17T07:36:39.7048417Z reduce over all of them. When sum over all ``sparse_dim``, this method 2025-07-17T07:36:39.7048902Z returns a dense tensor instead of a sparse tensor. 2025-07-17T07:36:39.7049161Z 2025-07-17T07:36:39.7049431Z All summed :attr:`dim` are squeezed (see :func:`torch.squeeze`), resulting an output 2025-07-17T07:36:39.7049997Z tensor having :attr:`dim` fewer dimensions than :attr:`input`. 2025-07-17T07:36:39.7050319Z 2025-07-17T07:36:39.7050546Z During backward, only gradients at ``nnz`` locations of :attr:`input` 2025-07-17T07:36:39.7051128Z will propagate back. Note that the gradients of :attr:`input` is coalesced. 2025-07-17T07:36:39.7051484Z 2025-07-17T07:36:39.7051582Z Args: 2025-07-17T07:36:39.7051822Z input (Tensor): the input sparse tensor 2025-07-17T07:36:39.7052338Z dim (int or tuple of ints): a dimension or a list of dimensions to reduce. Default: reduce 2025-07-17T07:36:39.7052834Z over all dims. 2025-07-17T07:36:39.7053262Z dtype (:class:`torch.dtype`, optional): the desired data type of returned Tensor. 2025-07-17T07:36:39.7053747Z Default: dtype of :attr:`input`. 2025-07-17T07:36:39.7053978Z 2025-07-17T07:36:39.7054078Z Example:: 2025-07-17T07:36:39.7054209Z 2025-07-17T07:36:39.7054305Z >>> nnz = 3 2025-07-17T07:36:39.7054530Z >>> dims = [5, 5, 2, 3] 2025-07-17T07:36:39.7054872Z >>> I = torch.cat([torch.randint(0, dims[0], size=(nnz,)), 2025-07-17T07:36:39.7055334Z torch.randint(0, dims[1], size=(nnz,))], 0).reshape(2, nnz) 2025-07-17T07:36:39.7055754Z >>> V = torch.randn(nnz, dims[2], dims[3]) 2025-07-17T07:36:39.7056098Z >>> size = torch.Size(dims) 2025-07-17T07:36:39.7056444Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-07-17T07:36:39.7056829Z >>> S = torch.sparse_coo_tensor(I, V, size) 2025-07-17T07:36:39.7057145Z >>> S 2025-07-17T07:36:39.7057389Z tensor(indices=tensor([[2, 0, 3], 2025-07-17T07:36:39.7057711Z [2, 4, 1]]), 2025-07-17T07:36:39.7058047Z values=tensor([[[-0.6438, -1.6467, 1.4004], 2025-07-17T07:36:39.7058421Z [ 0.3411, 0.0918, -0.2312]], 2025-07-17T07:36:39.7058646Z 2025-07-17T07:36:39.7058754Z [[ 0.5348, 0.0634, -2.0494], 2025-07-17T07:36:39.7059092Z [-0.7125, -1.0646, 2.1844]], 2025-07-17T07:36:39.7059311Z 2025-07-17T07:36:39.7059432Z [[ 0.1276, 0.1874, -0.6334], 2025-07-17T07:36:39.7059769Z [-1.9682, -0.5340, 0.7483]]]), 2025-07-17T07:36:39.7060127Z size=(5, 5, 2, 3), nnz=3, layout=torch.sparse_coo) 2025-07-17T07:36:39.7060507Z 2025-07-17T07:36:39.7060696Z # when sum over only part of sparse_dims, return a sparse tensor 2025-07-17T07:36:39.7061122Z >>> torch.sparse.sum(S, [1, 3]) 2025-07-17T07:36:39.7061453Z tensor(indices=tensor([[0, 2, 3]]), 2025-07-17T07:36:39.7061786Z values=tensor([[-1.4512, 0.4073], 2025-07-17T07:36:39.7062114Z [-0.8901, 0.2017], 2025-07-17T07:36:39.7062431Z [-0.3183, -1.7539]]), 2025-07-17T07:36:39.7062777Z size=(5, 2), nnz=3, layout=torch.sparse_coo) 2025-07-17T07:36:39.7063037Z 2025-07-17T07:36:39.7063187Z # when sum over all sparse dim, return a dense tensor 2025-07-17T07:36:39.7063635Z # with summed dims squeezed 2025-07-17T07:36:39.7063943Z >>> torch.sparse.sum(S, [0, 1, 3]) 2025-07-17T07:36:39.7064260Z tensor([-2.6596, -1.1450]) 2025-07-17T07:36:39.7064539Z 2025-07-17T07:36:39.7064893Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:39.7065278Z 2025-07-17T07:36:40.5058470Z msg = Cannot scrape callname=vmap in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=39. 2025-07-17T07:36:40.5059520Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:40.5059913Z 2025-07-17T07:36:40.5060129Z vmap is the vectorizing map; ``vmap(func)`` returns a new function that 2025-07-17T07:36:40.5060659Z maps ``func`` over some dimension of the inputs. Semantically, vmap 2025-07-17T07:36:40.5061176Z pushes the map into PyTorch operations called by ``func``, effectively 2025-07-17T07:36:40.5061621Z vectorizing those operations. 2025-07-17T07:36:40.5061821Z 2025-07-17T07:36:40.5062088Z vmap is useful for handling batch dimensions: one can write a function 2025-07-17T07:36:40.5062626Z ``func`` that runs on examples and then lift it to a function that can 2025-07-17T07:36:40.5063156Z take batches of examples with ``vmap(func)``. vmap can also be used to 2025-07-17T07:36:40.5063668Z compute batched gradients when composed with autograd. 2025-07-17T07:36:40.5063944Z 2025-07-17T07:36:40.5064053Z .. note:: 2025-07-17T07:36:40.5064358Z :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for 2025-07-17T07:36:40.5064785Z convenience. Use whichever one you'd like. 2025-07-17T07:36:40.5065019Z 2025-07-17T07:36:40.5065100Z Args: 2025-07-17T07:36:40.5065423Z func (function): A Python function that takes one or more arguments. 2025-07-17T07:36:40.5065858Z Must return one or more Tensors. 2025-07-17T07:36:40.5066276Z in_dims (int or nested structure): Specifies which dimension of the 2025-07-17T07:36:40.5066759Z inputs should be mapped over. ``in_dims`` should have a 2025-07-17T07:36:40.5067237Z structure like the inputs. If the ``in_dim`` for a particular 2025-07-17T07:36:40.5067994Z input is None, then that indicates there is no map dimension. 2025-07-17T07:36:40.5068395Z Default: 0. 2025-07-17T07:36:40.5068841Z out_dims (int or Tuple[int]): Specifies where the mapped dimension 2025-07-17T07:36:40.5069454Z should appear in the outputs. If ``out_dims`` is a Tuple, then 2025-07-17T07:36:40.5070351Z it should have one element per output. Default: 0. 2025-07-17T07:36:40.5071061Z randomness (str): Specifies whether the randomness in this 2025-07-17T07:36:40.5071568Z vmap should be the same or different across batches. If 'different', 2025-07-17T07:36:40.5072118Z the randomness for each batch will be different. If 'same', the 2025-07-17T07:36:40.5072634Z randomness will be the same across batches. If 'error', any calls to 2025-07-17T07:36:40.5073183Z random functions will error. Default: 'error'. WARNING: this flag 2025-07-17T07:36:40.5073714Z only applies to random PyTorch operations and does not apply to 2025-07-17T07:36:40.5074166Z Python's random module or numpy randomness. 2025-07-17T07:36:40.5074624Z chunk_size (None or int): If None (default), apply a single vmap over inputs. 2025-07-17T07:36:40.5075448Z If not None, then compute the vmap :attr:`chunk_size` samples at a time. 2025-07-17T07:36:40.5076044Z Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop. 2025-07-17T07:36:40.5076669Z If you run into memory issues computing the vmap, please try a non-None chunk_size. 2025-07-17T07:36:40.5077063Z 2025-07-17T07:36:40.5077145Z Returns: 2025-07-17T07:36:40.5077456Z Returns a new "batched" function. It takes the same inputs as 2025-07-17T07:36:40.5077940Z ``func``, except each input has an extra dimension at the index 2025-07-17T07:36:40.5078517Z specified by ``in_dims``. It takes returns the same outputs as 2025-07-17T07:36:40.5079011Z ``func``, except each output has an extra dimension at the index 2025-07-17T07:36:40.5079417Z specified by ``out_dims``. 2025-07-17T07:36:40.5079600Z 2025-07-17T07:36:40.5079682Z .. warning: 2025-07-17T07:36:40.5080006Z :func:`vmap` works best with functional-style code. Please do not 2025-07-17T07:36:40.5080508Z perform any side-effects in ``func``, with the exception of 2025-07-17T07:36:40.5081041Z in-place PyTorch operations. Examples of side-effects include mutating 2025-07-17T07:36:40.5081605Z Python data structures and assigning values to variables not captured 2025-07-17T07:36:40.5082036Z in ``func``. 2025-07-17T07:36:40.5082172Z 2025-07-17T07:36:40.5082414Z One example of using :func:`vmap` is to compute batched dot products. PyTorch 2025-07-17T07:36:40.5083015Z doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully 2025-07-17T07:36:40.5083569Z rummaging through docs, use :func:`vmap` to construct a new function. 2025-07-17T07:36:40.5083901Z 2025-07-17T07:36:40.5084032Z >>> torch.dot # [D], [D] -> [] 2025-07-17T07:36:40.5084434Z >>> batched_dot = torch.func.vmap(torch.dot) # [N, D], [N, D] -> [N] 2025-07-17T07:36:40.5084863Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-07-17T07:36:40.5085204Z >>> batched_dot(x, y) 2025-07-17T07:36:40.5085441Z 2025-07-17T07:36:40.5085677Z :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler 2025-07-17T07:36:40.5086115Z model authoring experience. 2025-07-17T07:36:40.5086304Z 2025-07-17T07:36:40.5086411Z >>> batch_size, feature_size = 3, 5 2025-07-17T07:36:40.5086795Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-07-17T07:36:40.5087168Z >>> 2025-07-17T07:36:40.5087371Z >>> def model(feature_vec): 2025-07-17T07:36:40.5087686Z >>> # Very simple linear model with activation 2025-07-17T07:36:40.5088049Z >>> return feature_vec.dot(weights).relu() 2025-07-17T07:36:40.5088355Z >>> 2025-07-17T07:36:40.5088627Z >>> examples = torch.randn(batch_size, feature_size) 2025-07-17T07:36:40.5089005Z >>> result = torch.vmap(model)(examples) 2025-07-17T07:36:40.5089230Z 2025-07-17T07:36:40.5089476Z :func:`vmap` can also help vectorize computations that were previously difficult 2025-07-17T07:36:40.5090083Z or impossible to batch. One example is higher-order gradient computation. 2025-07-17T07:36:40.5090660Z The PyTorch autograd engine computes vjps (vector-Jacobian products). 2025-07-17T07:36:40.5091233Z Computing a full Jacobian matrix for some function f: R^N -> R^N usually 2025-07-17T07:36:40.5091814Z requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`, 2025-07-17T07:36:40.5092412Z we can vectorize the whole computation, computing the Jacobian in a single 2025-07-17T07:36:40.5092868Z call to ``autograd.grad``. 2025-07-17T07:36:40.5093040Z 2025-07-17T07:36:40.5093123Z >>> # Setup 2025-07-17T07:36:40.5093342Z >>> N = 5 2025-07-17T07:36:40.5093573Z >>> f = lambda x: x**2 2025-07-17T07:36:40.5093850Z >>> x = torch.randn(N, requires_grad=True) 2025-07-17T07:36:40.5094166Z >>> y = f(x) 2025-07-17T07:36:40.5094397Z >>> I_N = torch.eye(N) 2025-07-17T07:36:40.5094634Z >>> 2025-07-17T07:36:40.5094849Z >>> # Sequential approach 2025-07-17T07:36:40.5095332Z >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0] 2025-07-17T07:36:40.5095776Z >>> for v in I_N.unbind()] 2025-07-17T07:36:40.5096106Z >>> jacobian = torch.stack(jacobian_rows) 2025-07-17T07:36:40.5096420Z >>> 2025-07-17T07:36:40.5096654Z >>> # vectorized gradient computation 2025-07-17T07:36:40.5096954Z >>> def get_vjp(v): 2025-07-17T07:36:40.5097233Z >>> return torch.autograd.grad(y, x, v) 2025-07-17T07:36:40.5097580Z >>> jacobian = torch.vmap(get_vjp)(I_N) 2025-07-17T07:36:40.5097797Z 2025-07-17T07:36:40.5098054Z :func:`vmap` can also be nested, producing an output with multiple batched dimensions 2025-07-17T07:36:40.5098506Z 2025-07-17T07:36:40.5098608Z >>> torch.dot # [D], [D] -> [] 2025-07-17T07:36:40.5098912Z >>> batched_dot = torch.vmap( 2025-07-17T07:36:40.5099206Z ... torch.vmap(torch.dot) 2025-07-17T07:36:40.5099498Z ... ) # [N1, N0, D], [N1, N0, D] -> [N1, N0] 2025-07-17T07:36:40.5099864Z >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5) 2025-07-17T07:36:40.5100235Z >>> batched_dot(x, y) # tensor of size [2, 3] 2025-07-17T07:36:40.5100467Z 2025-07-17T07:36:40.5100703Z If the inputs are not batched along the first dimension, ``in_dims`` specifies 2025-07-17T07:36:40.5101210Z the dimension that each inputs are batched along as 2025-07-17T07:36:40.5101481Z 2025-07-17T07:36:40.5101582Z >>> torch.dot # [N], [N] -> [] 2025-07-17T07:36:40.5102002Z >>> batched_dot = torch.vmap(torch.dot, in_dims=1) # [N, D], [N, D] -> [D] 2025-07-17T07:36:40.5102449Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-07-17T07:36:40.5102785Z >>> batched_dot( 2025-07-17T07:36:40.5103023Z ... x, y 2025-07-17T07:36:40.5103342Z ... ) # output is [5] instead of [2] if batched along the 0th dimension 2025-07-17T07:36:40.5103659Z 2025-07-17T07:36:40.5103913Z If there are multiple inputs each of which is batched along different dimensions, 2025-07-17T07:36:40.5104499Z ``in_dims`` must be a tuple with the batch dimension for each input as 2025-07-17T07:36:40.5104806Z 2025-07-17T07:36:40.5104915Z >>> torch.dot # [D], [D] -> [] 2025-07-17T07:36:40.5105337Z >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None)) # [N, D], [D] -> [N] 2025-07-17T07:36:40.5105811Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-07-17T07:36:40.5106132Z >>> batched_dot( 2025-07-17T07:36:40.5106351Z ... x, y 2025-07-17T07:36:40.5106676Z ... ) # second arg doesn't have a batch dim because in_dim[1] was None 2025-07-17T07:36:40.5106981Z 2025-07-17T07:36:40.5107222Z If the input is a Python struct, ``in_dims`` must be a tuple containing a struct 2025-07-17T07:36:40.5107690Z matching the shape of the input: 2025-07-17T07:36:40.5107884Z 2025-07-17T07:36:40.5108021Z >>> f = lambda dict: torch.dot(dict["x"], dict["y"]) 2025-07-17T07:36:40.5108388Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-07-17T07:36:40.5108716Z >>> input = {"x": x, "y": y} 2025-07-17T07:36:40.5109070Z >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},)) 2025-07-17T07:36:40.5109458Z >>> batched_dot(input) 2025-07-17T07:36:40.5109623Z 2025-07-17T07:36:40.5109905Z By default, the output is batched along the first dimension. However, it can be batched 2025-07-17T07:36:40.5110422Z along any dimension by using ``out_dims`` 2025-07-17T07:36:40.5110645Z 2025-07-17T07:36:40.5110736Z >>> f = lambda x: x**2 2025-07-17T07:36:40.5111005Z >>> x = torch.randn(2, 5) 2025-07-17T07:36:40.5111310Z >>> batched_pow = torch.vmap(f, out_dims=1) 2025-07-17T07:36:40.5111632Z >>> batched_pow(x) # [5, 2] 2025-07-17T07:36:40.5111828Z 2025-07-17T07:36:40.5112114Z For any function that uses kwargs, the returned function will not batch the kwargs but will 2025-07-17T07:36:40.5112614Z accept kwargs 2025-07-17T07:36:40.5112745Z 2025-07-17T07:36:40.5112842Z >>> x = torch.randn([2, 5]) 2025-07-17T07:36:40.5113119Z >>> def fn(x, scale=4.): 2025-07-17T07:36:40.5113492Z >>> return x * scale 2025-07-17T07:36:40.5113744Z >>> 2025-07-17T07:36:40.5113954Z >>> batched_pow = torch.vmap(fn) 2025-07-17T07:36:40.5114299Z >>> assert torch.allclose(batched_pow(x), x * 4) 2025-07-17T07:36:40.5114773Z >>> batched_pow(x, scale=x) # scale is not batched, output has shape [2, 2, 5] 2025-07-17T07:36:40.5115114Z 2025-07-17T07:36:40.5115213Z .. note:: 2025-07-17T07:36:40.5115546Z vmap does not provide general autobatching or handle variable-length 2025-07-17T07:36:40.5115984Z sequences out of the box. 2025-07-17T07:36:40.5116163Z 2025-07-17T07:36:40.5116411Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:40.5116789Z 2025-07-17T07:36:40.5117374Z msg = Cannot scrape callname=grad in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=306. 2025-07-17T07:36:40.5118207Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:40.5118822Z ``grad`` operator helps computing gradients of ``func`` with respect to the 2025-07-17T07:36:40.5119366Z input(s) specified by ``argnums``. This operator can be nested to 2025-07-17T07:36:40.5119779Z compute higher-order gradients. 2025-07-17T07:36:40.5119996Z 2025-07-17T07:36:40.5120076Z Args: 2025-07-17T07:36:40.5120407Z func (Callable): A Python function that takes one or more arguments. 2025-07-17T07:36:40.5120992Z Must return a single-element Tensor. If specified ``has_aux`` equals ``True``, 2025-07-17T07:36:40.5121627Z function can return a tuple of single-element Tensor and other auxiliary objects: 2025-07-17T07:36:40.5122112Z ``(output, aux)``. 2025-07-17T07:36:40.5122566Z argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to. 2025-07-17T07:36:40.5123166Z ``argnums`` can be single integer or tuple of integers. Default: 0. 2025-07-17T07:36:40.5123701Z has_aux (bool): Flag indicating that ``func`` returns a tensor and other 2025-07-17T07:36:40.5124189Z auxiliary objects: ``(output, aux)``. Default: False. 2025-07-17T07:36:40.5124473Z 2025-07-17T07:36:40.5124556Z Returns: 2025-07-17T07:36:40.5124961Z Function to compute gradients with respect to its inputs. By default, the output of 2025-07-17T07:36:40.5125675Z the function is the gradient tensor(s) with respect to the first argument. 2025-07-17T07:36:40.5126301Z If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects 2025-07-17T07:36:40.5126936Z is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with 2025-07-17T07:36:40.5127451Z respect to each ``argnums`` value is returned. 2025-07-17T07:36:40.5127700Z 2025-07-17T07:36:40.5127800Z Example of using ``grad``: 2025-07-17T07:36:40.5127992Z 2025-07-17T07:36:40.5128086Z >>> # xdoctest: +SKIP 2025-07-17T07:36:40.5128376Z >>> from torch.func import grad 2025-07-17T07:36:40.5128679Z >>> x = torch.randn([]) 2025-07-17T07:36:40.5128981Z >>> cos_x = grad(lambda x: torch.sin(x))(x) 2025-07-17T07:36:40.5129338Z >>> assert torch.allclose(cos_x, x.cos()) 2025-07-17T07:36:40.5129641Z >>> 2025-07-17T07:36:40.5129867Z >>> # Second-order gradients 2025-07-17T07:36:40.5130220Z >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x) 2025-07-17T07:36:40.5130616Z >>> assert torch.allclose(neg_sin_x, -x.sin()) 2025-07-17T07:36:40.5130854Z 2025-07-17T07:36:40.5131099Z When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients: 2025-07-17T07:36:40.5131477Z 2025-07-17T07:36:40.5131582Z >>> # xdoctest: +SKIP 2025-07-17T07:36:40.5131881Z >>> from torch.func import grad, vmap 2025-07-17T07:36:40.5132244Z >>> batch_size, feature_size = 3, 5 2025-07-17T07:36:40.5132548Z >>> 2025-07-17T07:36:40.5132786Z >>> def model(weights, feature_vec): 2025-07-17T07:36:40.5133218Z >>> # Very simple linear model with activation 2025-07-17T07:36:40.5133562Z >>> assert feature_vec.dim() == 1 2025-07-17T07:36:40.5133914Z >>> return feature_vec.dot(weights).relu() 2025-07-17T07:36:40.5134235Z >>> 2025-07-17T07:36:40.5134479Z >>> def compute_loss(weights, example, target): 2025-07-17T07:36:40.5134834Z >>> y = model(weights, example) 2025-07-17T07:36:40.5135183Z >>> return ((y - target) ** 2).mean() # MSELoss 2025-07-17T07:36:40.5135496Z >>> 2025-07-17T07:36:40.5135791Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-07-17T07:36:40.5136281Z >>> examples = torch.randn(batch_size, feature_size) 2025-07-17T07:36:40.5136648Z >>> targets = torch.randn(batch_size) 2025-07-17T07:36:40.5136996Z >>> inputs = (weights, examples, targets) 2025-07-17T07:36:40.5137461Z >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))( 2025-07-17T07:36:40.5137912Z ... *inputs 2025-07-17T07:36:40.5138139Z ... ) 2025-07-17T07:36:40.5138276Z 2025-07-17T07:36:40.5138448Z Example of using ``grad`` with ``has_aux`` and ``argnums``: 2025-07-17T07:36:40.5138736Z 2025-07-17T07:36:40.5138844Z >>> # xdoctest: +SKIP 2025-07-17T07:36:40.5139121Z >>> from torch.func import grad 2025-07-17T07:36:40.5139443Z >>> def my_loss_func(y, y_pred): 2025-07-17T07:36:40.5139784Z >>> loss_per_sample = (0.5 * y_pred - y) ** 2 2025-07-17T07:36:40.5140141Z >>> loss = loss_per_sample.mean() 2025-07-17T07:36:40.5140477Z >>> return loss, (y_pred, loss_per_sample) 2025-07-17T07:36:40.5140796Z >>> 2025-07-17T07:36:40.5141084Z >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True) 2025-07-17T07:36:40.5141441Z >>> y_true = torch.rand(4) 2025-07-17T07:36:40.5141770Z >>> y_preds = torch.rand(4, requires_grad=True) 2025-07-17T07:36:40.5142124Z >>> out = fn(y_true, y_preds) 2025-07-17T07:36:40.5142577Z >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample)) 2025-07-17T07:36:40.5142933Z 2025-07-17T07:36:40.5143026Z .. note:: 2025-07-17T07:36:40.5143328Z Using PyTorch ``torch.no_grad`` together with ``grad``. 2025-07-17T07:36:40.5143607Z 2025-07-17T07:36:40.5143768Z Case 1: Using ``torch.no_grad`` inside a function: 2025-07-17T07:36:40.5144024Z 2025-07-17T07:36:40.5144125Z >>> # xdoctest: +SKIP 2025-07-17T07:36:40.5144412Z >>> def f(x): 2025-07-17T07:36:40.5144682Z >>> with torch.no_grad(): 2025-07-17T07:36:40.5144993Z >>> c = x ** 2 2025-07-17T07:36:40.5145274Z >>> return x - c 2025-07-17T07:36:40.5145469Z 2025-07-17T07:36:40.5145662Z In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``. 2025-07-17T07:36:40.5145971Z 2025-07-17T07:36:40.5146165Z Case 2: Using ``grad`` inside ``torch.no_grad`` context manager: 2025-07-17T07:36:40.5146466Z 2025-07-17T07:36:40.5146564Z >>> # xdoctest: +SKIP 2025-07-17T07:36:40.5146865Z >>> with torch.no_grad(): 2025-07-17T07:36:40.5147165Z >>> grad(f)(x) 2025-07-17T07:36:40.5147339Z 2025-07-17T07:36:40.5147571Z In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the 2025-07-17T07:36:40.5148120Z outer one. This is because ``grad`` is a "function transform": its result 2025-07-17T07:36:40.5148679Z should not depend on the result of a context manager outside of ``f``. 2025-07-17T07:36:40.5149013Z 2025-07-17T07:36:40.5149105Z 2025-07-17T07:36:40.5149462Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:40.5149836Z 2025-07-17T07:36:42.0946336Z msg = Cannot scrape callname=CustomOpDef.register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py line=396. 2025-07-17T07:36:42.0947345Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:42.0948215Z Register a FakeTensor implementation for this custom op. 2025-07-17T07:36:42.0948505Z 2025-07-17T07:36:42.0948749Z This is necessary to get the operator to work efficiently with torch.compile. 2025-07-17T07:36:42.0949133Z 2025-07-17T07:36:42.0949354Z The Fake impl (sometimes also known as a meta kernel or abstract impl) 2025-07-17T07:36:42.0949916Z specifies the behavior of this operator on Tensors that carry no data. 2025-07-17T07:36:42.0950401Z Given some input Tensors with certain properties 2025-07-17T07:36:42.0950920Z (sizes/strides/storage_offset/device), it specifies what the properties of 2025-07-17T07:36:42.0951505Z the output Tensors are. 2025-07-17T07:36:42.0951691Z 2025-07-17T07:36:42.0951906Z Please see :func:`torch.library.impl_abstract` for more details. 2025-07-17T07:36:42.0952221Z 2025-07-17T07:36:42.0952303Z Args: 2025-07-17T07:36:42.0952606Z fn (Callable): The function to register as the FakeTensor 2025-07-17T07:36:42.0952997Z implementation. 2025-07-17T07:36:42.0953178Z 2025-07-17T07:36:42.0953275Z Examples: 2025-07-17T07:36:42.0953498Z >>> import torch 2025-07-17T07:36:42.0953775Z >>> import numpy as np 2025-07-17T07:36:42.0954078Z >>> from torch import Tensor 2025-07-17T07:36:42.0954363Z >>> 2025-07-17T07:36:42.0954681Z >>> # Example 1: an operator without data-dependent output shape 2025-07-17T07:36:42.0955196Z >>> @torch.library.custom_op("mylib::linear", mutates_args=()) 2025-07-17T07:36:42.0955691Z >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-07-17T07:36:42.0956115Z >>> return (x @ weight.t()) + bias 2025-07-17T07:36:42.0956426Z >>> 2025-07-17T07:36:42.0956696Z >>> @linear.register_fake 2025-07-17T07:36:42.0957029Z >>> def _(x, weight, bias): 2025-07-17T07:36:42.0957344Z >>> assert x.dim() == 2 2025-07-17T07:36:42.0957661Z >>> assert weight.dim() == 2 2025-07-17T07:36:42.0957974Z >>> assert bias.dim() == 1 2025-07-17T07:36:42.0958313Z >>> assert x.shape[1] == weight.shape[1] 2025-07-17T07:36:42.0958686Z >>> assert weight.shape[0] == bias.shape[0] 2025-07-17T07:36:42.0959057Z >>> assert x.device == weight.device 2025-07-17T07:36:42.0959427Z >>> return x.new_empty(x.size(0), weight.size(0)) 2025-07-17T07:36:42.0959769Z >>> 2025-07-17T07:36:42.0960005Z >>> x = torch.randn(2, 2) 2025-07-17T07:36:42.0960312Z >>> weight = torch.randn(2, 2) 2025-07-17T07:36:42.0960631Z >>> bias = torch.randn(2) 2025-07-17T07:36:42.0960968Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-07-17T07:36:42.0961396Z >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias) 2025-07-17T07:36:42.0961841Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-07-17T07:36:42.0962332Z >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias)) 2025-07-17T07:36:42.0962781Z >>> 2025-07-17T07:36:42.0963078Z >>> # Example 2: an operator with data-dependent output shape 2025-07-17T07:36:42.0963569Z >>> @torch.library.custom_op("mylib::nonzero", mutates_args=()) 2025-07-17T07:36:42.0963999Z >>> def nonzero(x: Tensor) -> Tensor: 2025-07-17T07:36:42.0964450Z >>> x_np = x.cpu().numpy() 2025-07-17T07:36:42.0964800Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-07-17T07:36:42.0965196Z >>> return torch.tensor(res, device=x.device) 2025-07-17T07:36:42.0965581Z >>> 2025-07-17T07:36:42.0965829Z >>> @nonzero.register_fake 2025-07-17T07:36:42.0966141Z >>> def _(x): 2025-07-17T07:36:42.0966458Z >>> # Number of nonzero-elements is data-dependent. 2025-07-17T07:36:42.0966976Z >>> # Since we cannot peek at the data in an abstract impl, 2025-07-17T07:36:42.0967419Z >>> # we use the ctx object to construct a new symint that 2025-07-17T07:36:42.0967821Z >>> # represents the data-dependent size. 2025-07-17T07:36:42.0968168Z >>> ctx = torch.library.get_ctx() 2025-07-17T07:36:42.0968515Z >>> nnz = ctx.new_dynamic_size() 2025-07-17T07:36:42.0968849Z >>> shape = [nnz, x.dim()] 2025-07-17T07:36:42.0969201Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-07-17T07:36:42.0969560Z >>> return result 2025-07-17T07:36:42.0969835Z >>> 2025-07-17T07:36:42.0970392Z >>> x = torch.tensor([0, 1, 2, 0, 0, 1]) 2025-07-17T07:36:42.0970750Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-07-17T07:36:42.0971149Z >>> out = torch.compile(nonzero, fullgraph=True)(x) 2025-07-17T07:36:42.0971551Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-07-17T07:36:42.0971916Z >>> assert torch.allclose(out, x.nonzero()) 2025-07-17T07:36:42.0972165Z 2025-07-17T07:36:42.0972246Z 2025-07-17T07:36:42.0972898Z Original Error: IndentationError('expected an indented block after function definition on line 36', ('', 37, 1, '_._ = None\n', 37, 2)) 2025-07-17T07:36:42.0973539Z 2025-07-17T07:36:42.0973632Z _._ = None 2025-07-17T07:36:42.0973820Z ^ 2025-07-17T07:36:42.1071710Z msg = Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_profile.py line=94. 2025-07-17T07:36:42.1072706Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.1073084Z 2025-07-17T07:36:42.1073321Z Registers a fake kernel based on the given operator profiles. This fake 2025-07-17T07:36:42.1073900Z kernel registration will override any existing fake kernel registrations. 2025-07-17T07:36:42.1074277Z 2025-07-17T07:36:42.1074483Z The input is a dictionary mapping operator names to a set of operator 2025-07-17T07:36:42.1075042Z profiles, which we will use to generate fake kernels. The operator profiles 2025-07-17T07:36:42.1075588Z are a record of the input and output tensor metadata. Based on this 2025-07-17T07:36:42.1076127Z information we will match a given input to the recorded profile, and return 2025-07-17T07:36:42.1076705Z an output with the same metadata as in the recorded profile. If a profile 2025-07-17T07:36:42.1077183Z doesn't exist then an exception will be thrown. 2025-07-17T07:36:42.1077429Z 2025-07-17T07:36:42.1077657Z The fake kernel generation is considered unsafe because it relies on the 2025-07-17T07:36:42.1078237Z rigid, pre-defined operator profiles that do not account for potential 2025-07-17T07:36:42.1078848Z variations in output behavior. Specifically, the generated kernels assume a 2025-07-17T07:36:42.1079463Z fixed relationship between input and output ranks. However, in reality, it's 2025-07-17T07:36:42.1080067Z possible that data-dependent operations may produce outputs of different 2025-07-17T07:36:42.1080645Z ranks even when given inputs of the same rank. The generated fake kernels 2025-07-17T07:36:42.1081203Z are inflexible and unable to accommodate these nuances, making them 2025-07-17T07:36:42.1081619Z potentially unsafe. 2025-07-17T07:36:42.1081779Z 2025-07-17T07:36:42.1081859Z Args: 2025-07-17T07:36:42.1082191Z op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator 2025-07-17T07:36:42.1082725Z name to a set of operator profiles from which we will generate fake 2025-07-17T07:36:42.1083117Z kernels. 2025-07-17T07:36:42.1083268Z 2025-07-17T07:36:42.1083352Z Examples: 2025-07-17T07:36:42.1083468Z 2025-07-17T07:36:42.1083647Z >>> # Example: Registering an op-profile from draft-export 2025-07-17T07:36:42.1084008Z >>> import torch 2025-07-17T07:36:42.1084320Z >>> from torch.export._draft_export import draft_export 2025-07-17T07:36:42.1084837Z >>> 2025-07-17T07:36:42.1085135Z >>> @torch.library.custom_op("mylib::foo", mutates_args=()) 2025-07-17T07:36:42.1085634Z >>> def foo(x: Tensor, y: Tensor) -> Tensor: 2025-07-17T07:36:42.1085983Z >>> return x + y 2025-07-17T07:36:42.1086242Z >>> 2025-07-17T07:36:42.1086448Z >>> class M(torch.nn.Module): 2025-07-17T07:36:42.1086749Z >>> def forward(self, a, b): 2025-07-17T07:36:42.1087097Z >>> res = torch.ops.mylib.foo(a, b) # no fake impl 2025-07-17T07:36:42.1087435Z >>> return res 2025-07-17T07:36:42.1087685Z >>> 2025-07-17T07:36:42.1087966Z >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4)) 2025-07-17T07:36:42.1088501Z >>> 2025-07-17T07:36:42.1088914Z >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles): 2025-07-17T07:36:42.1089452Z >>> decomp = ep.run_decompositions() 2025-07-17T07:36:42.1089674Z 2025-07-17T07:36:42.1089679Z 2025-07-17T07:36:42.1089945Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.1090310Z 2025-07-17T07:36:42.1126236Z msg = Cannot scrape callname=triton_op in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=21. 2025-07-17T07:36:42.1127216Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.1127881Z Create a custom operator whose implementation is backed by 1+ triton kernels. 2025-07-17T07:36:42.1128321Z 2025-07-17T07:36:42.1128535Z This is a more structured way of using triton kernels with PyTorch. 2025-07-17T07:36:42.1129178Z Prefer using triton kernels with no ``torch.library`` custom operator wrappers 2025-07-17T07:36:42.1129870Z (like :func:`torch.library.custom_op`, :func:`torch.library.triton_op`) because 2025-07-17T07:36:42.1130347Z that is simpler; 2025-07-17T07:36:42.1130835Z only use :func:`torch.library.custom_op`/:func:`torch.library.triton_op` if you 2025-07-17T07:36:42.1131501Z want to create an operator that behaves like PyTorch built-in operators. 2025-07-17T07:36:42.1132126Z For example, you may use a ``torch.library`` wrapper API to define the 2025-07-17T07:36:42.1132686Z behavior of the triton kernel when passed a tensor subclass or under 2025-07-17T07:36:42.1133184Z a TorchDispatchMode. 2025-07-17T07:36:42.1133416Z 2025-07-17T07:36:42.1133780Z Use :func:`torch.library.triton_op` instead of :func:`torch.library.custom_op` 2025-07-17T07:36:42.1134324Z when the implementation 2025-07-17T07:36:42.1134824Z consists of 1+ triton kernels. :func:`torch.library.custom_op` treats 2025-07-17T07:36:42.1135320Z custom operators as opaque (:func:`torch.compile` and 2025-07-17T07:36:42.1135838Z :func:`torch.export.export` will never trace into them), but ``triton_op`` 2025-07-17T07:36:42.1136416Z makes the implementation visible to these subsystems, allowing them 2025-07-17T07:36:42.1136860Z to optimize the triton kernel(s). 2025-07-17T07:36:42.1137125Z 2025-07-17T07:36:42.1137308Z Note that ``fn`` must only consist of calls to PyTorch-understood 2025-07-17T07:36:42.1137839Z operators and triton kernels. Any triton kernels called inside ``fn`` 2025-07-17T07:36:42.1138373Z must be wrapped in a call to :func:`torch.library.wrap_triton`. 2025-07-17T07:36:42.1138674Z 2025-07-17T07:36:42.1138757Z Args: 2025-07-17T07:36:42.1139111Z name (str): A name for the custom op that looks like "{namespace}::{name}", 2025-07-17T07:36:42.1139662Z e.g. "mylib::my_linear". The name is used as the op's stable identifier 2025-07-17T07:36:42.1140148Z in PyTorch subsystems (e.g. torch.export, FX graphs). 2025-07-17T07:36:42.1140707Z To avoid name collisions, please use your project name as the namespace; 2025-07-17T07:36:42.1141257Z e.g. all custom ops in pytorch/fbgemm use "fbgemm" as the namespace. 2025-07-17T07:36:42.1141856Z mutates_args (Iterable[str] or "unknown"): The names of args that the function mutates. 2025-07-17T07:36:42.1142603Z This MUST be accurate, otherwise, the behavior is undefined. If "unknown", 2025-07-17T07:36:42.1143214Z it pessimistically assumes that all inputs to the operator are being mutated. 2025-07-17T07:36:42.1143788Z schema (None | str): A schema string for the operator. If None 2025-07-17T07:36:42.1144300Z (recommended) we'll infer a schema for the operator from its type 2025-07-17T07:36:42.1144832Z annotations. We recommend letting us infer a schema unless you 2025-07-17T07:36:42.1145259Z have a specific reason not to. 2025-07-17T07:36:42.1145703Z Example: "(Tensor x, int y) -> (Tensor, Tensor)". 2025-07-17T07:36:42.1145962Z 2025-07-17T07:36:42.1146063Z Example:: 2025-07-17T07:36:42.1146188Z 2025-07-17T07:36:42.1146323Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:42.1146670Z >>> import torch 2025-07-17T07:36:42.1146990Z >>> from torch.library import triton_op, wrap_triton 2025-07-17T07:36:42.1147342Z >>> 2025-07-17T07:36:42.1147615Z >>> import triton 2025-07-17T07:36:42.1147896Z >>> from triton import language as tl 2025-07-17T07:36:42.1148207Z >>> 2025-07-17T07:36:42.1148405Z >>> @triton.jit 2025-07-17T07:36:42.1148652Z >>> def add_kernel( 2025-07-17T07:36:42.1148911Z >>> in_ptr0, 2025-07-17T07:36:42.1149162Z >>> in_ptr1, 2025-07-17T07:36:42.1149407Z >>> out_ptr, 2025-07-17T07:36:42.1149718Z >>> n_elements, 2025-07-17T07:36:42.1150003Z >>> BLOCK_SIZE: "tl.constexpr", 2025-07-17T07:36:42.1150354Z >>> ): 2025-07-17T07:36:42.1150682Z >>> pid = tl.program_id(axis=0) 2025-07-17T07:36:42.1151019Z >>> block_start = pid * BLOCK_SIZE 2025-07-17T07:36:42.1151460Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-07-17T07:36:42.1151838Z >>> mask = offsets < n_elements 2025-07-17T07:36:42.1152249Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-07-17T07:36:42.1152620Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-07-17T07:36:42.1153033Z >>> output = x + y 2025-07-17T07:36:42.1153349Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-07-17T07:36:42.1153764Z >>> 2025-07-17T07:36:42.1154025Z >>> @triton_op("mylib::add", mutates_args={}) 2025-07-17T07:36:42.1154506Z >>> def add(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor: 2025-07-17T07:36:42.1154925Z >>> output = torch.empty_like(x) 2025-07-17T07:36:42.1155329Z >>> n_elements = output.numel() 2025-07-17T07:36:42.1155640Z >>> 2025-07-17T07:36:42.1155849Z >>> def grid(meta): 2025-07-17T07:36:42.1156274Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-07-17T07:36:42.1156650Z >>> 2025-07-17T07:36:42.1157003Z >>> # NB: we need to wrap the triton kernel in a call to wrap_triton 2025-07-17T07:36:42.1157488Z >>> wrap_triton(add_kernel)[grid](x, y, output, n_elements, 16) 2025-07-17T07:36:42.1157956Z >>> return output 2025-07-17T07:36:42.1158205Z >>> 2025-07-17T07:36:42.1158486Z >>> @torch.compile 2025-07-17T07:36:42.1158744Z >>> def f(x, y): 2025-07-17T07:36:42.1158989Z >>> return add(x, y) 2025-07-17T07:36:42.1159337Z >>> 2025-07-17T07:36:42.1159572Z >>> x = torch.randn(3, device="cuda") 2025-07-17T07:36:42.1159929Z >>> y = torch.randn(3, device="cuda") 2025-07-17T07:36:42.1160270Z >>> 2025-07-17T07:36:42.1160477Z >>> z = f(x, y) 2025-07-17T07:36:42.1160795Z >>> assert torch.allclose(z, x + y) 2025-07-17T07:36:42.1161032Z 2025-07-17T07:36:42.1161111Z 2025-07-17T07:36:42.1161476Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.1161917Z 2025-07-17T07:36:42.1162501Z msg = Cannot scrape callname=wrap_triton in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=202. 2025-07-17T07:36:42.1163536Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.1164173Z Allows capture of a triton kernel into a graph via make_fx or 2025-07-17T07:36:42.1164586Z non-strict ``torch.export``. 2025-07-17T07:36:42.1164777Z 2025-07-17T07:36:42.1165066Z These technologies perform Dispatcher-based tracing (via 2025-07-17T07:36:42.1165615Z ``__torch_dispatch__``) and cannot see calls to raw triton kernels. 2025-07-17T07:36:42.1166131Z The ``wrap_triton`` API wraps a triton kernel into a callable that 2025-07-17T07:36:42.1166705Z can actually be traced into a graph. 2025-07-17T07:36:42.1166924Z 2025-07-17T07:36:42.1167147Z Please use this API together with :func:`torch.library.triton_op`. 2025-07-17T07:36:42.1167469Z 2025-07-17T07:36:42.1167555Z Examples: 2025-07-17T07:36:42.1167698Z 2025-07-17T07:36:42.1167800Z >>> # xdoctest: +SKIP 2025-07-17T07:36:42.1168087Z >>> import torch 2025-07-17T07:36:42.1168339Z >>> import triton 2025-07-17T07:36:42.1168695Z >>> from triton import language as tl 2025-07-17T07:36:42.1169105Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-07-17T07:36:42.1169513Z >>> from torch.library import wrap_triton 2025-07-17T07:36:42.1169839Z >>> 2025-07-17T07:36:42.1170200Z >>> @triton.jit 2025-07-17T07:36:42.1170439Z >>> def add_kernel( 2025-07-17T07:36:42.1170702Z >>> in_ptr0, 2025-07-17T07:36:42.1170952Z >>> in_ptr1, 2025-07-17T07:36:42.1171197Z >>> out_ptr, 2025-07-17T07:36:42.1171438Z >>> n_elements, 2025-07-17T07:36:42.1171753Z >>> BLOCK_SIZE: "tl.constexpr", 2025-07-17T07:36:42.1172056Z >>> ): 2025-07-17T07:36:42.1172298Z >>> pid = tl.program_id(axis=0) 2025-07-17T07:36:42.1172698Z >>> block_start = pid * BLOCK_SIZE 2025-07-17T07:36:42.1173091Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-07-17T07:36:42.1173449Z >>> mask = offsets < n_elements 2025-07-17T07:36:42.1173791Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-07-17T07:36:42.1174156Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-07-17T07:36:42.1174482Z >>> output = x + y 2025-07-17T07:36:42.1174803Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-07-17T07:36:42.1175139Z >>> 2025-07-17T07:36:42.1175350Z >>> def add(x, y): 2025-07-17T07:36:42.1175616Z >>> output = torch.empty_like(x) 2025-07-17T07:36:42.1175950Z >>> n_elements = output.numel() 2025-07-17T07:36:42.1176252Z >>> 2025-07-17T07:36:42.1176457Z >>> def grid_fn(meta): 2025-07-17T07:36:42.1176822Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-07-17T07:36:42.1177192Z >>> 2025-07-17T07:36:42.1177497Z >>> wrap_triton(add_kernel)[grid_fn](x, y, output, n_elements, 16) 2025-07-17T07:36:42.1177906Z >>> return output 2025-07-17T07:36:42.1178166Z >>> 2025-07-17T07:36:42.1178389Z >>> x = torch.randn(3, device="cuda") 2025-07-17T07:36:42.1178722Z >>> y = torch.randn(3, device="cuda") 2025-07-17T07:36:42.1179051Z >>> gm = make_fx(add)(x, y) 2025-07-17T07:36:42.1179388Z >>> print(gm.code) 2025-07-17T07:36:42.1179685Z >>> # def forward(self, x_1, y_1): 2025-07-17T07:36:42.1180134Z >>> # empty_like = torch.ops.aten.empty_like.default(x_1, pin_memory = False) 2025-07-17T07:36:42.1180733Z >>> # triton_kernel_wrapper_mutation_proxy = triton_kernel_wrapper_mutation( 2025-07-17T07:36:42.1181210Z >>> # kernel_idx = 0, constant_args_idx = 0, 2025-07-17T07:36:42.1181563Z >>> # grid = [(1, 1, 1)], kwargs = { 2025-07-17T07:36:42.1181937Z >>> # 'in_ptr0': x_1, 'in_ptr1': y_1, 'out_ptr': empty_like, 2025-07-17T07:36:42.1182477Z >>> # 'n_elements': 3, 'BLOCK_SIZE': 16 2025-07-17T07:36:42.1182806Z >>> # }) 2025-07-17T07:36:42.1183070Z >>> # return empty_like 2025-07-17T07:36:42.1183266Z 2025-07-17T07:36:42.1183359Z 2025-07-17T07:36:42.1183713Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.1184094Z 2025-07-17T07:36:42.1873398Z msg = Cannot scrape callname=print_assert_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=286. 2025-07-17T07:36:42.1874528Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.1874909Z 2025-07-17T07:36:42.1875140Z Test if two objects are equal, and print an error message if test fails. 2025-07-17T07:36:42.1875531Z 2025-07-17T07:36:42.1875778Z The test is performed with ``actual == desired``. 2025-07-17T07:36:42.1876094Z 2025-07-17T07:36:42.1876198Z Parameters 2025-07-17T07:36:42.1876417Z ---------- 2025-07-17T07:36:42.1876629Z test_string : str 2025-07-17T07:36:42.1877060Z The message supplied to AssertionError. 2025-07-17T07:36:42.1877426Z actual : object 2025-07-17T07:36:42.1877721Z The object to test for equality against `desired`. 2025-07-17T07:36:42.1878066Z desired : object 2025-07-17T07:36:42.1878312Z The expected result. 2025-07-17T07:36:42.1878477Z 2025-07-17T07:36:42.1878575Z Examples 2025-07-17T07:36:42.1878769Z -------- 2025-07-17T07:36:42.1878999Z >>> np.testing.print_assert_equal( 2025-07-17T07:36:42.1879321Z ... "Test XYZ of func xyz", [0, 1], [0, 1] 2025-07-17T07:36:42.1879671Z ... ) # doctest: +SKIP 2025-07-17T07:36:42.1880094Z >>> np.testing.print_assert_equal( 2025-07-17T07:36:42.1880485Z ... "Test XYZ of func xyz", [0, 1], [0, 2] 2025-07-17T07:36:42.1880830Z ... ) # doctest: +SKIP 2025-07-17T07:36:42.1881245Z Traceback (most recent call last): 2025-07-17T07:36:42.1881651Z ... 2025-07-17T07:36:42.1881878Z AssertionError: Test XYZ of func xyz failed 2025-07-17T07:36:42.1882192Z ACTUAL: 2025-07-17T07:36:42.1882456Z [0, 1] 2025-07-17T07:36:42.1882701Z DESIRED: 2025-07-17T07:36:42.1882899Z [0, 2] 2025-07-17T07:36:42.1883008Z 2025-07-17T07:36:42.1883012Z 2025-07-17T07:36:42.1883345Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.1883725Z 2025-07-17T07:36:42.1884362Z msg = Cannot scrape callname=assert_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=331. 2025-07-17T07:36:42.1885496Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.1886072Z 2025-07-17T07:36:42.1886396Z Raises an AssertionError if two items are not equal up to desired 2025-07-17T07:36:42.1887027Z precision. 2025-07-17T07:36:42.1887181Z 2025-07-17T07:36:42.1887371Z .. note:: It is recommended to use one of `assert_allclose`, 2025-07-17T07:36:42.1887837Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-07-17T07:36:42.1888329Z instead of this function for more consistent floating point 2025-07-17T07:36:42.1888712Z comparisons. 2025-07-17T07:36:42.1888874Z 2025-07-17T07:36:42.1889087Z The test verifies that the elements of `actual` and `desired` satisfy. 2025-07-17T07:36:42.1889417Z 2025-07-17T07:36:42.1889583Z ``abs(desired-actual) < float64(1.5 * 10**(-decimal))`` 2025-07-17T07:36:42.1889849Z 2025-07-17T07:36:42.1890083Z That is a looser test than originally documented, but agrees with what the 2025-07-17T07:36:42.1890812Z actual implementation in `assert_array_almost_equal` did up to rounding 2025-07-17T07:36:42.1891551Z vagaries. An exception is raised at conflicting values. For ndarrays this 2025-07-17T07:36:42.1892313Z delegates to assert_array_almost_equal 2025-07-17T07:36:42.1892530Z 2025-07-17T07:36:42.1892616Z Parameters 2025-07-17T07:36:42.1892829Z ---------- 2025-07-17T07:36:42.1893044Z actual : array_like 2025-07-17T07:36:42.1893489Z The object to check. 2025-07-17T07:36:42.1893757Z desired : array_like 2025-07-17T07:36:42.1894011Z The expected object. 2025-07-17T07:36:42.1894263Z decimal : int, optional 2025-07-17T07:36:42.1894540Z Desired precision, default is 7. 2025-07-17T07:36:42.1894848Z err_msg : str, optional 2025-07-17T07:36:42.1895154Z The error message to be printed in case of failure. 2025-07-17T07:36:42.1895538Z verbose : bool, optional 2025-07-17T07:36:42.1895906Z If True, the conflicting values are appended to the error message. 2025-07-17T07:36:42.1896220Z 2025-07-17T07:36:42.1896312Z Raises 2025-07-17T07:36:42.1896495Z ------ 2025-07-17T07:36:42.1896699Z AssertionError 2025-07-17T07:36:42.1897097Z If actual and desired are not equal up to specified precision. 2025-07-17T07:36:42.1897400Z 2025-07-17T07:36:42.1897481Z See Also 2025-07-17T07:36:42.1897678Z -------- 2025-07-17T07:36:42.1898032Z assert_allclose: Compare two array_like objects for equality with desired 2025-07-17T07:36:42.1898516Z relative and/or absolute precision. 2025-07-17T07:36:42.1898951Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-07-17T07:36:42.1899282Z 2025-07-17T07:36:42.1899363Z Examples 2025-07-17T07:36:42.1899563Z -------- 2025-07-17T07:36:42.1899824Z >>> from torch._numpy.testing import assert_almost_equal 2025-07-17T07:36:42.1900227Z >>> assert_almost_equal(2.3333333333333, 2.33333334) 2025-07-17T07:36:42.1900637Z >>> assert_almost_equal(2.3333333333333, 2.33333334, decimal=10) 2025-07-17T07:36:42.1901021Z Traceback (most recent call last): 2025-07-17T07:36:42.1901306Z ... 2025-07-17T07:36:42.1901510Z AssertionError: 2025-07-17T07:36:42.1901761Z Arrays are not almost equal to 10 decimals 2025-07-17T07:36:42.1902078Z ACTUAL: 2.3333333333333 2025-07-17T07:36:42.1902329Z DESIRED: 2.33333334 2025-07-17T07:36:42.1902473Z 2025-07-17T07:36:42.1902577Z >>> assert_almost_equal( 2025-07-17T07:36:42.1902924Z ... np.array([1.0, 2.3333333333333]), np.array([1.0, 2.33333334]), decimal=9 2025-07-17T07:36:42.1903343Z ... ) 2025-07-17T07:36:42.1903567Z Traceback (most recent call last): 2025-07-17T07:36:42.1903846Z ... 2025-07-17T07:36:42.1904059Z AssertionError: 2025-07-17T07:36:42.1904317Z Arrays are not almost equal to 9 decimals 2025-07-17T07:36:42.1904618Z 2025-07-17T07:36:42.1904851Z Mismatched elements: 1 / 2 (50%) 2025-07-17T07:36:42.1905176Z Max absolute difference: 6.666699636781459e-09 2025-07-17T07:36:42.1905525Z Max relative difference: 2.8571569790287484e-09 2025-07-17T07:36:42.1905897Z x: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-07-17T07:36:42.1906275Z y: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-07-17T07:36:42.1906515Z 2025-07-17T07:36:42.1906522Z 2025-07-17T07:36:42.1906784Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.1907151Z 2025-07-17T07:36:42.1907712Z msg = Cannot scrape callname=assert_approx_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=457. 2025-07-17T07:36:42.1908655Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.1909053Z 2025-07-17T07:36:42.1909272Z Raises an AssertionError if two items are not equal up to significant 2025-07-17T07:36:42.1909694Z digits. 2025-07-17T07:36:42.1909807Z 2025-07-17T07:36:42.1909985Z .. note:: It is recommended to use one of `assert_allclose`, 2025-07-17T07:36:42.1910480Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-07-17T07:36:42.1910969Z instead of this function for more consistent floating point 2025-07-17T07:36:42.1911355Z comparisons. 2025-07-17T07:36:42.1911522Z 2025-07-17T07:36:42.1911707Z Given two numbers, check that they are approximately equal. 2025-07-17T07:36:42.1912226Z Approximately equal is defined as the number of significant digits 2025-07-17T07:36:42.1912650Z that agree. 2025-07-17T07:36:42.1912775Z 2025-07-17T07:36:42.1912862Z Parameters 2025-07-17T07:36:42.1913152Z ---------- 2025-07-17T07:36:42.1913368Z actual : scalar 2025-07-17T07:36:42.1913591Z The object to check. 2025-07-17T07:36:42.1913851Z desired : scalar 2025-07-17T07:36:42.1914091Z The expected object. 2025-07-17T07:36:42.1914353Z significant : int, optional 2025-07-17T07:36:42.1914644Z Desired precision, default is 7. 2025-07-17T07:36:42.1914955Z err_msg : str, optional 2025-07-17T07:36:42.1915254Z The error message to be printed in case of failure. 2025-07-17T07:36:42.1915618Z verbose : bool, optional 2025-07-17T07:36:42.1915990Z If True, the conflicting values are appended to the error message. 2025-07-17T07:36:42.1916303Z 2025-07-17T07:36:42.1916391Z Raises 2025-07-17T07:36:42.1916631Z ------ 2025-07-17T07:36:42.1916840Z AssertionError 2025-07-17T07:36:42.1917167Z If actual and desired are not equal up to specified precision. 2025-07-17T07:36:42.1917470Z 2025-07-17T07:36:42.1917549Z See Also 2025-07-17T07:36:42.1917749Z -------- 2025-07-17T07:36:42.1918097Z assert_allclose: Compare two array_like objects for equality with desired 2025-07-17T07:36:42.1918568Z relative and/or absolute precision. 2025-07-17T07:36:42.1919011Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-07-17T07:36:42.1919330Z 2025-07-17T07:36:42.1919423Z Examples 2025-07-17T07:36:42.1919612Z -------- 2025-07-17T07:36:42.1919845Z >>> np.testing.assert_approx_equal( 2025-07-17T07:36:42.1920164Z ... 0.12345677777777e-20, 0.1234567e-20 2025-07-17T07:36:42.1920474Z ... ) # doctest: +SKIP 2025-07-17T07:36:42.1920737Z >>> np.testing.assert_approx_equal( 2025-07-17T07:36:42.1921031Z ... 0.12345670e-20, 2025-07-17T07:36:42.1921347Z ... 0.12345671e-20, # doctest: +SKIP 2025-07-17T07:36:42.1921645Z ... significant=8, 2025-07-17T07:36:42.1921882Z ... ) 2025-07-17T07:36:42.1922104Z >>> np.testing.assert_approx_equal( 2025-07-17T07:36:42.1922385Z ... 0.12345670e-20, 2025-07-17T07:36:42.1922639Z ... 0.12345672e-20, # doctest: +SKIP 2025-07-17T07:36:42.1922946Z ... significant=8, 2025-07-17T07:36:42.1923170Z ... ) 2025-07-17T07:36:42.1923446Z Traceback (most recent call last): 2025-07-17T07:36:42.1923732Z ... 2025-07-17T07:36:42.1923925Z AssertionError: 2025-07-17T07:36:42.1924230Z Items are not equal to 8 significant digits: 2025-07-17T07:36:42.1924559Z ACTUAL: 1.234567e-21 2025-07-17T07:36:42.1924794Z DESIRED: 1.2345672e-21 2025-07-17T07:36:42.1924959Z 2025-07-17T07:36:42.1925115Z the evaluated condition that raises the exception is 2025-07-17T07:36:42.1925494Z 2025-07-17T07:36:42.1925686Z >>> abs(0.12345670e-20 / 1e-21 - 0.12345672e-20 / 1e-21) >= 10 ** -(8 - 1) 2025-07-17T07:36:42.1926082Z True 2025-07-17T07:36:42.1926190Z 2025-07-17T07:36:42.1926194Z 2025-07-17T07:36:42.1926452Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.1926834Z 2025-07-17T07:36:42.1927457Z msg = Cannot scrape callname=assert_array_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=744. 2025-07-17T07:36:42.1928379Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.1928769Z 2025-07-17T07:36:42.1928972Z Raises an AssertionError if two array_like objects are not equal. 2025-07-17T07:36:42.1929303Z 2025-07-17T07:36:42.1929502Z Given two array_like objects, check that the shape is equal and all 2025-07-17T07:36:42.1930045Z elements of these objects are equal (but see the Notes for the special 2025-07-17T07:36:42.1930570Z handling of a scalar). An exception is raised at shape mismatch or 2025-07-17T07:36:42.1931107Z conflicting values. In contrast to the standard usage in numpy, NaNs 2025-07-17T07:36:42.1931664Z are compared like numbers, no assertion is raised if both objects have 2025-07-17T07:36:42.1932093Z NaNs in the same positions. 2025-07-17T07:36:42.1932280Z 2025-07-17T07:36:42.1932501Z The usual caution for verifying equality with floating point numbers is 2025-07-17T07:36:42.1932931Z advised. 2025-07-17T07:36:42.1933180Z 2025-07-17T07:36:42.1933283Z Parameters 2025-07-17T07:36:42.1933477Z ---------- 2025-07-17T07:36:42.1933685Z x : array_like 2025-07-17T07:36:42.1933922Z The actual object to check. 2025-07-17T07:36:42.1934235Z y : array_like 2025-07-17T07:36:42.1934473Z The desired, expected object. 2025-07-17T07:36:42.1934766Z err_msg : str, optional 2025-07-17T07:36:42.1935063Z The error message to be printed in case of failure. 2025-07-17T07:36:42.1935422Z verbose : bool, optional 2025-07-17T07:36:42.1935792Z If True, the conflicting values are appended to the error message. 2025-07-17T07:36:42.1936197Z strict : bool, optional 2025-07-17T07:36:42.1936611Z If True, raise an AssertionError when either the shape or the data 2025-07-17T07:36:42.1937102Z type of the array_like objects does not match. The special 2025-07-17T07:36:42.1937592Z handling for scalars mentioned in the Notes section is disabled. 2025-07-17T07:36:42.1937903Z 2025-07-17T07:36:42.1937981Z Raises 2025-07-17T07:36:42.1938181Z ------ 2025-07-17T07:36:42.1938397Z AssertionError 2025-07-17T07:36:42.1938654Z If actual and desired objects are not equal. 2025-07-17T07:36:42.1938905Z 2025-07-17T07:36:42.1938986Z See Also 2025-07-17T07:36:42.1939188Z -------- 2025-07-17T07:36:42.1939528Z assert_allclose: Compare two array_like objects for equality with desired 2025-07-17T07:36:42.1940009Z relative and/or absolute precision. 2025-07-17T07:36:42.1940453Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-07-17T07:36:42.1940770Z 2025-07-17T07:36:42.1940858Z Notes 2025-07-17T07:36:42.1941040Z ----- 2025-07-17T07:36:42.1941330Z When one of `x` and `y` is a scalar and the other is array_like, the 2025-07-17T07:36:42.1942027Z function checks that each element of the array_like object is equal to 2025-07-17T07:36:42.1942619Z the scalar. This behaviour can be disabled with the `strict` parameter. 2025-07-17T07:36:42.1943156Z 2025-07-17T07:36:42.1943265Z Examples 2025-07-17T07:36:42.1943473Z -------- 2025-07-17T07:36:42.1952834Z The first assert does not raise an exception: 2025-07-17T07:36:42.1953118Z 2025-07-17T07:36:42.1953233Z >>> np.testing.assert_array_equal( 2025-07-17T07:36:42.1953592Z ... [1.0, 2.33333, np.nan], [np.exp(0), 2.33333, np.nan] 2025-07-17T07:36:42.1953925Z ... ) 2025-07-17T07:36:42.1954054Z 2025-07-17T07:36:42.1954280Z Use `assert_allclose` or one of the nulp (number of floating point values) 2025-07-17T07:36:42.1954741Z functions for these cases instead: 2025-07-17T07:36:42.1954942Z 2025-07-17T07:36:42.1955050Z >>> np.testing.assert_allclose( 2025-07-17T07:36:42.1955440Z ... [1.0, np.pi, np.nan], [1, np.sqrt(np.pi) ** 2, np.nan], rtol=1e-10, atol=0 2025-07-17T07:36:42.1955838Z ... ) 2025-07-17T07:36:42.1955963Z 2025-07-17T07:36:42.1956201Z As mentioned in the Notes section, `assert_array_equal` has special 2025-07-17T07:36:42.1956733Z handling for scalars. Here the test checks that each value in `x` is 3: 2025-07-17T07:36:42.1957083Z 2025-07-17T07:36:42.1957187Z >>> x = np.full((2, 5), fill_value=3) 2025-07-17T07:36:42.1957516Z >>> np.testing.assert_array_equal(x, 3) 2025-07-17T07:36:42.1957730Z 2025-07-17T07:36:42.1957940Z Use `strict` to raise an AssertionError when comparing a scalar with an 2025-07-17T07:36:42.1958356Z array: 2025-07-17T07:36:42.1958482Z 2025-07-17T07:36:42.1958661Z >>> np.testing.assert_array_equal(x, 3, strict=True) 2025-07-17T07:36:42.1959035Z Traceback (most recent call last): 2025-07-17T07:36:42.1959312Z ... 2025-07-17T07:36:42.1959524Z AssertionError: 2025-07-17T07:36:42.1959762Z Arrays are not equal 2025-07-17T07:36:42.1959992Z 2025-07-17T07:36:42.1960217Z (shapes (2, 5), () mismatch) 2025-07-17T07:36:42.1960508Z x: torch.ndarray([[3, 3, 3, 3, 3], 2025-07-17T07:36:42.1960783Z [3, 3, 3, 3, 3]]) 2025-07-17T07:36:42.1961048Z y: torch.ndarray(3) 2025-07-17T07:36:42.1961196Z 2025-07-17T07:36:42.1961415Z The `strict` parameter also ensures that the array data types match: 2025-07-17T07:36:42.1961736Z 2025-07-17T07:36:42.1961949Z >>> x = np.array([2, 2, 2]) 2025-07-17T07:36:42.1962259Z >>> y = np.array([2.0, 2.0, 2.0], dtype=np.float32) 2025-07-17T07:36:42.1962651Z >>> np.testing.assert_array_equal(x, y, strict=True) 2025-07-17T07:36:42.1963027Z Traceback (most recent call last): 2025-07-17T07:36:42.1963300Z ... 2025-07-17T07:36:42.1963511Z AssertionError: 2025-07-17T07:36:42.1963747Z Arrays are not equal 2025-07-17T07:36:42.1963974Z 2025-07-17T07:36:42.1964241Z (dtypes dtype("int64"), dtype("float32") mismatch) 2025-07-17T07:36:42.1964602Z x: torch.ndarray([2, 2, 2]) 2025-07-17T07:36:42.1964874Z y: torch.ndarray([2., 2., 2.]) 2025-07-17T07:36:42.1965069Z 2025-07-17T07:36:42.1965461Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.1965840Z 2025-07-17T07:36:42.1966471Z msg = Cannot scrape callname=assert_array_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=851. 2025-07-17T07:36:42.1967442Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.1967825Z 2025-07-17T07:36:42.1968035Z Raises an AssertionError if two objects are not equal up to desired 2025-07-17T07:36:42.1968460Z precision. 2025-07-17T07:36:42.1968581Z 2025-07-17T07:36:42.1968773Z .. note:: It is recommended to use one of `assert_allclose`, 2025-07-17T07:36:42.1969237Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-07-17T07:36:42.1969711Z instead of this function for more consistent floating point 2025-07-17T07:36:42.1970276Z comparisons. 2025-07-17T07:36:42.1970432Z 2025-07-17T07:36:42.1970685Z The test verifies identical shapes and that the elements of ``actual`` and 2025-07-17T07:36:42.1971124Z ``desired`` satisfy. 2025-07-17T07:36:42.1971289Z 2025-07-17T07:36:42.1971417Z ``abs(desired-actual) < 1.5 * 10**(-decimal)`` 2025-07-17T07:36:42.1971657Z 2025-07-17T07:36:42.1971899Z That is a looser test than originally documented, but agrees with what the 2025-07-17T07:36:42.1972491Z actual implementation did up to rounding vagaries. An exception is raised 2025-07-17T07:36:42.1973073Z at shape mismatch or conflicting values. In contrast to the standard usage 2025-07-17T07:36:42.1973640Z in numpy, NaNs are compared like numbers, no assertion is raised if both 2025-07-17T07:36:42.1974098Z objects have NaNs in the same positions. 2025-07-17T07:36:42.1974315Z 2025-07-17T07:36:42.1974403Z Parameters 2025-07-17T07:36:42.1974615Z ---------- 2025-07-17T07:36:42.1974863Z x : array_like 2025-07-17T07:36:42.1975087Z The actual object to check. 2025-07-17T07:36:42.1975363Z y : array_like 2025-07-17T07:36:42.1975606Z The desired, expected object. 2025-07-17T07:36:42.1975898Z decimal : int, optional 2025-07-17T07:36:42.1976172Z Desired precision, default is 6. 2025-07-17T07:36:42.1976480Z err_msg : str, optional 2025-07-17T07:36:42.1976824Z The error message to be printed in case of failure. 2025-07-17T07:36:42.1977174Z verbose : bool, optional 2025-07-17T07:36:42.1977554Z If True, the conflicting values are appended to the error message. 2025-07-17T07:36:42.1977869Z 2025-07-17T07:36:42.1977962Z Raises 2025-07-17T07:36:42.1978148Z ------ 2025-07-17T07:36:42.1978362Z AssertionError 2025-07-17T07:36:42.1978694Z If actual and desired are not equal up to specified precision. 2025-07-17T07:36:42.1978999Z 2025-07-17T07:36:42.1979079Z See Also 2025-07-17T07:36:42.1979280Z -------- 2025-07-17T07:36:42.1979634Z assert_allclose: Compare two array_like objects for equality with desired 2025-07-17T07:36:42.1980104Z relative and/or absolute precision. 2025-07-17T07:36:42.1980549Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-07-17T07:36:42.1980888Z 2025-07-17T07:36:42.1980970Z Examples 2025-07-17T07:36:42.1981175Z -------- 2025-07-17T07:36:42.1981407Z the first assert does not raise an exception 2025-07-17T07:36:42.1981654Z 2025-07-17T07:36:42.1981900Z >>> np.testing.assert_array_almost_equal([1.0, 2.333, np.nan], [1.0, 2.333, np.nan]) 2025-07-17T07:36:42.1982394Z 2025-07-17T07:36:42.1982524Z >>> np.testing.assert_array_almost_equal( 2025-07-17T07:36:42.1982889Z ... [1.0, 2.33333, np.nan], [1.0, 2.33339, np.nan], decimal=5 2025-07-17T07:36:42.1983238Z ... ) 2025-07-17T07:36:42.1983468Z Traceback (most recent call last): 2025-07-17T07:36:42.1983759Z ... 2025-07-17T07:36:42.1983954Z AssertionError: 2025-07-17T07:36:42.1984217Z Arrays are not almost equal to 5 decimals 2025-07-17T07:36:42.1984536Z 2025-07-17T07:36:42.1984754Z Mismatched elements: 1 / 3 (33.3%) 2025-07-17T07:36:42.1985082Z Max absolute difference: 5.999999999994898e-05 2025-07-17T07:36:42.1985448Z Max relative difference: 2.5713661239633743e-05 2025-07-17T07:36:42.1985915Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-07-17T07:36:42.1986352Z y: torch.ndarray([1.0000, 2.3334, nan], dtype=float64) 2025-07-17T07:36:42.1986621Z 2025-07-17T07:36:42.1986754Z >>> np.testing.assert_array_almost_equal( 2025-07-17T07:36:42.1987111Z ... [1.0, 2.33333, np.nan], [1.0, 2.33333, 5], decimal=5 2025-07-17T07:36:42.1987445Z ... ) 2025-07-17T07:36:42.1987675Z Traceback (most recent call last): 2025-07-17T07:36:42.1987965Z ... 2025-07-17T07:36:42.1988162Z AssertionError: 2025-07-17T07:36:42.1988422Z Arrays are not almost equal to 5 decimals 2025-07-17T07:36:42.1988736Z 2025-07-17T07:36:42.1988951Z x and y nan location mismatch: 2025-07-17T07:36:42.1989299Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-07-17T07:36:42.1989726Z y: torch.ndarray([1.0000, 2.3333, 5.0000], dtype=float64) 2025-07-17T07:36:42.1989989Z 2025-07-17T07:36:42.1989993Z 2025-07-17T07:36:42.1990244Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.1990626Z 2025-07-17T07:36:42.1991248Z msg = Cannot scrape callname=clear_and_catch_warnings in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=1848. 2025-07-17T07:36:42.1992212Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.1992808Z Context manager that resets warning registry for catching warnings 2025-07-17T07:36:42.1993130Z 2025-07-17T07:36:42.1993383Z Warnings can be slippery, because, whenever a warning is triggered, Python 2025-07-17T07:36:42.1993956Z adds a ``__warningregistry__`` member to the *calling* module. This makes 2025-07-17T07:36:42.1994535Z it impossible to retrigger the warning in this module, whatever you put in 2025-07-17T07:36:42.1995135Z the warnings filters. This context manager accepts a sequence of `modules` 2025-07-17T07:36:42.1995635Z as a keyword argument to its constructor and: 2025-07-17T07:36:42.1995882Z 2025-07-17T07:36:42.1996105Z * stores and removes any ``__warningregistry__`` entries in given `modules` 2025-07-17T07:36:42.1996539Z on entry; 2025-07-17T07:36:42.1996859Z * resets ``__warningregistry__`` to its previous state on exit. 2025-07-17T07:36:42.1997157Z 2025-07-17T07:36:42.1997381Z This makes it possible to trigger any warning afresh inside the context 2025-07-17T07:36:42.1997905Z manager without disturbing the state of warnings outside. 2025-07-17T07:36:42.1998209Z 2025-07-17T07:36:42.1998440Z For compatibility with Python 3.0, please consider all arguments to be 2025-07-17T07:36:42.1998886Z keyword-only. 2025-07-17T07:36:42.1999025Z 2025-07-17T07:36:42.1999111Z Parameters 2025-07-17T07:36:42.1999335Z ---------- 2025-07-17T07:36:42.1999567Z record : bool, optional 2025-07-17T07:36:42.1999922Z Specifies whether warnings should be captured by a custom 2025-07-17T07:36:42.2000464Z implementation of ``warnings.showwarning()`` and be appended to a list 2025-07-17T07:36:42.2001021Z returned by the context manager. Otherwise None is returned by the 2025-07-17T07:36:42.2001556Z context manager. The objects appended to the list are arguments whose 2025-07-17T07:36:42.2002073Z attributes mirror the arguments to ``showwarning()``. 2025-07-17T07:36:42.2002576Z modules : sequence, optional 2025-07-17T07:36:42.2002993Z Sequence of modules for which to reset warnings registry on entry and 2025-07-17T07:36:42.2003513Z restore on exit. To work correctly, all 'ignore' filters should 2025-07-17T07:36:42.2003931Z filter by one of these modules. 2025-07-17T07:36:42.2004141Z 2025-07-17T07:36:42.2004237Z Examples 2025-07-17T07:36:42.2004443Z -------- 2025-07-17T07:36:42.2004666Z >>> import warnings 2025-07-17T07:36:42.2005012Z >>> with np.testing.clear_and_catch_warnings( # doctest: +SKIP 2025-07-17T07:36:42.2005510Z ... modules=[np.core.fromnumeric] 2025-07-17T07:36:42.2005889Z ... ): 2025-07-17T07:36:42.2006140Z ... warnings.simplefilter("always") 2025-07-17T07:36:42.2006611Z ... warnings.filterwarnings("ignore", module="np.core.fromnumeric") 2025-07-17T07:36:42.2007123Z ... # do something that raises a warning but ignore those in 2025-07-17T07:36:42.2007517Z ... # np.core.fromnumeric 2025-07-17T07:36:42.2007791Z 2025-07-17T07:36:42.2008142Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.2008520Z 2025-07-17T07:36:42.3589367Z msg = Cannot scrape callname=Conv1d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py line=354. 2025-07-17T07:36:42.3590331Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.3590971Z Applies a 1D convolution over a quantized input signal composed of 2025-07-17T07:36:42.3591415Z several quantized input planes. 2025-07-17T07:36:42.3591621Z 2025-07-17T07:36:42.3591863Z For details on input arguments, parameters, and implementation see 2025-07-17T07:36:42.3592295Z :class:`~torch.nn.Conv1d`. 2025-07-17T07:36:42.3592476Z 2025-07-17T07:36:42.3592599Z .. note:: 2025-07-17T07:36:42.3592913Z Only `zeros` is supported for the :attr:`padding_mode` argument. 2025-07-17T07:36:42.3593247Z 2025-07-17T07:36:42.3593331Z .. note:: 2025-07-17T07:36:42.3593634Z Only `torch.quint8` is supported for the input data type. 2025-07-17T07:36:42.3593920Z 2025-07-17T07:36:42.3593924Z 2025-07-17T07:36:42.3594023Z Attributes: 2025-07-17T07:36:42.3594359Z weight (Tensor): packed tensor derived from the learnable weight 2025-07-17T07:36:42.3594790Z parameter. 2025-07-17T07:36:42.3595137Z scale (Tensor): scalar for the output scale 2025-07-17T07:36:42.3595539Z zero_point (Tensor): scalar for the output zero point 2025-07-17T07:36:42.3595827Z 2025-07-17T07:36:42.3595979Z See :class:`~torch.nn.Conv1d` for other attributes. 2025-07-17T07:36:42.3596251Z 2025-07-17T07:36:42.3596429Z Examples:: 2025-07-17T07:36:42.3596560Z 2025-07-17T07:36:42.3596715Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_QENGINE) 2025-07-17T07:36:42.3597095Z >>> m = nn.quantized.Conv1d(16, 33, 3, stride=2) 2025-07-17T07:36:42.3597480Z >>> input = torch.randn(20, 16, 100) 2025-07-17T07:36:42.3597810Z >>> # quantize input to quint8 2025-07-17T07:36:42.3598107Z >>> # xdoctest: +SKIP 2025-07-17T07:36:42.3598496Z >>> q_input = torch.quantize_per_tensor(input, scale=1.0, zero_point=0, 2025-07-17T07:36:42.3598950Z ... dtype=torch.quint8) 2025-07-17T07:36:42.3599292Z >>> output = m(q_input) 2025-07-17T07:36:42.3599472Z 2025-07-17T07:36:42.3599550Z 2025-07-17T07:36:42.3599916Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.3600300Z 2025-07-17T07:36:42.3775997Z msg = Cannot scrape callname=LSTM in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/rnn.py line=12. 2025-07-17T07:36:42.3776941Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.3777438Z A quantized long short-term memory (LSTM). 2025-07-17T07:36:42.3777930Z 2025-07-17T07:36:42.3778205Z For the description and the argument types, please, refer to :class:`~torch.nn.LSTM` 2025-07-17T07:36:42.3778615Z 2025-07-17T07:36:42.3778701Z Attributes: 2025-07-17T07:36:42.3778963Z layers : instances of the `_LSTMLayer` 2025-07-17T07:36:42.3779189Z 2025-07-17T07:36:42.3779368Z .. note:: 2025-07-17T07:36:42.3779708Z To access the weights and biases, you need to access them per layer. 2025-07-17T07:36:42.3780211Z See examples in :class:`~torch.ao.nn.quantizable.LSTM` 2025-07-17T07:36:42.3780492Z 2025-07-17T07:36:42.3780581Z Examples:: 2025-07-17T07:36:42.3780818Z >>> # xdoctest: +SKIP 2025-07-17T07:36:42.3781209Z >>> custom_module_config = { 2025-07-17T07:36:42.3781556Z ... 'float_to_observed_custom_module_class': { 2025-07-17T07:36:42.3781920Z ... nn.LSTM: nn.quantizable.LSTM, 2025-07-17T07:36:42.3782244Z ... }, 2025-07-17T07:36:42.3782537Z ... 'observed_to_quantized_custom_module_class': { 2025-07-17T07:36:42.3782936Z ... nn.quantizable.LSTM: nn.quantized.LSTM, 2025-07-17T07:36:42.3783276Z ... } 2025-07-17T07:36:42.3783496Z ... } 2025-07-17T07:36:42.3783829Z >>> tq.prepare(model, prepare_custom_module_class=custom_module_config) 2025-07-17T07:36:42.3784401Z >>> tq.convert(model, convert_custom_module_class=custom_module_config) 2025-07-17T07:36:42.3784813Z 2025-07-17T07:36:42.3785162Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.3785537Z 2025-07-17T07:36:42.4349872Z msg = Cannot scrape callname=ActivationSparsifier in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16. 2025-07-17T07:36:42.4351124Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.4351520Z 2025-07-17T07:36:42.4351792Z The Activation sparsifier class aims to sparsify/prune activations in a neural 2025-07-17T07:36:42.4352395Z network. The idea is to attach the sparsifier to a layer (or layers) and it 2025-07-17T07:36:42.4352982Z zeroes out the activations based on the mask_fn (or sparsification function) 2025-07-17T07:36:42.4353428Z input by the user. 2025-07-17T07:36:42.4353809Z The mask_fn is applied once all the inputs are aggregated and reduced i.e. 2025-07-17T07:36:42.4354299Z mask = mask_fn(reduce_fn(aggregate_fn(activations))) 2025-07-17T07:36:42.4354558Z 2025-07-17T07:36:42.4354645Z Note:: 2025-07-17T07:36:42.4355079Z The sparsification mask is computed on the input **before it goes through the attached layer**. 2025-07-17T07:36:42.4355530Z 2025-07-17T07:36:42.4355609Z Args: 2025-07-17T07:36:42.4355817Z model (nn.Module): 2025-07-17T07:36:42.4356183Z The model whose layers will be sparsified. The layers that needs to be 2025-07-17T07:36:42.4356763Z sparsified should be added separately using the register_layer() function 2025-07-17T07:36:42.4357243Z aggregate_fn (Optional, Callable): 2025-07-17T07:36:42.4357701Z default aggregate_fn that is used if not specified while registering the layer. 2025-07-17T07:36:42.4358244Z specifies how inputs should be aggregated over time. 2025-07-17T07:36:42.4358801Z The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor. 2025-07-17T07:36:42.4359290Z Example 2025-07-17T07:36:42.4359590Z def add_agg_fn(tensor1, tensor2): return tensor1 + tensor2 2025-07-17T07:36:42.4359996Z reduce_fn (Optional, Callable): 2025-07-17T07:36:42.4360464Z default reduce_fn that is used if not specified while registering the layer. 2025-07-17T07:36:42.4361065Z reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after 2025-07-17T07:36:42.4361557Z calling agg_fn() on all inputs. 2025-07-17T07:36:42.4361873Z Example 2025-07-17T07:36:42.4362381Z def mean_reduce_fn(agg_tensor): return agg_tensor.mean(dim=0) 2025-07-17T07:36:42.4362810Z mask_fn (Optional, Callable): 2025-07-17T07:36:42.4363338Z default mask_fn that is used to create the sparsification mask using the tensor obtained after 2025-07-17T07:36:42.4364016Z calling the reduce_fn(). This is used by default if a custom one is passed in the 2025-07-17T07:36:42.4364475Z register_layer(). 2025-07-17T07:36:42.4365018Z Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config 2025-07-17T07:36:42.4365661Z arguments. 2025-07-17T07:36:42.4366025Z features (Optional, list): 2025-07-17T07:36:42.4366371Z default selected features to sparsify. 2025-07-17T07:36:42.4366880Z If this is non-empty, then the mask_fn will be applied for each feature of the input. 2025-07-17T07:36:42.4367370Z For example, 2025-07-17T07:36:42.4367789Z mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features] 2025-07-17T07:36:42.4368277Z feature_dim (Optional, int): 2025-07-17T07:36:42.4368775Z default dimension of input features. Again, features along this dim will be chosen 2025-07-17T07:36:42.4369266Z for sparsification. 2025-07-17T07:36:42.4369570Z sparse_config (Dict): 2025-07-17T07:36:42.4370189Z Default configuration for the mask_fn. This config will be passed 2025-07-17T07:36:42.4370637Z with the mask_fn() 2025-07-17T07:36:42.4370828Z 2025-07-17T07:36:42.4370912Z Example: 2025-07-17T07:36:42.4371137Z >>> # xdoctest: +SKIP 2025-07-17T07:36:42.4371405Z >>> model = SomeModel() 2025-07-17T07:36:42.4371812Z >>> act_sparsifier = ActivationSparsifier(...) # init activation sparsifier 2025-07-17T07:36:42.4372275Z >>> # Initialize aggregate_fn 2025-07-17T07:36:42.4372573Z >>> def agg_fn(x, y): 2025-07-17T07:36:42.4372881Z >>> return x + y 2025-07-17T07:36:42.4373230Z >>> 2025-07-17T07:36:42.4373449Z >>> # Initialize reduce_fn 2025-07-17T07:36:42.4373771Z >>> def reduce_fn(x): 2025-07-17T07:36:42.4374141Z >>> return torch.mean(x, dim=0) 2025-07-17T07:36:42.4374438Z >>> 2025-07-17T07:36:42.4374639Z >>> # Initialize mask_fn 2025-07-17T07:36:42.4374917Z >>> def mask_fn(data): 2025-07-17T07:36:42.4375227Z >>> return torch.eye(data.shape).to(data.device) 2025-07-17T07:36:42.4375561Z >>> 2025-07-17T07:36:42.4375743Z >>> 2025-07-17T07:36:42.4375969Z >>> act_sparsifier.register_layer( 2025-07-17T07:36:42.4376287Z ... model.some_layer, 2025-07-17T07:36:42.4376551Z ... aggregate_fn=agg_fn, 2025-07-17T07:36:42.4376835Z ... reduce_fn=reduce_fn, 2025-07-17T07:36:42.4377113Z ... mask_fn=mask_fn, 2025-07-17T07:36:42.4377355Z ... ) 2025-07-17T07:36:42.4377556Z >>> 2025-07-17T07:36:42.4377775Z >>> # start training process 2025-07-17T07:36:42.4378042Z >>> for _ in [...]: 2025-07-17T07:36:42.4378290Z >>> # epoch starts 2025-07-17T07:36:42.4378614Z >>> # model.forward(), compute_loss() and model.backwards() 2025-07-17T07:36:42.4378980Z >>> # epoch ends 2025-07-17T07:36:42.4379274Z >>> act_sparsifier.step() 2025-07-17T07:36:42.4379572Z >>> # end training process 2025-07-17T07:36:42.4379852Z >>> sparsifier.squash_mask() 2025-07-17T07:36:42.4380055Z 2025-07-17T07:36:42.4380305Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.4380683Z 2025-07-17T07:36:42.4381547Z msg = Cannot scrape callname=BaseDataScheduler.get_schedule_param in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py line=91. 2025-07-17T07:36:42.4382758Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.4383135Z 2025-07-17T07:36:42.4383508Z Abstract method that needs to be implemented by the child class. 2025-07-17T07:36:42.4384067Z The expected return type should is a dictionary of name to schedule_param value 2025-07-17T07:36:42.4384709Z The returned values will be updated in sparsifier when the scheduler step() function 2025-07-17T07:36:42.4385188Z is called. 2025-07-17T07:36:42.4385306Z 2025-07-17T07:36:42.4385441Z Example: 2025-07-17T07:36:42.4385672Z >>> def get_schedule_param(self): 2025-07-17T07:36:42.4385983Z ... new_param = {} 2025-07-17T07:36:42.4386309Z ... for name in self.sparsifier.data_groups.keys(): 2025-07-17T07:36:42.4386664Z ... new_param[name] = ( 2025-07-17T07:36:42.4387158Z ... self.sparsifier.data_groups[name][self.schedule_param] * 0.5 2025-07-17T07:36:42.4387621Z ... ) 2025-07-17T07:36:42.4387847Z ... return new_param 2025-07-17T07:36:42.4388037Z 2025-07-17T07:36:42.4388368Z When the step() function is called, the value in self.sparsifier.data_groups[name][self.schedule_param] 2025-07-17T07:36:42.4388925Z would be halved 2025-07-17T07:36:42.4389060Z 2025-07-17T07:36:42.4389307Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.4389686Z 2025-07-17T07:36:42.4597150Z msg = Cannot scrape callname=BaseSparsifier.squash_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py line=229. 2025-07-17T07:36:42.4598249Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.4598799Z Squashes the sparse masks into the appropriate tensors. 2025-07-17T07:36:42.4599077Z 2025-07-17T07:36:42.4599308Z If either the `params_to_keep` or `params_to_keep_per_layer` is set, 2025-07-17T07:36:42.4599805Z the module will have a `sparse_params` dict attached to it. 2025-07-17T07:36:42.4600108Z 2025-07-17T07:36:42.4600192Z Args: 2025-07-17T07:36:42.4600504Z params_to_keep: List of keys to save in the module or a dict 2025-07-17T07:36:42.4600963Z representing the modules and keys that will have 2025-07-17T07:36:42.4601360Z sparsity parameters saved 2025-07-17T07:36:42.4601804Z params_to_keep_per_layer: Dict to specify the params that should be 2025-07-17T07:36:42.4602289Z saved for specific layers. The keys in the dict 2025-07-17T07:36:42.4602702Z should be the module fqn, while the values should 2025-07-17T07:36:42.4603132Z be a list of strings with the names of the variables 2025-07-17T07:36:42.4603534Z to save in the `sparse_params` 2025-07-17T07:36:42.4603764Z 2025-07-17T07:36:42.4603860Z Examples: 2025-07-17T07:36:42.4604119Z >>> # xdoctest: +SKIP("locals are undefined") 2025-07-17T07:36:42.4604475Z >>> # Don't save any sparse params 2025-07-17T07:36:42.4604818Z >>> sparsifier.squash_mask() 2025-07-17T07:36:42.4605160Z >>> hasattr(model.submodule1, "sparse_params") 2025-07-17T07:36:42.4605557Z False 2025-07-17T07:36:42.4605689Z 2025-07-17T07:36:42.4605816Z >>> # Keep sparse params per layer 2025-07-17T07:36:42.4606143Z >>> sparsifier.squash_mask( 2025-07-17T07:36:42.4606473Z ... params_to_keep_per_layer={ 2025-07-17T07:36:42.4606826Z ... "submodule1.linear1": ("foo", "bar"), 2025-07-17T07:36:42.4607216Z ... "submodule2.linear42": ("baz",), 2025-07-17T07:36:42.4607539Z ... } 2025-07-17T07:36:42.4607757Z ... ) 2025-07-17T07:36:42.4608054Z >>> print(model.submodule1.linear1.sparse_params) 2025-07-17T07:36:42.4608419Z {'foo': 42, 'bar': 24} 2025-07-17T07:36:42.4608753Z >>> print(model.submodule2.linear42.sparse_params) 2025-07-17T07:36:42.4609114Z {'baz': 0.1} 2025-07-17T07:36:42.4609461Z 2025-07-17T07:36:42.4609581Z >>> # Keep sparse params for all layers 2025-07-17T07:36:42.4609993Z >>> sparsifier.squash_mask(params_to_keep=("foo", "bar")) 2025-07-17T07:36:42.4610420Z >>> print(model.submodule1.linear1.sparse_params) 2025-07-17T07:36:42.4610785Z {'foo': 42, 'bar': 24} 2025-07-17T07:36:42.4611132Z >>> print(model.submodule2.linear42.sparse_params) 2025-07-17T07:36:42.4611483Z {'foo': 42, 'bar': 24} 2025-07-17T07:36:42.4611677Z 2025-07-17T07:36:42.4611870Z >>> # Keep some sparse params for all layers, and specific ones for 2025-07-17T07:36:42.4612284Z >>> # some other layers 2025-07-17T07:36:42.4612670Z >>> sparsifier.squash_mask( 2025-07-17T07:36:42.4612989Z ... params_to_keep=("foo", "bar"), 2025-07-17T07:36:42.4613407Z ... params_to_keep_per_layer={"submodule2.linear42": ("baz",)}, 2025-07-17T07:36:42.4613802Z ... ) 2025-07-17T07:36:42.4614086Z >>> print(model.submodule1.linear1.sparse_params) 2025-07-17T07:36:42.4614450Z {'foo': 42, 'bar': 24} 2025-07-17T07:36:42.4614797Z >>> print(model.submodule2.linear42.sparse_params) 2025-07-17T07:36:42.4615160Z {'foo': 42, 'bar': 24, 'baz': 0.1} 2025-07-17T07:36:42.4615463Z 2025-07-17T07:36:42.4615836Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.4616201Z 2025-07-17T07:36:42.5373978Z msg = Cannot scrape callname=DTypeConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/backend_config.py line=181. 2025-07-17T07:36:42.5375067Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.5375445Z 2025-07-17T07:36:42.5375694Z Config object that specifies the supported data types passed as arguments to 2025-07-17T07:36:42.5376304Z quantize ops in the reference model spec, for input and output activations, 2025-07-17T07:36:42.5376766Z weights, and biases. 2025-07-17T07:36:42.5376918Z 2025-07-17T07:36:42.5377068Z For example, consider the following reference model: 2025-07-17T07:36:42.5377350Z 2025-07-17T07:36:42.5377507Z quant1 - [dequant1 - fp32_linear - quant2] - dequant2 2025-07-17T07:36:42.5377819Z 2025-07-17T07:36:42.5378027Z The pattern in the square brackets refers to the reference pattern of 2025-07-17T07:36:42.5378586Z statically quantized linear. Setting the input dtype as `torch.quint8` 2025-07-17T07:36:42.5379154Z in the DTypeConfig means we pass in `torch.quint8` as the dtype argument 2025-07-17T07:36:42.5379717Z to the first quantize op (quant1). Similarly, setting the output dtype as 2025-07-17T07:36:42.5380283Z `torch.quint8` means we pass in `torch.quint8` as the dtype argument to 2025-07-17T07:36:42.5380742Z the second quantize op (quant2). 2025-07-17T07:36:42.5380938Z 2025-07-17T07:36:42.5381150Z Note that the dtype here does not refer to the interface dtypes of the 2025-07-17T07:36:42.5381698Z op. For example, the "input dtype" here is not the dtype of the input 2025-07-17T07:36:42.5382233Z tensor passed to the quantized linear op. Though it can still be the 2025-07-17T07:36:42.5382748Z same as the interface dtype, this is not always the case, e.g. the 2025-07-17T07:36:42.5383275Z interface dtype is fp32 in dynamic quantization but the "input dtype" 2025-07-17T07:36:42.5383820Z specified in the DTypeConfig would still be quint8. The semantics of 2025-07-17T07:36:42.5384352Z dtypes here are the same as the semantics of the dtypes specified in 2025-07-17T07:36:42.5384753Z the observers. 2025-07-17T07:36:42.5384896Z 2025-07-17T07:36:42.5385101Z These dtypes are matched against the ones specified in the user's 2025-07-17T07:36:42.5385665Z QConfig. If there is a match, and the QConfig satisfies the constraints 2025-07-17T07:36:42.5386219Z specified in the DTypeConfig (if any), then we will quantize the given 2025-07-17T07:36:42.5386764Z pattern using this DTypeConfig. Otherwise, the QConfig is ignored and 2025-07-17T07:36:42.5387415Z the pattern will not be quantized. 2025-07-17T07:36:42.5387615Z 2025-07-17T07:36:42.5387734Z Example usage:: 2025-07-17T07:36:42.5387872Z 2025-07-17T07:36:42.5387974Z >>> # xdoctest: +SKIP(failing) 2025-07-17T07:36:42.5388311Z >>> dtype_config1 = DTypeConfig( 2025-07-17T07:36:42.5388632Z ... input_dtype=torch.quint8, 2025-07-17T07:36:42.5388954Z ... output_dtype=torch.quint8, 2025-07-17T07:36:42.5389263Z ... weight_dtype=torch.qint8, 2025-07-17T07:36:42.5389584Z ... bias_dtype=torch.float) 2025-07-17T07:36:42.5389783Z 2025-07-17T07:36:42.5389902Z >>> dtype_config2 = DTypeConfig( 2025-07-17T07:36:42.5390309Z ... input_dtype=DTypeWithConstraints( 2025-07-17T07:36:42.5390651Z ... dtype=torch.quint8, 2025-07-17T07:36:42.5390959Z ... quant_min_lower_bound=0, 2025-07-17T07:36:42.5391271Z ... quant_max_upper_bound=255, 2025-07-17T07:36:42.5391572Z ... ), 2025-07-17T07:36:42.5391834Z ... output_dtype=DTypeWithConstraints( 2025-07-17T07:36:42.5392176Z ... dtype=torch.quint8, 2025-07-17T07:36:42.5392467Z ... quant_min_lower_bound=0, 2025-07-17T07:36:42.5392790Z ... quant_max_upper_bound=255, 2025-07-17T07:36:42.5393091Z ... ), 2025-07-17T07:36:42.5393335Z ... weight_dtype=DTypeWithConstraints( 2025-07-17T07:36:42.5393667Z ... dtype=torch.qint8, 2025-07-17T07:36:42.5393973Z ... quant_min_lower_bound=-128, 2025-07-17T07:36:42.5394285Z ... quant_max_upper_bound=127, 2025-07-17T07:36:42.5394597Z ... ), 2025-07-17T07:36:42.5394828Z ... bias_dtype=torch.float) 2025-07-17T07:36:42.5395046Z 2025-07-17T07:36:42.5395151Z >>> dtype_config1.input_dtype 2025-07-17T07:36:42.5395436Z torch.quint8 2025-07-17T07:36:42.5395584Z 2025-07-17T07:36:42.5395685Z >>> dtype_config2.input_dtype 2025-07-17T07:36:42.5395966Z torch.quint8 2025-07-17T07:36:42.5396103Z 2025-07-17T07:36:42.5396237Z >>> dtype_config2.input_dtype_with_constraints 2025-07-17T07:36:42.5397031Z DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None) 2025-07-17T07:36:42.5397683Z 2025-07-17T07:36:42.5397946Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.5398317Z 2025-07-17T07:36:42.6310018Z msg = Cannot scrape callname=ModelReport in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report.py line=24. 2025-07-17T07:36:42.6311076Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.6311486Z 2025-07-17T07:36:42.6311787Z The ModelReport class aims to provide users an easy way to diagnose issues that they run into 2025-07-17T07:36:42.6312515Z with their models. The class works with all traceable GraphModules to help diagnose issues, 2025-07-17T07:36:42.6313285Z though the requirements on the type of model more-so depends on the specific report the user 2025-07-17T07:36:42.6314058Z is trying to generate. With respect to the reports, the ModelReport class is initialized with 2025-07-17T07:36:42.6314732Z a set of Detector classes, each of which generate reports on quantization configuration 2025-07-17T07:36:42.6315227Z issues a use might have. 2025-07-17T07:36:42.6315394Z 2025-07-17T07:36:42.6315532Z Currently supports generating reports on: 2025-07-17T07:36:42.6315992Z - Suggestions for per-channel vs. per-tensor quantization (nn.Module) 2025-07-17T07:36:42.6316596Z - Suggestions for dynamic vs static quantization for linear layers (Graph Modules) 2025-07-17T07:36:42.6317281Z - Suggestions for input-weight equalization for linear and conv layers (Graph Modules) 2025-07-17T07:36:42.6317912Z - Suggestions for outlier detection for all layers (Graph Modules) 2025-07-17T07:36:42.6318232Z 2025-07-17T07:36:42.6318629Z The ModelReport class has the primary functionality of inserting observers (primarily the ModelReportObserver) 2025-07-17T07:36:42.6319732Z where needed for each detector to gather the information it needs, and then after calibration, the ModelReport 2025-07-17T07:36:42.6320602Z class compiles the report generated by each Detector class into a single report to return to the user. It also 2025-07-17T07:36:42.6321313Z has the capability to remove all the observers it inserted as well. 2025-07-17T07:36:42.6321636Z 2025-07-17T07:36:42.6321916Z * :attr:`_model` The model we wish to generate the report for. Must be a traceable GraphModule 2025-07-17T07:36:42.6322330Z 2025-07-17T07:36:42.6322796Z * :attr:`_desired_report_detectors` The set of Detectors representing desired reports from the ModelReport class 2025-07-17T07:36:42.6323612Z Make sure that these are all unique types of detectors [do not have more than 1 of the same class] 2025-07-17T07:36:42.6324040Z 2025-07-17T07:36:42.6324341Z * :attr:`_desired_detector_names` The set of detector names of the _desired_report_detectors. 2025-07-17T07:36:42.6324969Z This set is generated by calling the get_detector_name() of each detector 2025-07-17T07:36:42.6325401Z 2025-07-17T07:36:42.6325736Z * :attr:`_detector_name_to_observer_fqns` The mapping from each detector to fqns of observers of interest 2025-07-17T07:36:42.6326512Z The purpose of this is to keep track of what observers were inserted for each detector, so that they 2025-07-17T07:36:42.6327063Z can be removed at the end if desired 2025-07-17T07:36:42.6327281Z 2025-07-17T07:36:42.6327595Z * :attr:`_prepared_flag` A boolean flag that keeps track of whether we have prepared the model or not 2025-07-17T07:36:42.6328267Z This is to ensure we only insert observers once with the ModelReport instance 2025-07-17T07:36:42.6328629Z 2025-07-17T07:36:42.6328878Z * :attr:`_removed_observers` A boolean to track if we have removed observers already 2025-07-17T07:36:42.6329544Z The purpose is to ensure we don't attempt to remove observers twice with the same ModelReport 2025-07-17T07:36:42.6330270Z instance. This also allows the functionality where we can generate the report multiple times 2025-07-17T07:36:42.6330849Z as long as we haven't removed the observers yet. 2025-07-17T07:36:42.6331110Z 2025-07-17T07:36:42.6331189Z Note: 2025-07-17T07:36:42.6331601Z This class was initially designed to work with the Fx Graph Mode workflow in mind. However, 2025-07-17T07:36:42.6332318Z full functionality is available as long as there is a traceable GraphModule that is being used. 2025-07-17T07:36:42.6333046Z One method to get a traceable GraphModule without going through the Fx workflow is to use 2025-07-17T07:36:42.6333571Z the QuantizationTracer class. 2025-07-17T07:36:42.6333775Z 2025-07-17T07:36:42.6333877Z General Flow for Fx workflow: 2025-07-17T07:36:42.6334453Z 1.) Initialize ModelReport object with reports of interest by passing in initialized detector objects and model 2025-07-17T07:36:42.6335079Z 2.) Prepare your model with prepare_fx 2025-07-17T07:36:42.6335545Z 3.) Call model_report.prepare_detailed_calibration to add relevant observers 2025-07-17T07:36:42.6336001Z 4.) Calibrate your model with data 2025-07-17T07:36:42.6336562Z 5.) Call model_report.generate_report on your model to generate report and optionally remove added observers 2025-07-17T07:36:42.6337122Z Optional 2025-07-17T07:36:42.6337500Z 6.) Call model_report.generate_visualizer to get a ModelReportVisualizer instance 2025-07-17T07:36:42.6338136Z 7.) To help in parsing report information and debugging, view report info as a: 2025-07-17T07:36:42.6338591Z - Table 2025-07-17T07:36:42.6338823Z - Histogram 2025-07-17T07:36:42.6339048Z - Line plot 2025-07-17T07:36:42.6339517Z 8.) Call model_report.generate_qconfigs to generate the qconfigs based on the report suggestions 2025-07-17T07:36:42.6339949Z 2025-07-17T07:36:42.6340076Z Example (with QuantizationTracer): 2025-07-17T07:36:42.6340372Z >>> # xdoctest: +SKIP 2025-07-17T07:36:42.6340716Z >>> # get the necessary qconfig 2025-07-17T07:36:42.6341035Z >>> config = PrepareCustomConfig() 2025-07-17T07:36:42.6341394Z >>> skipped_module_names, skipped_module_classes = ( 2025-07-17T07:36:42.6341815Z ... get_skipped_module_name_and_classes(config, False) 2025-07-17T07:36:42.6342174Z ... ) 2025-07-17T07:36:42.6342291Z 2025-07-17T07:36:42.6342431Z >>> # initialize our model and get GraphModule 2025-07-17T07:36:42.6342758Z >>> model = SomeModel() 2025-07-17T07:36:42.6343187Z >>> tracer = QuantizationTracer(skipped_module_names, skipped_module_classes) 2025-07-17T07:36:42.6343732Z >>> graph_module = GraphModule(model, tracer.trace(model)) 2025-07-17T07:36:42.6344010Z 2025-07-17T07:36:42.6344219Z >>> # get our set of detectors and ModelReport instance 2025-07-17T07:36:42.6344590Z >>> detector_set = set( 2025-07-17T07:36:42.6344854Z ... [ 2025-07-17T07:36:42.6345108Z ... DynamicStaticDetector(tolerance=0.5), 2025-07-17T07:36:42.6345558Z ... InputWeightEqualizationDetector(ratio_threshold=0.7), 2025-07-17T07:36:42.6345954Z ... ] 2025-07-17T07:36:42.6346169Z ... ) 2025-07-17T07:36:42.6346493Z >>> tracer_reporter = ModelReport(graph_module, tracer_detector_set) 2025-07-17T07:36:42.6346832Z 2025-07-17T07:36:42.6346986Z >>> # now we insert the observers and calibrate the model 2025-07-17T07:36:42.6347515Z >>> tracer_model_with_observers = tracer_reporter.prepare_detailed_calibration() 2025-07-17T07:36:42.6348078Z >>> for i in range(num_callibration_batches): 2025-07-17T07:36:42.6348459Z >>> example_input = get_callibration_input() 2025-07-17T07:36:42.6348850Z >>> tracer_model_with_observers(example_input) 2025-07-17T07:36:42.6349094Z 2025-07-17T07:36:42.6349363Z >>> # finally we generate the reports and optionally remove the observers we inserted 2025-07-17T07:36:42.6349886Z >>> reports = tracer_reporter.generate_model_report( 2025-07-17T07:36:42.6350273Z ... remove_inserted_observers=True 2025-07-17T07:36:42.6350583Z ... ) 2025-07-17T07:36:42.6350699Z 2025-07-17T07:36:42.6350915Z >>> # Optional: we can generate the qconfig mapping based on the suggestions 2025-07-17T07:36:42.6351416Z >>> qconfigs = model_report.generate_qconfig_mapping() 2025-07-17T07:36:42.6351698Z 2025-07-17T07:36:42.6351938Z >>> # Optional: we can generate the equalization mapping based on the suggestions 2025-07-17T07:36:42.6352481Z >>> qconfigs = model_report.generate_equalization_mapping() 2025-07-17T07:36:42.6352766Z 2025-07-17T07:36:42.6353041Z >>> # Optional: we get a ModelReportVisualizer instance to do any visualizations desired 2025-07-17T07:36:42.6353654Z >>> model_report_visualizer = tracer_reporter.generate_visualizer() 2025-07-17T07:36:42.6353974Z 2025-07-17T07:36:42.6353989Z 2025-07-17T07:36:42.6354239Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.6354604Z 2025-07-17T07:36:42.6380039Z msg = Cannot scrape callname=ModelReportVisualizer.generate_filtered_tables in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=301. 2025-07-17T07:36:42.6381322Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.6381769Z 2025-07-17T07:36:42.6382079Z Takes in optional filter values and generates two tables with desired information. 2025-07-17T07:36:42.6382607Z 2025-07-17T07:36:42.6382813Z The generated tables are presented in both a list-of-lists format 2025-07-17T07:36:42.6383129Z 2025-07-17T07:36:42.6383342Z The reason for the two tables are that they handle different things: 2025-07-17T07:36:42.6383828Z 1.) the first table handles all tensor level information 2025-07-17T07:36:42.6384305Z 2.) the second table handles and displays all channel based information 2025-07-17T07:36:42.6384647Z 2025-07-17T07:36:42.6384957Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-07-17T07:36:42.6385868Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-07-17T07:36:42.6386753Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-07-17T07:36:42.6387277Z 2025-07-17T07:36:42.6387430Z Tensor table columns: 2025-07-17T07:36:42.6387829Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-07-17T07:36:42.6388289Z ---- --------- --------- --------- --------- --------- 2025-07-17T07:36:42.6388587Z 2025-07-17T07:36:42.6388702Z Per-Channel table columns: 2025-07-17T07:36:42.6389194Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-07-17T07:36:42.6389783Z ---- --------- ------- --------- --------- --------- --------- 2025-07-17T07:36:42.6390137Z 2025-07-17T07:36:42.6390217Z Args: 2025-07-17T07:36:42.6390727Z feature_filter (str, optional): Filters the features presented to only those that 2025-07-17T07:36:42.6391332Z contain this filter substring 2025-07-17T07:36:42.6391705Z Default = "", results in all the features being printed 2025-07-17T07:36:42.6392239Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-07-17T07:36:42.6392854Z Default = "", results in all the modules in the reports to be visible in the table 2025-07-17T07:36:42.6393227Z 2025-07-17T07:36:42.6393337Z Returns a dictionary with two keys: 2025-07-17T07:36:42.6393718Z (Dict[str, Tuple[List, List]]) A dict containing two keys: 2025-07-17T07:36:42.6394130Z "tensor_level_info", "channel_level_info" 2025-07-17T07:36:42.6394463Z Each key maps to a tuple with: 2025-07-17T07:36:42.6394798Z A list of the headers of each table 2025-07-17T07:36:42.6395205Z A list of lists containing the table information row by row 2025-07-17T07:36:42.6395658Z The 0th index row will contain the headers of the columns 2025-07-17T07:36:42.6396068Z The rest of the rows will contain data 2025-07-17T07:36:42.6396297Z 2025-07-17T07:36:42.6396393Z Example Use: 2025-07-17T07:36:42.6396636Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:42.6397019Z >>> mod_report_visualizer.generate_filtered_tables( 2025-07-17T07:36:42.6397466Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-07-17T07:36:42.6398043Z ... ) # generates table with per_channel_min info for all modules in block 1 of the model 2025-07-17T07:36:42.6398428Z 2025-07-17T07:36:42.6398674Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.6399047Z 2025-07-17T07:36:42.6399970Z msg = Cannot scrape callname=ModelReportVisualizer.generate_table_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=399. 2025-07-17T07:36:42.6401252Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.6401631Z 2025-07-17T07:36:42.6401911Z Takes in optional filter values and prints out formatted tables of the information. 2025-07-17T07:36:42.6402300Z 2025-07-17T07:36:42.6402649Z The reason for the two tables printed out instead of one large one are that they handle different things: 2025-07-17T07:36:42.6403259Z 1.) the first table handles all tensor level information 2025-07-17T07:36:42.6403742Z 2.) the second table handles and displays all channel based information 2025-07-17T07:36:42.6404069Z 2025-07-17T07:36:42.6404389Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-07-17T07:36:42.6405143Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-07-17T07:36:42.6406015Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-07-17T07:36:42.6406496Z 2025-07-17T07:36:42.6406676Z Tensor table columns: 2025-07-17T07:36:42.6407026Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-07-17T07:36:42.6407466Z ---- --------- --------- --------- --------- --------- 2025-07-17T07:36:42.6407736Z 2025-07-17T07:36:42.6407839Z Per-Channel table columns: 2025-07-17T07:36:42.6408014Z 2025-07-17T07:36:42.6408241Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-07-17T07:36:42.6408788Z ---- --------- ------- --------- --------- --------- --------- 2025-07-17T07:36:42.6409062Z 2025-07-17T07:36:42.6409143Z Args: 2025-07-17T07:36:42.6409597Z feature_filter (str, optional): Filters the features presented to only those that 2025-07-17T07:36:42.6410092Z contain this filter substring 2025-07-17T07:36:42.6410456Z Default = "", results in all the features being printed 2025-07-17T07:36:42.6410995Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-07-17T07:36:42.6411634Z Default = "", results in all the modules in the reports to be visible in the table 2025-07-17T07:36:42.6411993Z 2025-07-17T07:36:42.6412093Z Example Use: 2025-07-17T07:36:42.6412339Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:42.6412742Z >>> mod_report_visualizer.generate_table_visualization( 2025-07-17T07:36:42.6413213Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-07-17T07:36:42.6413603Z ... ) 2025-07-17T07:36:42.6413914Z >>> # prints out neatly formatted table with per_channel_min info 2025-07-17T07:36:42.6414342Z >>> # for all modules in block 1 of the model 2025-07-17T07:36:42.6414572Z 2025-07-17T07:36:42.6414835Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.6415198Z 2025-07-17T07:36:42.6416105Z msg = Cannot scrape callname=ModelReportVisualizer.generate_plot_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=564. 2025-07-17T07:36:42.6417398Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.6417784Z 2025-07-17T07:36:42.6418015Z Takes in a feature and optional module_filter and plots of the desired data. 2025-07-17T07:36:42.6418366Z 2025-07-17T07:36:42.6418647Z For per channel features, it averages the value across the channels and plots a point 2025-07-17T07:36:42.6419295Z per module. The reason for this is that for models with hundreds of channels, it can 2025-07-17T07:36:42.6419958Z be hard to differentiate one channel line from another, and so the point of generating 2025-07-17T07:36:42.6420629Z a single average point per module is to give a sense of general trends that encourage 2025-07-17T07:36:42.6421115Z further deep dives. 2025-07-17T07:36:42.6421274Z 2025-07-17T07:36:42.6421356Z Note: 2025-07-17T07:36:42.6421740Z Only features in the report that have tensor value data are plottable by this class 2025-07-17T07:36:42.6422303Z When the tensor information is plotted, it will plot: 2025-07-17T07:36:42.6422704Z idx as the x val, feature value as the y_val 2025-07-17T07:36:42.6423120Z When the channel information is plotted, it will plot: 2025-07-17T07:36:42.6423667Z the first idx of each module as the x val, feature value as the y_val [for each channel] 2025-07-17T07:36:42.6424272Z The reason for this is that we want to be able to compare values across the 2025-07-17T07:36:42.6424859Z channels for same layer, and it will be hard if values are staggered by idx 2025-07-17T07:36:42.6425389Z This means each module is represented by only 1 x value 2025-07-17T07:36:42.6425762Z Args: 2025-07-17T07:36:42.6426090Z feature_filter (str): Filters the features presented to only those that 2025-07-17T07:36:42.6426549Z contain this filter substring 2025-07-17T07:36:42.6427028Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-07-17T07:36:42.6427702Z Default = "", results in all the modules in the reports to be visible in the table 2025-07-17T07:36:42.6428079Z 2025-07-17T07:36:42.6428163Z Example Use: 2025-07-17T07:36:42.6428419Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:42.6428817Z >>> mod_report_visualizer.generate_plot_visualization( 2025-07-17T07:36:42.6429270Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-07-17T07:36:42.6429661Z ... ) 2025-07-17T07:36:42.6429959Z >>> # outputs line plot of per_channel_min information for all 2025-07-17T07:36:42.6430418Z >>> # modules in block1 of model each channel gets it's own line, 2025-07-17T07:36:42.6430947Z >>> # and it's plotted across the in-order modules on the x-axis 2025-07-17T07:36:42.6431231Z 2025-07-17T07:36:42.6431492Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.6431855Z 2025-07-17T07:36:42.6432826Z msg = Cannot scrape callname=ModelReportVisualizer.generate_histogram_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=643. 2025-07-17T07:36:42.6434129Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.6434500Z 2025-07-17T07:36:42.6434773Z Takes in a feature and optional module_filter and plots the histogram of desired data. 2025-07-17T07:36:42.6435180Z 2025-07-17T07:36:42.6435259Z Note: 2025-07-17T07:36:42.6435642Z Only features in the report that have tensor value data can be viewed as a histogram 2025-07-17T07:36:42.6436277Z If you want to plot a histogram from all the channel values of a specific feature for 2025-07-17T07:36:42.6436908Z a specific model, make sure to specify both the model and the feature properly 2025-07-17T07:36:42.6437519Z in the filters and you should be able to see a distribution of the channel data 2025-07-17T07:36:42.6437880Z 2025-07-17T07:36:42.6437975Z Args: 2025-07-17T07:36:42.6438338Z feature_filter (str, optional): Filters the features presented to only those that 2025-07-17T07:36:42.6438830Z contain this filter substring 2025-07-17T07:36:42.6439201Z Default = "", results in all the features being printed 2025-07-17T07:36:42.6439719Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-07-17T07:36:42.6440341Z Default = "", results in all the modules in the reports to be visible in the table 2025-07-17T07:36:42.6440936Z num_bins (int, optional): The number of bins to create the histogram with 2025-07-17T07:36:42.6441484Z Default = 10, the values will be split into 10 equal sized bins 2025-07-17T07:36:42.6441780Z 2025-07-17T07:36:42.6441866Z Example Use: 2025-07-17T07:36:42.6442096Z >>> # xdoctest: +SKIP 2025-07-17T07:36:42.6442568Z >>> mod_report_visualizer.generategenerate_histogram_visualization_plot_visualization( 2025-07-17T07:36:42.6443171Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-07-17T07:36:42.6443571Z ... ) 2025-07-17T07:36:42.6443965Z # outputs histogram of per_channel_min information for all modules in block1 of model 2025-07-17T07:36:42.6444618Z information is gathered across all channels for all modules in block 1 for the 2025-07-17T07:36:42.6445204Z per_channel_min and is displayed in a histogram of equally sized bins 2025-07-17T07:36:42.6445636Z 2025-07-17T07:36:42.6445886Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.6446265Z 2025-07-17T07:36:42.7612064Z msg = Cannot scrape callname=record_function in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py line=734. 2025-07-17T07:36:42.7613037Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.7613795Z Context manager/function decorator that adds a label to a code block/function when running autograd profiler. 2025-07-17T07:36:42.7614698Z Label will only appear if CPU activity tracing is enabled. 2025-07-17T07:36:42.7614993Z 2025-07-17T07:36:42.7615142Z It is useful when tracing the code profile. 2025-07-17T07:36:42.7615380Z 2025-07-17T07:36:42.7615478Z Args: 2025-07-17T07:36:42.7615733Z name (str): Label assigned to the block of code. 2025-07-17T07:36:42.7616174Z node_id (int): ID of node, for distributed profiling. Unset in 2025-07-17T07:36:42.7616577Z non-distributed cases. 2025-07-17T07:36:42.7616760Z 2025-07-17T07:36:42.7616843Z Example: 2025-07-17T07:36:42.7617158Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_AUTOGRAD_PROFILER) 2025-07-17T07:36:42.7617674Z >>> x = torch.randn((1, 1), requires_grad=True) 2025-07-17T07:36:42.7618068Z >>> with torch.autograd.profiler.profile() as prof: 2025-07-17T07:36:42.7618439Z ... y = x**2 2025-07-17T07:36:42.7618758Z ... with torch.autograd.profiler.record_function( 2025-07-17T07:36:42.7619134Z ... "label-z" 2025-07-17T07:36:42.7619400Z ... ): # label the block 2025-07-17T07:36:42.7619693Z ... z = y**3 2025-07-17T07:36:42.7619963Z ... y.backward() 2025-07-17T07:36:42.7620226Z >>> # xdoctest: +IGNORE_WANT 2025-07-17T07:36:42.7620557Z >>> # NOTE: some columns were removed for brevity 2025-07-17T07:36:42.7621004Z >>> print(prof.key_averages().table(sort_by="self_cpu_time_total")) 2025-07-17T07:36:42.7621508Z ----------------------------------- --------------- --------------- --------------- 2025-07-17T07:36:42.7622002Z Name Self CPU total % CPU time avg Number of Calls 2025-07-17T07:36:42.7622486Z ----------------------------------- --------------- --------------- --------------- 2025-07-17T07:36:42.7622926Z pow 60.77% 47.470us 3 2025-07-17T07:36:42.7623293Z mul 21.73% 25.465us 2 2025-07-17T07:36:42.7623715Z PowBackward0 12.03% 121.891us 1 2025-07-17T07:36:42.7624235Z torch::autograd::AccumulateGrad 2.70% 6.324us 1 2025-07-17T07:36:42.7624712Z label-z 2.13% 12.421us 1 2025-07-17T07:36:42.7625165Z torch::autograd::GraphRoot 0.64% 1.503us 1 2025-07-17T07:36:42.7625675Z ----------------------------------- --------------- --------------- --------------- 2025-07-17T07:36:42.7626095Z Self CPU time total: 234.344us 2025-07-17T07:36:42.7626403Z CUDA time total: 0.000us 2025-07-17T07:36:42.7626605Z 2025-07-17T07:36:42.7626685Z 2025-07-17T07:36:42.7627049Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.7627415Z 2025-07-17T07:36:42.9149654Z msg = Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py line=685. 2025-07-17T07:36:42.9151597Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:42.9152306Z 2025-07-17T07:36:42.9152824Z Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh. 2025-07-17T07:36:42.9154066Z The submesh created consists of the dimensions and the communicators indicated by 2025-07-17T07:36:42.9154973Z ``mesh_dim_names`` 2025-07-17T07:36:42.9155231Z 2025-07-17T07:36:42.9155390Z Args: 2025-07-17T07:36:42.9155975Z mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the 2025-07-17T07:36:42.9156955Z mesh dimension of the DeviceMesh to create the submesh for. 2025-07-17T07:36:42.9157671Z Returns: 2025-07-17T07:36:42.9158068Z A :class:`DeviceMesh` object 2025-07-17T07:36:42.9158430Z 2025-07-17T07:36:42.9158954Z The following program runs on each process/rank in an SPMD manner in a world size of 8. 2025-07-17T07:36:42.9160233Z In the first example: 2025-07-17T07:36:42.9160960Z Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]). 2025-07-17T07:36:42.9162057Z Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of DeviceMesh:([4, 5, 6, 7]). 2025-07-17T07:36:42.9163171Z Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of DeviceMesh:([0, 4]). 2025-07-17T07:36:42.9164249Z Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of DeviceMesh:([1, 5]). 2025-07-17T07:36:42.9165422Z Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of DeviceMesh:([2, 6]). 2025-07-17T07:36:42.9166690Z Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of DeviceMesh:([3, 7]). 2025-07-17T07:36:42.9167328Z 2025-07-17T07:36:42.9167503Z In the second example: 2025-07-17T07:36:42.9168238Z Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]). 2025-07-17T07:36:42.9169436Z Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]). 2025-07-17T07:36:42.9170861Z Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]). 2025-07-17T07:36:42.9172009Z Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]). 2025-07-17T07:36:42.9172712Z 2025-07-17T07:36:42.9172894Z Example:: 2025-07-17T07:36:42.9173112Z 2025-07-17T07:36:42.9173289Z >>> # xdoctest: +SKIP("no rank") 2025-07-17T07:36:42.9173917Z >>> from torch.distributed.device_mesh import DeviceMesh 2025-07-17T07:36:42.9174438Z >>> 2025-07-17T07:36:42.9174785Z >>> # Initialize a 2D device mesh as (2, 4) to represent the topology 2025-07-17T07:36:42.9175239Z >>> # of cross-host(dim 0), and within-host (dim 1). 2025-07-17T07:36:42.9175745Z >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-07-17T07:36:42.9176227Z >>> tp_mesh = mesh_2d["tp"] 2025-07-17T07:36:42.9176518Z >>> dp_mesh = mesh_2d["dp"] 2025-07-17T07:36:42.9176788Z >>> 2025-07-17T07:36:42.9177006Z >>> # Initialize a 3D mesh. 2025-07-17T07:36:42.9177457Z >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp")) 2025-07-17T07:36:42.9178157Z >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh. 2025-07-17T07:36:42.9178689Z >>> dp_cp_mesh = mesh_3d["dp", "cp"] 2025-07-17T07:36:42.9179025Z >>> cp_dp_mesh = mesh_3d["cp", "dp"] 2025-07-17T07:36:42.9179237Z 2025-07-17T07:36:42.9179917Z Original Error: SyntaxError('positional argument follows keyword argument', ('', 6, 82, 'mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))\n', 6, 83)) 2025-07-17T07:36:42.9180737Z 2025-07-17T07:36:42.9180981Z mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-07-17T07:36:42.9181471Z ^ 2025-07-17T07:36:42.9515530Z msg = Cannot scrape callname=batch_isend_irecv in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2706. 2025-07-17T07:36:42.9517468Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.9518124Z 2025-07-17T07:36:42.9518567Z Send or Receive a batch of tensors asynchronously and return a list of requests. 2025-07-17T07:36:42.9519250Z 2025-07-17T07:36:42.9519706Z Process each of the operations in ``p2p_op_list`` and return the corresponding 2025-07-17T07:36:42.9520771Z requests. NCCL, Gloo, and UCC backend are currently supported. 2025-07-17T07:36:42.9521334Z 2025-07-17T07:36:42.9521486Z Args: 2025-07-17T07:36:42.9522107Z p2p_op_list: A list of point-to-point operations(type of each operator is 2025-07-17T07:36:42.9523177Z ``torch.distributed.P2POp``). The order of the isend/irecv in the list 2025-07-17T07:36:42.9524555Z matters and it needs to match with corresponding isend/irecv on the 2025-07-17T07:36:42.9525237Z remote end. 2025-07-17T07:36:42.9525551Z 2025-07-17T07:36:42.9525676Z Returns: 2025-07-17T07:36:42.9526331Z A list of distributed request objects returned by calling the corresponding 2025-07-17T07:36:42.9527164Z op in the op_list. 2025-07-17T07:36:42.9527469Z 2025-07-17T07:36:42.9527613Z Examples: 2025-07-17T07:36:42.9528013Z >>> # xdoctest: +SKIP("no rank") 2025-07-17T07:36:42.9528729Z >>> send_tensor = torch.arange(2, dtype=torch.float32) + 2 * rank 2025-07-17T07:36:42.9529561Z >>> recv_tensor = torch.randn(2, dtype=torch.float32) 2025-07-17T07:36:42.9530680Z >>> send_op = dist.P2POp(dist.isend, send_tensor, (rank + 1) % world_size) 2025-07-17T07:36:42.9531511Z >>> recv_op = dist.P2POp( 2025-07-17T07:36:42.9532207Z ... dist.irecv, recv_tensor, (rank - 1 + world_size) % world_size 2025-07-17T07:36:42.9532941Z ... ) 2025-07-17T07:36:42.9533407Z >>> reqs = batch_isend_irecv([send_op, recv_op]) 2025-07-17T07:36:42.9534045Z >>> for req in reqs: 2025-07-17T07:36:42.9534501Z >>> req.wait() 2025-07-17T07:36:42.9534930Z >>> recv_tensor 2025-07-17T07:36:42.9535353Z tensor([2, 3]) # Rank 0 2025-07-17T07:36:42.9535860Z tensor([0, 1]) # Rank 1 2025-07-17T07:36:42.9536201Z 2025-07-17T07:36:42.9536645Z .. note:: Note that when this API is used with the NCCL PG backend, users must set 2025-07-17T07:36:42.9537699Z the current GPU device with `torch.cuda.set_device`, otherwise it will 2025-07-17T07:36:42.9538521Z lead to unexpected hang issues. 2025-07-17T07:36:42.9538955Z 2025-07-17T07:36:42.9539347Z In addition, if this API is the first collective call in the ``group`` 2025-07-17T07:36:42.9540339Z passed to ``dist.P2POp``, all ranks of the ``group`` must participate in 2025-07-17T07:36:42.9541346Z this API call; otherwise, the behavior is undefined. If this API call is 2025-07-17T07:36:42.9542389Z not the first collective call in the ``group``, batched P2P operations 2025-07-17T07:36:42.9543363Z involving only a subset of ranks of the ``group`` are allowed. 2025-07-17T07:36:42.9543946Z 2025-07-17T07:36:42.9544415Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.9545131Z 2025-07-17T07:36:42.9546257Z msg = Cannot scrape callname=all_reduce in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2838. 2025-07-17T07:36:42.9548076Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.9548772Z 2025-07-17T07:36:42.9549263Z Reduces the tensor data across all machines in a way that all get the final result. 2025-07-17T07:36:42.9550003Z 2025-07-17T07:36:42.9550424Z After the call ``tensor`` is going to be bitwise identical in all processes. 2025-07-17T07:36:42.9551035Z 2025-07-17T07:36:42.9551295Z Complex tensors are supported. 2025-07-17T07:36:42.9551652Z 2025-07-17T07:36:42.9551804Z Args: 2025-07-17T07:36:42.9552404Z tensor (Tensor): Input and output of the collective. The function 2025-07-17T07:36:42.9553185Z operates in-place. 2025-07-17T07:36:42.9553718Z op (optional): One of the values from 2025-07-17T07:36:42.9554312Z ``torch.distributed.ReduceOp`` 2025-07-17T07:36:42.9554983Z enum. Specifies an operation used for element-wise reductions. 2025-07-17T07:36:42.9555984Z group (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:42.9556893Z the default process group will be used. 2025-07-17T07:36:42.9557670Z async_op (bool, optional): Whether this op should be an async op 2025-07-17T07:36:42.9558276Z 2025-07-17T07:36:42.9558435Z Returns: 2025-07-17T07:36:42.9558908Z Async work handle, if async_op is set to True. 2025-07-17T07:36:42.9559602Z None, if not async_op or if not part of the group 2025-07-17T07:36:42.9560085Z 2025-07-17T07:36:42.9560224Z Examples: 2025-07-17T07:36:42.9560796Z >>> # xdoctest: +SKIP("no rank") 2025-07-17T07:36:42.9561416Z >>> # All tensors below are of torch.int64 type. 2025-07-17T07:36:42.9562066Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:42.9562698Z >>> device = torch.device(f"cuda:{rank}") 2025-07-17T07:36:42.9563534Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-07-17T07:36:42.9564327Z >>> tensor 2025-07-17T07:36:42.9564767Z tensor([1, 2], device='cuda:0') # Rank 0 2025-07-17T07:36:42.9565424Z tensor([3, 4], device='cuda:1') # Rank 1 2025-07-17T07:36:42.9566032Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-07-17T07:36:42.9566613Z >>> tensor 2025-07-17T07:36:42.9567159Z tensor([4, 6], device='cuda:0') # Rank 0 2025-07-17T07:36:42.9567775Z tensor([4, 6], device='cuda:1') # Rank 1 2025-07-17T07:36:42.9568181Z 2025-07-17T07:36:42.9568412Z >>> # All tensors below are of torch.cfloat type. 2025-07-17T07:36:42.9569040Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:42.9569643Z >>> tensor = torch.tensor( 2025-07-17T07:36:42.9570447Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-07-17T07:36:42.9571060Z ... ) + 2 * rank * (1 + 1j) 2025-07-17T07:36:42.9571547Z >>> tensor 2025-07-17T07:36:42.9572016Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-07-17T07:36:42.9572723Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-07-17T07:36:42.9573405Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-07-17T07:36:42.9574002Z >>> tensor 2025-07-17T07:36:42.9574471Z tensor([4.+4.j, 6.+6.j], device='cuda:0') # Rank 0 2025-07-17T07:36:42.9575146Z tensor([4.+4.j, 6.+6.j], device='cuda:1') # Rank 1 2025-07-17T07:36:42.9575610Z 2025-07-17T07:36:42.9575617Z 2025-07-17T07:36:42.9576082Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.9576773Z 2025-07-17T07:36:42.9577960Z msg = Cannot scrape callname=gather_object in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3198. 2025-07-17T07:36:42.9579820Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.9580528Z 2025-07-17T07:36:42.9580919Z Gathers picklable objects from the whole group in a single process. 2025-07-17T07:36:42.9581559Z 2025-07-17T07:36:42.9581985Z Similar to :func:`gather`, but Python objects can be passed in. Note that the 2025-07-17T07:36:42.9582897Z object must be picklable in order to be gathered. 2025-07-17T07:36:42.9583379Z 2025-07-17T07:36:42.9583522Z Args: 2025-07-17T07:36:42.9583931Z obj (Any): Input object. Must be picklable. 2025-07-17T07:36:42.9584745Z object_gather_list (list[Any]): Output list. On the ``dst`` rank, it 2025-07-17T07:36:42.9585710Z should be correctly sized as the size of the group for this 2025-07-17T07:36:42.9586647Z collective and will contain the output. Must be ``None`` on non-dst 2025-07-17T07:36:42.9587477Z ranks. (default is ``None``) 2025-07-17T07:36:42.9588460Z dst (int, optional): Destination rank on global process group (regardless of ``group`` argument). 2025-07-17T07:36:42.9589644Z (If both ``dst`` and ``group_dst`` are None, default is global rank 0) 2025-07-17T07:36:42.9590632Z group: (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:42.9591623Z the default process group will be used. Default is ``None``. 2025-07-17T07:36:42.9592847Z group_dst (int, optional): Destination rank on ``group``. Invalid to specify both ``dst`` and ``group_dst`` 2025-07-17T07:36:42.9593728Z 2025-07-17T07:36:42.9593875Z Returns: 2025-07-17T07:36:42.9594439Z None. On the ``dst`` rank, ``object_gather_list`` will contain the 2025-07-17T07:36:42.9595191Z output of the collective. 2025-07-17T07:36:42.9595512Z 2025-07-17T07:36:42.9595898Z .. note:: Note that this API differs slightly from the gather collective 2025-07-17T07:36:42.9596894Z since it does not provide an async_op handle and thus will be a blocking 2025-07-17T07:36:42.9597989Z call. 2025-07-17T07:36:42.9598190Z 2025-07-17T07:36:42.9598599Z .. note:: For NCCL-based processed groups, internal tensor representations 2025-07-17T07:36:42.9599638Z of objects must be moved to the GPU device before communication takes 2025-07-17T07:36:42.9600513Z place. In this case, the device used is given by 2025-07-17T07:36:42.9601414Z ``torch.cuda.current_device()`` and it is the user's responsibility to 2025-07-17T07:36:42.9602431Z ensure that this is set so that each rank has an individual GPU, via 2025-07-17T07:36:42.9603242Z ``torch.cuda.set_device()``. 2025-07-17T07:36:42.9603618Z 2025-07-17T07:36:42.9603928Z .. warning:: 2025-07-17T07:36:42.9604603Z Object collectives have a number of serious performance and scalability 2025-07-17T07:36:42.9605642Z limitations. See :ref:`object_collectives` for details. 2025-07-17T07:36:42.9606182Z 2025-07-17T07:36:42.9606338Z .. warning:: 2025-07-17T07:36:42.9606945Z :func:`gather_object` uses ``pickle`` module implicitly, which is 2025-07-17T07:36:42.9607921Z known to be insecure. It is possible to construct malicious pickle data 2025-07-17T07:36:42.9608952Z which will execute arbitrary code during unpickling. Only call this 2025-07-17T07:36:42.9609766Z function with data you trust. 2025-07-17T07:36:42.9610103Z 2025-07-17T07:36:42.9610266Z .. warning:: 2025-07-17T07:36:42.9610858Z Calling :func:`gather_object` with GPU tensors is not well supported 2025-07-17T07:36:42.9611891Z and inefficient as it incurs GPU -> CPU transfer since tensors would be 2025-07-17T07:36:42.9612823Z pickled. Please consider using :func:`gather` instead. 2025-07-17T07:36:42.9613350Z 2025-07-17T07:36:42.9613511Z Example:: 2025-07-17T07:36:42.9613962Z >>> # xdoctest: +SKIP("need process group init") 2025-07-17T07:36:42.9614723Z >>> # Note: Process group initialization omitted on each rank. 2025-07-17T07:36:42.9615497Z >>> import torch.distributed as dist 2025-07-17T07:36:42.9616098Z >>> # Assumes world_size of 3. 2025-07-17T07:36:42.9616773Z >>> gather_objects = ["foo", 12, {1: 2}] # any picklable object 2025-07-17T07:36:42.9617530Z >>> output = [None for _ in gather_objects] 2025-07-17T07:36:42.9618139Z >>> dist.gather_object( 2025-07-17T07:36:42.9618687Z ... gather_objects[dist.get_rank()], 2025-07-17T07:36:42.9619309Z ... output if dist.get_rank() == 0 else None, 2025-07-17T07:36:42.9619873Z ... dst=0 2025-07-17T07:36:42.9620279Z ... ) 2025-07-17T07:36:42.9620618Z >>> # On rank 0 2025-07-17T07:36:42.9620999Z >>> output 2025-07-17T07:36:42.9621379Z ['foo', 12, {1: 2}] 2025-07-17T07:36:42.9621630Z 2025-07-17T07:36:42.9622134Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.9635819Z 2025-07-17T07:36:42.9636853Z msg = Cannot scrape callname=all_gather in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3794. 2025-07-17T07:36:42.9637845Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.9638225Z 2025-07-17T07:36:42.9638382Z Gathers tensors from the whole group in a list. 2025-07-17T07:36:42.9638635Z 2025-07-17T07:36:42.9638775Z Complex and uneven sized tensors are supported. 2025-07-17T07:36:42.9639037Z 2025-07-17T07:36:42.9639119Z Args: 2025-07-17T07:36:42.9639415Z tensor_list (list[Tensor]): Output list. It should contain 2025-07-17T07:36:42.9639916Z correctly-sized tensors to be used for output of the collective. 2025-07-17T07:36:42.9640368Z Uneven sized tensors are supported. 2025-07-17T07:36:42.9640792Z tensor (Tensor): Tensor to be broadcast from current process. 2025-07-17T07:36:42.9641336Z group (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:42.9641802Z the default process group will be used. 2025-07-17T07:36:42.9642230Z async_op (bool, optional): Whether this op should be an async op 2025-07-17T07:36:42.9642666Z 2025-07-17T07:36:42.9642763Z Returns: 2025-07-17T07:36:42.9643006Z Async work handle, if async_op is set to True. 2025-07-17T07:36:42.9643405Z None, if not async_op or if not part of the group 2025-07-17T07:36:42.9643658Z 2025-07-17T07:36:42.9643758Z Examples: 2025-07-17T07:36:42.9644006Z >>> # xdoctest: +SKIP("need process group init") 2025-07-17T07:36:42.9644389Z >>> # All tensors below are of torch.int64 dtype. 2025-07-17T07:36:42.9644754Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:42.9645098Z >>> device = torch.device(f"cuda:{rank}") 2025-07-17T07:36:42.9645474Z >>> tensor_list = [ 2025-07-17T07:36:42.9645915Z ... torch.zeros(2, dtype=torch.int64, device=device) for _ in range(2) 2025-07-17T07:36:42.9646330Z ... ] 2025-07-17T07:36:42.9646525Z >>> tensor_list 2025-07-17T07:36:42.9646867Z [tensor([0, 0], device='cuda:0'), tensor([0, 0], device='cuda:0')] # Rank 0 2025-07-17T07:36:42.9647381Z [tensor([0, 0], device='cuda:1'), tensor([0, 0], device='cuda:1')] # Rank 1 2025-07-17T07:36:42.9647915Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-07-17T07:36:42.9648346Z >>> tensor 2025-07-17T07:36:42.9648593Z tensor([1, 2], device='cuda:0') # Rank 0 2025-07-17T07:36:42.9648927Z tensor([3, 4], device='cuda:1') # Rank 1 2025-07-17T07:36:42.9649268Z >>> dist.all_gather(tensor_list, tensor) 2025-07-17T07:36:42.9649580Z >>> tensor_list 2025-07-17T07:36:42.9649918Z [tensor([1, 2], device='cuda:0'), tensor([3, 4], device='cuda:0')] # Rank 0 2025-07-17T07:36:42.9650472Z [tensor([1, 2], device='cuda:1'), tensor([3, 4], device='cuda:1')] # Rank 1 2025-07-17T07:36:42.9650801Z 2025-07-17T07:36:42.9650940Z >>> # All tensors below are of torch.cfloat dtype. 2025-07-17T07:36:42.9651314Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:42.9651618Z >>> tensor_list = [ 2025-07-17T07:36:42.9651991Z ... torch.zeros(2, dtype=torch.cfloat, device=device) for _ in range(2) 2025-07-17T07:36:42.9652422Z ... ] 2025-07-17T07:36:42.9652630Z >>> tensor_list 2025-07-17T07:36:42.9653010Z [tensor([0.+0.j, 0.+0.j], device='cuda:0'), tensor([0.+0.j, 0.+0.j], device='cuda:0')] # Rank 0 2025-07-17T07:36:42.9653631Z [tensor([0.+0.j, 0.+0.j], device='cuda:1'), tensor([0.+0.j, 0.+0.j], device='cuda:1')] # Rank 1 2025-07-17T07:36:42.9654098Z >>> tensor = torch.tensor( 2025-07-17T07:36:42.9654423Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-07-17T07:36:42.9654814Z ... ) + 2 * rank * (1 + 1j) 2025-07-17T07:36:42.9655085Z >>> tensor 2025-07-17T07:36:42.9655359Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-07-17T07:36:42.9655732Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-07-17T07:36:42.9656101Z >>> dist.all_gather(tensor_list, tensor) 2025-07-17T07:36:42.9656438Z >>> tensor_list 2025-07-17T07:36:42.9656882Z [tensor([1.+1.j, 2.+2.j], device='cuda:0'), tensor([3.+3.j, 4.+4.j], device='cuda:0')] # Rank 0 2025-07-17T07:36:42.9657492Z [tensor([1.+1.j, 2.+2.j], device='cuda:1'), tensor([3.+3.j, 4.+4.j], device='cuda:1')] # Rank 1 2025-07-17T07:36:42.9657850Z 2025-07-17T07:36:42.9657865Z 2025-07-17T07:36:42.9658116Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.9658486Z 2025-07-17T07:36:42.9689606Z msg = Cannot scrape callname=all_to_all_single in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4500. 2025-07-17T07:36:42.9690636Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.9691015Z 2025-07-17T07:36:42.9691278Z Split input tensor and then scatter the split list to all processes in a group. 2025-07-17T07:36:42.9691660Z 2025-07-17T07:36:42.9691916Z Later the received tensors are concatenated from all the processes in the group 2025-07-17T07:36:42.9692416Z and returned as a single output tensor. 2025-07-17T07:36:42.9692805Z 2025-07-17T07:36:42.9692917Z Complex tensors are supported. 2025-07-17T07:36:42.9693118Z 2025-07-17T07:36:42.9693197Z Args: 2025-07-17T07:36:42.9693479Z output (Tensor): Gathered concatenated output tensor. 2025-07-17T07:36:42.9693889Z input (Tensor): Input tensor to scatter. 2025-07-17T07:36:42.9694331Z output_split_sizes: (list[Int], optional): Output split sizes for dim 0 2025-07-17T07:36:42.9694884Z if specified None or empty, dim 0 of ``output`` tensor must divide 2025-07-17T07:36:42.9695316Z equally by ``world_size``. 2025-07-17T07:36:42.9695717Z input_split_sizes: (list[Int], optional): Input split sizes for dim 0 2025-07-17T07:36:42.9696335Z if specified None or empty, dim 0 of ``input`` tensor must divide 2025-07-17T07:36:42.9696761Z equally by ``world_size``. 2025-07-17T07:36:42.9697195Z group (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:42.9697658Z the default process group will be used. 2025-07-17T07:36:42.9698097Z async_op (bool, optional): Whether this op should be an async op. 2025-07-17T07:36:42.9698406Z 2025-07-17T07:36:42.9698501Z Returns: 2025-07-17T07:36:42.9698745Z Async work handle, if async_op is set to True. 2025-07-17T07:36:42.9699144Z None, if not async_op or if not part of the group. 2025-07-17T07:36:42.9699397Z 2025-07-17T07:36:42.9699503Z .. warning:: 2025-07-17T07:36:42.9699827Z `all_to_all_single` is experimental and subject to change. 2025-07-17T07:36:42.9700105Z 2025-07-17T07:36:42.9700222Z Examples: 2025-07-17T07:36:42.9700553Z >>> # xdoctest: +SKIP("Undefined rank") 2025-07-17T07:36:42.9701047Z >>> input = torch.arange(4) + rank * 4 2025-07-17T07:36:42.9701503Z >>> input 2025-07-17T07:36:42.9701834Z tensor([0, 1, 2, 3]) # Rank 0 2025-07-17T07:36:42.9702235Z tensor([4, 5, 6, 7]) # Rank 1 2025-07-17T07:36:42.9702537Z tensor([8, 9, 10, 11]) # Rank 2 2025-07-17T07:36:42.9702821Z tensor([12, 13, 14, 15]) # Rank 3 2025-07-17T07:36:42.9703166Z >>> output = torch.empty([4], dtype=torch.int64) 2025-07-17T07:36:42.9703543Z >>> dist.all_to_all_single(output, input) 2025-07-17T07:36:42.9703847Z >>> output 2025-07-17T07:36:42.9704084Z tensor([0, 4, 8, 12]) # Rank 0 2025-07-17T07:36:42.9704385Z tensor([1, 5, 9, 13]) # Rank 1 2025-07-17T07:36:42.9704669Z tensor([2, 6, 10, 14]) # Rank 2 2025-07-17T07:36:42.9704962Z tensor([3, 7, 11, 15]) # Rank 3 2025-07-17T07:36:42.9705169Z 2025-07-17T07:36:42.9705331Z >>> # Essentially, it is similar to following operation: 2025-07-17T07:36:42.9705747Z >>> scatter_list = list(input.chunk(world_size)) 2025-07-17T07:36:42.9706130Z >>> gather_list = list(output.chunk(world_size)) 2025-07-17T07:36:42.9706486Z >>> for i in range(world_size): 2025-07-17T07:36:42.9706915Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src = i) 2025-07-17T07:36:42.9707260Z 2025-07-17T07:36:42.9707376Z >>> # Another example with uneven split 2025-07-17T07:36:42.9707696Z >>> input 2025-07-17T07:36:42.9707979Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-07-17T07:36:42.9708410Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-07-17T07:36:42.9708831Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-07-17T07:36:42.9709265Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-07-17T07:36:42.9709639Z >>> input_splits 2025-07-17T07:36:42.9709905Z [2, 2, 1, 1] # Rank 0 2025-07-17T07:36:42.9710273Z [3, 2, 2, 2] # Rank 1 2025-07-17T07:36:42.9710636Z [2, 1, 1, 1] # Rank 2 2025-07-17T07:36:42.9710995Z [2, 2, 2, 1] # Rank 3 2025-07-17T07:36:42.9711316Z >>> output_splits 2025-07-17T07:36:42.9711721Z [2, 3, 2, 2] # Rank 0 2025-07-17T07:36:42.9712079Z [2, 2, 1, 2] # Rank 1 2025-07-17T07:36:42.9712427Z [1, 2, 1, 2] # Rank 2 2025-07-17T07:36:42.9712792Z [1, 2, 1, 1] # Rank 3 2025-07-17T07:36:42.9713127Z >>> output = ... 2025-07-17T07:36:42.9713489Z >>> dist.all_to_all_single(output, input, output_splits, input_splits) 2025-07-17T07:36:42.9713882Z >>> output 2025-07-17T07:36:42.9714173Z tensor([ 0, 1, 10, 11, 12, 20, 21, 30, 31]) # Rank 0 2025-07-17T07:36:42.9714658Z tensor([ 2, 3, 13, 14, 22, 32, 33]) # Rank 1 2025-07-17T07:36:42.9715073Z tensor([ 4, 15, 16, 23, 34, 35]) # Rank 2 2025-07-17T07:36:42.9715499Z tensor([ 5, 17, 18, 24, 36]) # Rank 3 2025-07-17T07:36:42.9715772Z 2025-07-17T07:36:42.9715789Z 2025-07-17T07:36:42.9715949Z >>> # Another example with tensors of torch.cfloat type. 2025-07-17T07:36:42.9716330Z >>> input = torch.tensor( 2025-07-17T07:36:42.9716640Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-07-17T07:36:42.9716992Z ... ) + 4 * rank * (1 + 1j) 2025-07-17T07:36:42.9717256Z >>> input 2025-07-17T07:36:42.9717554Z tensor([1+1j, 2+2j, 3+3j, 4+4j]) # Rank 0 2025-07-17T07:36:42.9718020Z tensor([5+5j, 6+6j, 7+7j, 8+8j]) # Rank 1 2025-07-17T07:36:42.9718491Z tensor([9+9j, 10+10j, 11+11j, 12+12j]) # Rank 2 2025-07-17T07:36:42.9718961Z tensor([13+13j, 14+14j, 15+15j, 16+16j]) # Rank 3 2025-07-17T07:36:42.9719409Z >>> output = torch.empty([4], dtype=torch.int64) 2025-07-17T07:36:42.9719782Z >>> dist.all_to_all_single(output, input) 2025-07-17T07:36:42.9720104Z >>> output 2025-07-17T07:36:42.9720396Z tensor([1+1j, 5+5j, 9+9j, 13+13j]) # Rank 0 2025-07-17T07:36:42.9720865Z tensor([2+2j, 6+6j, 10+10j, 14+14j]) # Rank 1 2025-07-17T07:36:42.9721334Z tensor([3+3j, 7+7j, 11+11j, 15+15j]) # Rank 2 2025-07-17T07:36:42.9721791Z tensor([4+4j, 8+8j, 12+12j, 16+16j]) # Rank 3 2025-07-17T07:36:42.9722093Z 2025-07-17T07:36:42.9722344Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.9722723Z 2025-07-17T07:36:42.9723328Z msg = Cannot scrape callname=all_to_all in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4642. 2025-07-17T07:36:42.9724276Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.9724651Z 2025-07-17T07:36:42.9725026Z Scatters list of input tensors to all processes in a group and return gathered list of tensors in output list. 2025-07-17T07:36:42.9725600Z 2025-07-17T07:36:42.9725712Z Complex tensors are supported. 2025-07-17T07:36:42.9725916Z 2025-07-17T07:36:42.9725995Z Args: 2025-07-17T07:36:42.9726332Z output_tensor_list (list[Tensor]): List of tensors to be gathered one 2025-07-17T07:36:42.9726764Z per rank. 2025-07-17T07:36:42.9727121Z input_tensor_list (list[Tensor]): List of tensors to scatter one per rank. 2025-07-17T07:36:42.9727699Z group (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:42.9728177Z the default process group will be used. 2025-07-17T07:36:42.9728603Z async_op (bool, optional): Whether this op should be an async op. 2025-07-17T07:36:42.9728920Z 2025-07-17T07:36:42.9729003Z Returns: 2025-07-17T07:36:42.9729259Z Async work handle, if async_op is set to True. 2025-07-17T07:36:42.9729639Z None, if not async_op or if not part of the group. 2025-07-17T07:36:42.9729902Z 2025-07-17T07:36:42.9730067Z .. warning:: 2025-07-17T07:36:42.9730346Z `all_to_all` is experimental and subject to change. 2025-07-17T07:36:42.9730601Z 2025-07-17T07:36:42.9730699Z Examples: 2025-07-17T07:36:42.9730927Z >>> # xdoctest: +SKIP("Undefined rank") 2025-07-17T07:36:42.9731268Z >>> input = torch.arange(4) + rank * 4 2025-07-17T07:36:42.9731601Z >>> input = list(input.chunk(4)) 2025-07-17T07:36:42.9731883Z >>> input 2025-07-17T07:36:42.9732177Z [tensor([0]), tensor([1]), tensor([2]), tensor([3])] # Rank 0 2025-07-17T07:36:42.9732620Z [tensor([4]), tensor([5]), tensor([6]), tensor([7])] # Rank 1 2025-07-17T07:36:42.9733117Z [tensor([8]), tensor([9]), tensor([10]), tensor([11])] # Rank 2 2025-07-17T07:36:42.9733577Z [tensor([12]), tensor([13]), tensor([14]), tensor([15])] # Rank 3 2025-07-17T07:36:42.9734041Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-07-17T07:36:42.9734456Z >>> dist.all_to_all(output, input) 2025-07-17T07:36:42.9734753Z >>> output 2025-07-17T07:36:42.9735056Z [tensor([0]), tensor([4]), tensor([8]), tensor([12])] # Rank 0 2025-07-17T07:36:42.9735504Z [tensor([1]), tensor([5]), tensor([9]), tensor([13])] # Rank 1 2025-07-17T07:36:42.9735937Z [tensor([2]), tensor([6]), tensor([10]), tensor([14])] # Rank 2 2025-07-17T07:36:42.9736378Z [tensor([3]), tensor([7]), tensor([11]), tensor([15])] # Rank 3 2025-07-17T07:36:42.9736666Z 2025-07-17T07:36:42.9736827Z >>> # Essentially, it is similar to following operation: 2025-07-17T07:36:42.9737202Z >>> scatter_list = input 2025-07-17T07:36:42.9737468Z >>> gather_list = output 2025-07-17T07:36:42.9737749Z >>> for i in range(world_size): 2025-07-17T07:36:42.9738176Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src=i) 2025-07-17T07:36:42.9738513Z 2025-07-17T07:36:42.9738596Z >>> input 2025-07-17T07:36:42.9738879Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-07-17T07:36:42.9739310Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-07-17T07:36:42.9739738Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-07-17T07:36:42.9740155Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-07-17T07:36:42.9740522Z >>> input_splits 2025-07-17T07:36:42.9740797Z [2, 2, 1, 1] # Rank 0 2025-07-17T07:36:42.9741147Z [3, 2, 2, 2] # Rank 1 2025-07-17T07:36:42.9741505Z [2, 1, 1, 1] # Rank 2 2025-07-17T07:36:42.9741867Z [2, 2, 2, 1] # Rank 3 2025-07-17T07:36:42.9742201Z >>> output_splits 2025-07-17T07:36:42.9742461Z [2, 3, 2, 2] # Rank 0 2025-07-17T07:36:42.9742815Z [2, 2, 1, 2] # Rank 1 2025-07-17T07:36:42.9743175Z [1, 2, 1, 2] # Rank 2 2025-07-17T07:36:42.9743520Z [1, 2, 1, 1] # Rank 3 2025-07-17T07:36:42.9743886Z >>> input = list(input.split(input_splits)) 2025-07-17T07:36:42.9744207Z >>> input 2025-07-17T07:36:42.9744523Z [tensor([0, 1]), tensor([2, 3]), tensor([4]), tensor([5])] # Rank 0 2025-07-17T07:36:42.9745041Z [tensor([10, 11, 12]), tensor([13, 14]), tensor([15, 16]), tensor([17, 18])] # Rank 1 2025-07-17T07:36:42.9745570Z [tensor([20, 21]), tensor([22]), tensor([23]), tensor([24])] # Rank 2 2025-07-17T07:36:42.9746101Z [tensor([30, 31]), tensor([32, 33]), tensor([34, 35]), tensor([36])] # Rank 3 2025-07-17T07:36:42.9746508Z >>> output = ... 2025-07-17T07:36:42.9746783Z >>> dist.all_to_all(output, input) 2025-07-17T07:36:42.9747092Z >>> output 2025-07-17T07:36:42.9747488Z [tensor([0, 1]), tensor([10, 11, 12]), tensor([20, 21]), tensor([30, 31])] # Rank 0 2025-07-17T07:36:42.9748016Z [tensor([2, 3]), tensor([13, 14]), tensor([22]), tensor([32, 33])] # Rank 1 2025-07-17T07:36:42.9748541Z [tensor([4]), tensor([15, 16]), tensor([23]), tensor([34, 35])] # Rank 2 2025-07-17T07:36:42.9749060Z [tensor([5]), tensor([17, 18]), tensor([24]), tensor([36])] # Rank 3 2025-07-17T07:36:42.9749379Z 2025-07-17T07:36:42.9749540Z >>> # Another example with tensors of torch.cfloat type. 2025-07-17T07:36:42.9749920Z >>> input = torch.tensor( 2025-07-17T07:36:42.9750244Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-07-17T07:36:42.9750633Z ... ) + 4 * rank * (1 + 1j) 2025-07-17T07:36:42.9750931Z >>> input = list(input.chunk(4)) 2025-07-17T07:36:42.9751227Z >>> input 2025-07-17T07:36:42.9751571Z [tensor([1+1j]), tensor([2+2j]), tensor([3+3j]), tensor([4+4j])] # Rank 0 2025-07-17T07:36:42.9752107Z [tensor([5+5j]), tensor([6+6j]), tensor([7+7j]), tensor([8+8j])] # Rank 1 2025-07-17T07:36:42.9752658Z [tensor([9+9j]), tensor([10+10j]), tensor([11+11j]), tensor([12+12j])] # Rank 2 2025-07-17T07:36:42.9753223Z [tensor([13+13j]), tensor([14+14j]), tensor([15+15j]), tensor([16+16j])] # Rank 3 2025-07-17T07:36:42.9753736Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-07-17T07:36:42.9754267Z >>> dist.all_to_all(output, input) 2025-07-17T07:36:42.9754740Z >>> output 2025-07-17T07:36:42.9755198Z [tensor([1+1j]), tensor([5+5j]), tensor([9+9j]), tensor([13+13j])] # Rank 0 2025-07-17T07:36:42.9756033Z [tensor([2+2j]), tensor([6+6j]), tensor([10+10j]), tensor([14+14j])] # Rank 1 2025-07-17T07:36:42.9756973Z [tensor([3+3j]), tensor([7+7j]), tensor([11+11j]), tensor([15+15j])] # Rank 2 2025-07-17T07:36:42.9757704Z [tensor([4+4j]), tensor([8+8j]), tensor([12+12j]), tensor([16+16j])] # Rank 3 2025-07-17T07:36:42.9758036Z 2025-07-17T07:36:42.9758041Z 2025-07-17T07:36:42.9758309Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.9758678Z 2025-07-17T07:36:42.9759216Z msg = Cannot scrape callname=__doc__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/launch.py line=2. 2025-07-17T07:36:42.9760164Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:42.9760538Z 2025-07-17T07:36:42.9760652Z Module ``torch.distributed.launch``. 2025-07-17T07:36:42.9760882Z 2025-07-17T07:36:42.9761130Z ``torch.distributed.launch`` is a module that spawns up multiple distributed 2025-07-17T07:36:42.9761662Z training processes on each of the training nodes. 2025-07-17T07:36:42.9761923Z 2025-07-17T07:36:42.9762034Z .. warning:: 2025-07-17T07:36:42.9762159Z 2025-07-17T07:36:42.9762410Z This module is going to be deprecated in favor of :ref:`torchrun `. 2025-07-17T07:36:42.9762800Z 2025-07-17T07:36:42.9763134Z The utility can be used for single-node distributed training, in which one or 2025-07-17T07:36:42.9763737Z more processes per node will be spawned. The utility can be used for either 2025-07-17T07:36:42.9764301Z CPU training or GPU training. If the utility is used for GPU training, 2025-07-17T07:36:42.9764884Z each distributed process will be operating on a single GPU. This can achieve 2025-07-17T07:36:42.9765565Z well-improved single-node training performance. It can also be used in 2025-07-17T07:36:42.9766188Z multi-node distributed training, by spawning up multiple processes on each node 2025-07-17T07:36:42.9766791Z for well-improved multi-node distributed training performance as well. 2025-07-17T07:36:42.9767375Z This will especially be beneficial for systems with multiple Infiniband 2025-07-17T07:36:42.9767973Z interfaces that have direct-GPU support, since all of them can be utilized for 2025-07-17T07:36:42.9768451Z aggregated communication bandwidth. 2025-07-17T07:36:42.9768780Z 2025-07-17T07:36:42.9769009Z In both cases of single-node distributed training or multi-node distributed 2025-07-17T07:36:42.9769600Z training, this utility will launch the given number of processes per node 2025-07-17T07:36:42.9770467Z (``--nproc-per-node``). If used for GPU training, this number needs to be less 2025-07-17T07:36:42.9771022Z or equal to the number of GPUs on the current system (``nproc_per_node``), 2025-07-17T07:36:42.9771561Z and each process will be operating on a single GPU from *GPU 0 to 2025-07-17T07:36:42.9771995Z GPU (nproc_per_node - 1)*. 2025-07-17T07:36:42.9772170Z 2025-07-17T07:36:42.9772284Z **How to use this module:** 2025-07-17T07:36:42.9772457Z 2025-07-17T07:36:42.9772724Z 1. Single-Node multi-process distributed training 2025-07-17T07:36:42.9772996Z 2025-07-17T07:36:42.9773085Z :: 2025-07-17T07:36:42.9773191Z 2025-07-17T07:36:42.9773438Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-07-17T07:36:42.9773972Z YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other 2025-07-17T07:36:42.9774437Z arguments of your training script) 2025-07-17T07:36:42.9774680Z 2025-07-17T07:36:42.9774885Z 2. Multi-Node multi-process distributed training: (e.g. two nodes) 2025-07-17T07:36:42.9775205Z 2025-07-17T07:36:42.9775208Z 2025-07-17T07:36:42.9775362Z Node 1: *(IP: 192.168.1.1, and has a free port: 1234)* 2025-07-17T07:36:42.9775611Z 2025-07-17T07:36:42.9775689Z :: 2025-07-17T07:36:42.9775806Z 2025-07-17T07:36:42.9776039Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-07-17T07:36:42.9776547Z --nnodes=2 --node-rank=0 --master-addr="192.168.1.1" 2025-07-17T07:36:42.9777038Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-07-17T07:36:42.9777504Z and all other arguments of your training script) 2025-07-17T07:36:42.9777777Z 2025-07-17T07:36:42.9777858Z Node 2: 2025-07-17T07:36:42.9777970Z 2025-07-17T07:36:42.9778062Z :: 2025-07-17T07:36:42.9778169Z 2025-07-17T07:36:42.9778401Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-07-17T07:36:42.9778912Z --nnodes=2 --node-rank=1 --master-addr="192.168.1.1" 2025-07-17T07:36:42.9779390Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-07-17T07:36:42.9779866Z and all other arguments of your training script) 2025-07-17T07:36:42.9780124Z 2025-07-17T07:36:42.9780281Z 3. To look up what optional arguments this module offers: 2025-07-17T07:36:42.9780563Z 2025-07-17T07:36:42.9780642Z :: 2025-07-17T07:36:42.9780745Z 2025-07-17T07:36:42.9780890Z python -m torch.distributed.launch --help 2025-07-17T07:36:42.9781133Z 2025-07-17T07:36:42.9781136Z 2025-07-17T07:36:42.9781275Z **Important Notices:** 2025-07-17T07:36:42.9781433Z 2025-07-17T07:36:42.9781615Z 1. This utility and multi-process distributed (single-node or 2025-07-17T07:36:42.9782164Z multi-node) GPU training currently only achieves the best performance using 2025-07-17T07:36:42.9782780Z the NCCL distributed backend. Thus NCCL backend is the recommended backend to 2025-07-17T07:36:42.9783237Z use for GPU training. 2025-07-17T07:36:42.9783399Z 2025-07-17T07:36:42.9783609Z 2. In your training program, you must parse the command-line argument: 2025-07-17T07:36:42.9784167Z ``--local-rank=LOCAL_PROCESS_RANK``, which will be provided by this module. 2025-07-17T07:36:42.9784741Z If your training program uses GPUs, you should ensure that your code only 2025-07-17T07:36:42.9785264Z runs on the GPU device of LOCAL_PROCESS_RANK. This can be done by: 2025-07-17T07:36:42.9785577Z 2025-07-17T07:36:42.9785683Z Parsing the local_rank argument 2025-07-17T07:36:42.9785874Z 2025-07-17T07:36:42.9785964Z :: 2025-07-17T07:36:42.9786071Z 2025-07-17T07:36:42.9786174Z >>> # xdoctest: +SKIP 2025-07-17T07:36:42.9786424Z >>> import argparse 2025-07-17T07:36:42.9786702Z >>> parser = argparse.ArgumentParser() 2025-07-17T07:36:42.9787124Z >>> parser.add_argument("--local-rank", "--local_rank", type=int) 2025-07-17T07:36:42.9787643Z >>> args = parser.parse_args() 2025-07-17T07:36:42.9787852Z 2025-07-17T07:36:42.9787969Z Set your device to local rank using either 2025-07-17T07:36:42.9788191Z 2025-07-17T07:36:42.9788282Z :: 2025-07-17T07:36:42.9788385Z 2025-07-17T07:36:42.9788582Z >>> torch.cuda.set_device(args.local_rank) # before your code runs 2025-07-17T07:36:42.9788905Z 2025-07-17T07:36:42.9788981Z or 2025-07-17T07:36:42.9789100Z 2025-07-17T07:36:42.9789219Z :: 2025-07-17T07:36:42.9789321Z 2025-07-17T07:36:42.9789461Z >>> with torch.cuda.device(args.local_rank): 2025-07-17T07:36:42.9789789Z >>> # your code to run 2025-07-17T07:36:42.9790108Z >>> ... 2025-07-17T07:36:42.9790239Z 2025-07-17T07:36:42.9790354Z .. versionchanged:: 2.0.0 2025-07-17T07:36:42.9790519Z 2025-07-17T07:36:42.9790764Z The launcher will passes the ``--local-rank=`` argument to your script. 2025-07-17T07:36:42.9791359Z From PyTorch 2.0.0 onwards, the dashed ``--local-rank`` is preferred over the 2025-07-17T07:36:42.9791865Z previously used underscored ``--local_rank``. 2025-07-17T07:36:42.9792110Z 2025-07-17T07:36:42.9792359Z For backward compatibility, it may be necessary for users to handle both 2025-07-17T07:36:42.9792970Z cases in their argument parsing code. This means including both ``"--local-rank"`` 2025-07-17T07:36:42.9793570Z and ``"--local_rank"`` in the argument parser. If only ``"--local_rank"`` is 2025-07-17T07:36:42.9794150Z provided, the launcher will trigger an error: "error: unrecognized arguments: 2025-07-17T07:36:42.9794750Z --local-rank=". For training code that only supports PyTorch 2.0.0+, 2025-07-17T07:36:42.9795240Z including ``"--local-rank"`` should be sufficient. 2025-07-17T07:36:42.9795504Z 2025-07-17T07:36:42.9795733Z 3. In your training program, you are supposed to call the following function 2025-07-17T07:36:42.9796325Z at the beginning to start the distributed backend. It is strongly recommended 2025-07-17T07:36:42.9796903Z that ``init_method=env://``. Other init methods (e.g. ``tcp://``) may work, 2025-07-17T07:36:42.9797429Z but ``env://`` is the one that is officially supported by this module. 2025-07-17T07:36:42.9797742Z 2025-07-17T07:36:42.9797822Z :: 2025-07-17T07:36:42.9797928Z 2025-07-17T07:36:42.9798141Z >>> torch.distributed.init_process_group(backend='YOUR BACKEND', 2025-07-17T07:36:42.9798585Z >>> init_method='env://') 2025-07-17T07:36:42.9798833Z 2025-07-17T07:36:42.9799068Z 4. In your training program, you can either use regular distributed functions 2025-07-17T07:36:42.9799668Z or use :func:`torch.nn.parallel.DistributedDataParallel` module. If your 2025-07-17T07:36:42.9800227Z training program uses GPUs for training and you would like to use 2025-07-17T07:36:42.9800726Z :func:`torch.nn.parallel.DistributedDataParallel` module, 2025-07-17T07:36:42.9801132Z here is how to configure it. 2025-07-17T07:36:42.9801316Z 2025-07-17T07:36:42.9801407Z :: 2025-07-17T07:36:42.9801511Z 2025-07-17T07:36:42.9801701Z >>> model = torch.nn.parallel.DistributedDataParallel(model, 2025-07-17T07:36:42.9802138Z >>> device_ids=[args.local_rank], 2025-07-17T07:36:42.9802528Z >>> output_device=args.local_rank) 2025-07-17T07:36:42.9802798Z 2025-07-17T07:36:42.9803037Z Please ensure that ``device_ids`` argument is set to be the only GPU device id 2025-07-17T07:36:42.9803628Z that your code will be operating on. This is generally the local rank of the 2025-07-17T07:36:42.9804222Z process. In other words, the ``device_ids`` needs to be ``[args.local_rank]``, 2025-07-17T07:36:42.9804778Z and ``output_device`` needs to be ``args.local_rank`` in order to use this 2025-07-17T07:36:42.9805192Z utility 2025-07-17T07:36:42.9805383Z 2025-07-17T07:36:42.9805642Z 5. Another way to pass ``local_rank`` to the subprocesses via environment variable 2025-07-17T07:36:42.9806301Z ``LOCAL_RANK``. This behavior is enabled when you launch the script with 2025-07-17T07:36:42.9806852Z ``--use-env=True``. You must adjust the subprocess example above to replace 2025-07-17T07:36:42.9807386Z ``args.local_rank`` with ``os.environ['LOCAL_RANK']``; the launcher 2025-07-17T07:36:42.9807863Z will not pass ``--local-rank`` when you specify this flag. 2025-07-17T07:36:42.9808140Z 2025-07-17T07:36:42.9808241Z .. warning:: 2025-07-17T07:36:42.9808364Z 2025-07-17T07:36:42.9808562Z ``local_rank`` is NOT globally unique: it is only unique per process 2025-07-17T07:36:42.9809068Z on a machine. Thus, don't use it to decide if you should, e.g., 2025-07-17T07:36:42.9809548Z write to a networked filesystem. See 2025-07-17T07:36:42.9809984Z https://github.com/pytorch/pytorch/issues/12042 for an example of 2025-07-17T07:36:42.9810476Z how things can go wrong if you don't do this correctly. 2025-07-17T07:36:42.9810749Z 2025-07-17T07:36:42.9810764Z 2025-07-17T07:36:42.9810772Z 2025-07-17T07:36:42.9810776Z 2025-07-17T07:36:42.9811024Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:42.9811391Z 2025-07-17T07:36:43.0427186Z msg = Cannot scrape callname=init_from_local_shards in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py line=361. 2025-07-17T07:36:43.0428264Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.0428641Z 2025-07-17T07:36:43.0428879Z Creates an :class:`ShardedTensor` from local shards and the global metadata. 2025-07-17T07:36:43.0429383Z Needs to be called on all ranks in an SPMD fashion. 2025-07-17T07:36:43.0429656Z 2025-07-17T07:36:43.0429748Z Args: 2025-07-17T07:36:43.0430139Z local_shards (List[:class `torch.distributed._shard.sharded_tensor.Shard`]): A list 2025-07-17T07:36:43.0430688Z of shards that represent the local shards on this rank. 2025-07-17T07:36:43.0431209Z global_size (int...): a list, tuple, or `torch.Size` of integers defining the 2025-07-17T07:36:43.0431679Z shape of the overall sharded tensor. 2025-07-17T07:36:43.0431903Z 2025-07-17T07:36:43.0431993Z Keyword args: 2025-07-17T07:36:43.0432394Z process_group (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:43.0432905Z the default process group will be used. 2025-07-17T07:36:43.0433300Z init_rrefs (bool, optional): Whether or not to initialize 2025-07-17T07:36:43.0433792Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-07-17T07:36:43.0434310Z Need to initialize the RPC Framework if specified as ``True``. 2025-07-17T07:36:43.0434720Z Default: ``False``. 2025-07-17T07:36:43.0434888Z 2025-07-17T07:36:43.0434971Z Returns: 2025-07-17T07:36:43.0435243Z A :class:`ShardedTensor` object handle on this rank 2025-07-17T07:36:43.0435502Z 2025-07-17T07:36:43.0435506Z 2025-07-17T07:36:43.0435618Z Examples: 2025-07-17T07:36:43.0435996Z Suppose we want construct a sharded tensor on two ranks, global size = (10, 5), 2025-07-17T07:36:43.0436542Z each shard have a (5, 5) local tensor, we can do it like below: 2025-07-17T07:36:43.0436848Z 2025-07-17T07:36:43.0436932Z on rank 0: 2025-07-17T07:36:43.0437187Z >>> # xdoctest: +SKIP("not distributed") 2025-07-17T07:36:43.0437530Z >>> local_shard_metadata = ShardMetadata( 2025-07-17T07:36:43.0437868Z >>> shard_offsets=[0, 0], 2025-07-17T07:36:43.0438160Z >>> shard_lengths=[5, 5], 2025-07-17T07:36:43.0438450Z >>> placement="rank:0/cuda:0" 2025-07-17T07:36:43.0438792Z >>> ) 2025-07-17T07:36:43.0439107Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-07-17T07:36:43.0439618Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-07-17T07:36:43.0439921Z 2025-07-17T07:36:43.0440001Z on rank 1: 2025-07-17T07:36:43.0440269Z >>> # xdoctest: +SKIP("not distributed") 2025-07-17T07:36:43.0440851Z >>> local_shard_metadata = ShardMetadata( 2025-07-17T07:36:43.0441189Z >>> shard_offsets=[5, 0], 2025-07-17T07:36:43.0441473Z >>> shard_lengths=[5, 5], 2025-07-17T07:36:43.0441779Z >>> placement="rank:1/cuda:1" 2025-07-17T07:36:43.0442073Z >>> ) 2025-07-17T07:36:43.0442374Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-07-17T07:36:43.0442878Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-07-17T07:36:43.0443181Z 2025-07-17T07:36:43.0443445Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.0443809Z 2025-07-17T07:36:43.0559234Z msg = Cannot scrape callname=ShardedTensor._init_from_local_tensor in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=835. 2025-07-17T07:36:43.0560352Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.0560744Z 2025-07-17T07:36:43.0561006Z Initialize a ShardedTensor given only one local tensor, global sharded tensor 2025-07-17T07:36:43.0561504Z size and sharding spec on each rank. 2025-07-17T07:36:43.0561713Z 2025-07-17T07:36:43.0561808Z Args: 2025-07-17T07:36:43.0562134Z local_tensor (Tensor): Single tensor of local shard stored in each rank. 2025-07-17T07:36:43.0562748Z sharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): 2025-07-17T07:36:43.0563297Z The specification describing how to shard the Tensor. 2025-07-17T07:36:43.0563742Z global_size (Sequence[int]): Size of the sharded tensor. 2025-07-17T07:36:43.0564289Z process_group (ProcessGroup, optional): The process group to aggregate on. 2025-07-17T07:36:43.0564804Z Default: None 2025-07-17T07:36:43.0565233Z init_rrefs (bool, optional): Whether or not to initialize 2025-07-17T07:36:43.0565853Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-07-17T07:36:43.0566679Z Need to initialize the RPC Framework if specified as ``True``. 2025-07-17T07:36:43.0567313Z Default: ``False``. 2025-07-17T07:36:43.0567484Z 2025-07-17T07:36:43.0567566Z Returns: 2025-07-17T07:36:43.0567925Z A :class:`ShardedTensor` sharded based on the given sharding_spec with local 2025-07-17T07:36:43.0568402Z tensor stored in the current rank. 2025-07-17T07:36:43.0568620Z 2025-07-17T07:36:43.0568715Z Examples: 2025-07-17T07:36:43.0568920Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.0569222Z >>> # All tensors below are of torch.int64 type. 2025-07-17T07:36:43.0569585Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:43.0570132Z >>> tensor = torch.arange(2, dtype=torch.int64) + 1 + 2 * rank 2025-07-17T07:36:43.0570630Z >>> local_tensor = torch.unsqueeze(torch.cat([tensor, tensor + 2])) 2025-07-17T07:36:43.0571039Z >>> local_tensor 2025-07-17T07:36:43.0571279Z tensor([[1, 2, 3, 4]]) # Rank 0 2025-07-17T07:36:43.0571614Z tensor([[3, 4, 5, 6]]) # Rank 1 2025-07-17T07:36:43.0571915Z >>> sharding_dim = 0 2025-07-17T07:36:43.0572205Z >>> sharding_spec = ChunkShardingSpec( 2025-07-17T07:36:43.0572525Z dim=sharding_dim, 2025-07-17T07:36:43.0572808Z placements=[ 2025-07-17T07:36:43.0573071Z "rank:0/cuda:0", 2025-07-17T07:36:43.0573340Z "rank:1/cuda:1", 2025-07-17T07:36:43.0573613Z ], 2025-07-17T07:36:43.0573827Z ) 2025-07-17T07:36:43.0574066Z >>> st = ShardedTensor._init_from_local_tensor( 2025-07-17T07:36:43.0574434Z ... local_tensor, sharding_spec, [2, 4] 2025-07-17T07:36:43.0574754Z ... ) 2025-07-17T07:36:43.0574960Z >>> st 2025-07-17T07:36:43.0575164Z ShardedTensor( 2025-07-17T07:36:43.0575424Z ShardedTensorMetadata( 2025-07-17T07:36:43.0575719Z shards_metadata=[ 2025-07-17T07:36:43.0576160Z ShardMetadata(shard_offsets=[0, 0], shard_sizes=[1, 4], placement=rank:0/cuda:0), 2025-07-17T07:36:43.0576848Z ShardMetadata(shard_offsets=[1, 0], shard_sizes=[1, 4], placement=rank:1/cuda:1), 2025-07-17T07:36:43.0577467Z ], 2025-07-17T07:36:43.0577697Z size=torch.Size([2, 4]) 2025-07-17T07:36:43.0577984Z ) 2025-07-17T07:36:43.0578196Z >>> st.local_tensor() 2025-07-17T07:36:43.0578446Z tensor([1, 2, 3, 4]) # Rank 0 2025-07-17T07:36:43.0578737Z tensor([3, 4, 5, 6]) # Rank 1 2025-07-17T07:36:43.0578933Z 2025-07-17T07:36:43.0579196Z Warning: This API is experimental and subject to change. It lacks of a fully across 2025-07-17T07:36:43.0579826Z rank validations, and we only validate the local shard on the current rank. 2025-07-17T07:36:43.0580495Z We fully rely on the user to ensure local tensor is sharded based on the 2025-07-17T07:36:43.0580925Z sharding spec. 2025-07-17T07:36:43.0581078Z 2025-07-17T07:36:43.0581343Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.0581709Z 2025-07-17T07:36:43.0582406Z msg = Cannot scrape callname=ShardedTensor.reshard in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=1076. 2025-07-17T07:36:43.0583446Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.0583830Z 2025-07-17T07:36:43.0584075Z Reshard a sharded tensor given the ``resharding_spec``. For now, we only support 2025-07-17T07:36:43.0584540Z single local shard. 2025-07-17T07:36:43.0584685Z 2025-07-17T07:36:43.0584912Z If ``resharding_spec`` is same as the original one, this becomes a no-op. 2025-07-17T07:36:43.0585474Z If only ``resharding_spec`` shares the same sharding dim with the original one, 2025-07-17T07:36:43.0585944Z we swap local shards directly. 2025-07-17T07:36:43.0586389Z For more generic cases, we merge different shards across different ranks and split 2025-07-17T07:36:43.0587008Z the local shards based on the ``resharding_spec`` via `all_to_all` collective API. 2025-07-17T07:36:43.0587390Z 2025-07-17T07:36:43.0587471Z Args: 2025-07-17T07:36:43.0587874Z resharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): The 2025-07-17T07:36:43.0588447Z specification describing how the tensor is sharded. 2025-07-17T07:36:43.0588719Z 2025-07-17T07:36:43.0588799Z Returns: 2025-07-17T07:36:43.0589120Z A :class:`ShardedTensor` object whose local shards are resharded. 2025-07-17T07:36:43.0589433Z 2025-07-17T07:36:43.0589528Z Examples: 2025-07-17T07:36:43.0589738Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.0590025Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:43.0590430Z >>> tensor = torch.arange(4, dtype=torch.int64) + 1 + 2 * rank 2025-07-17T07:36:43.0590837Z >>> tensor = torch.stack([tensor, tensor]) 2025-07-17T07:36:43.0591154Z >>> tensor 2025-07-17T07:36:43.0591399Z tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) # Rank 0 2025-07-17T07:36:43.0591742Z tensor([[3, 4, 5, 6], [3, 4, 5, 6]]) # Rank 1 2025-07-17T07:36:43.0592066Z tensor([[5, 6, 7, 8], [5, 6, 7, 8]]) # Rank 2 2025-07-17T07:36:43.0592415Z tensor([[7, 8, 9, 10], [7, 8, 9, 10]]) # Rank 3 2025-07-17T07:36:43.0592747Z >>> sharding_dim = 0 2025-07-17T07:36:43.0593009Z >>> spec = ChunkShardingSpec( 2025-07-17T07:36:43.0593307Z dim=sharding_dim, 2025-07-17T07:36:43.0593581Z placements=[ 2025-07-17T07:36:43.0593828Z "rank:0/cuda:0", 2025-07-17T07:36:43.0594109Z "rank:1/cuda:1", 2025-07-17T07:36:43.0594385Z "rank:2/cuda:2", 2025-07-17T07:36:43.0594648Z "rank:3/cuda:3", 2025-07-17T07:36:43.0594914Z ], 2025-07-17T07:36:43.0595130Z ) 2025-07-17T07:36:43.0595343Z >>> current_offsets = [0] * 2 2025-07-17T07:36:43.0595646Z >>> current_offsets[0] = rank * 2 2025-07-17T07:36:43.0595998Z >>> shard_metadata = ShardMetadata( 2025-07-17T07:36:43.0596366Z shard_offsets=copy.deepcopy(current_offsets), 2025-07-17T07:36:43.0596727Z shard_sizes=tensor.size(), 2025-07-17T07:36:43.0597138Z placement=spec.placements[rank], 2025-07-17T07:36:43.0597453Z ) 2025-07-17T07:36:43.0597658Z >>> local_shards = [ 2025-07-17T07:36:43.0597927Z Shard( 2025-07-17T07:36:43.0598166Z tensor=tensor, 2025-07-17T07:36:43.0598444Z metadata=shard_metadata, 2025-07-17T07:36:43.0598745Z ) 2025-07-17T07:36:43.0598958Z ] 2025-07-17T07:36:43.0599292Z >>> st = ShardedTensor._init_from_local_shards(local_shards, tensor.size()) 2025-07-17T07:36:43.0599736Z >>> sharding_dim = 1 2025-07-17T07:36:43.0600023Z >>> resharding_spec = ChunkShardingSpec( 2025-07-17T07:36:43.0600341Z dim=sharding_dim, 2025-07-17T07:36:43.0600672Z placements=[ 2025-07-17T07:36:43.0600930Z "rank:0/cuda:0", 2025-07-17T07:36:43.0601203Z "rank:1/cuda:1", 2025-07-17T07:36:43.0601462Z "rank:2/cuda:2", 2025-07-17T07:36:43.0601734Z "rank:3/cuda:3", 2025-07-17T07:36:43.0602008Z ], 2025-07-17T07:36:43.0602208Z ) 2025-07-17T07:36:43.0602431Z >>> st.reshard(resharding_spec) 2025-07-17T07:36:43.0602749Z >>> tensor = st.local_shards()[0].tensor 2025-07-17T07:36:43.0603045Z >>> tensor 2025-07-17T07:36:43.0603314Z tensor([[1], [1], [3], [3], [5], [5], [7], [7]]) # Rank 0 2025-07-17T07:36:43.0603710Z tensor([[2], [2], [4], [4], [6], [6], [8], [8]]) # Rank 1 2025-07-17T07:36:43.0604087Z tensor([[3], [3], [5], [5], [7], [7], [9], [9]]) # Rank 2 2025-07-17T07:36:43.0604538Z tensor([[4], [4], [6], [6], [8], [8], [10], [10]]) # Rank 3 2025-07-17T07:36:43.0604789Z 2025-07-17T07:36:43.0605059Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.0605515Z 2025-07-17T07:36:43.0774283Z msg = Cannot scrape callname=ShardingPlan in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharding_plan/api.py line=12. 2025-07-17T07:36:43.0775279Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.0775681Z 2025-07-17T07:36:43.0775895Z Representation of a sharding plan, describes how to shard a module 2025-07-17T07:36:43.0776491Z across hosts. `plan` is used to shard module parameters according to the spec provided, 2025-07-17T07:36:43.0777164Z `output_plan` and `return_local_tensor` are optional, they are used to specify the output 2025-07-17T07:36:43.0777805Z layout of a module with a spec, and when to convert back to data parallel fashion. 2025-07-17T07:36:43.0778178Z 2025-07-17T07:36:43.0778259Z Args: 2025-07-17T07:36:43.0778640Z plan (Dict[str, Union[:class:`torch.distributed._shard.sharding_spec.ShardingSpec`, 2025-07-17T07:36:43.0779200Z :class:`torch.distributed._shard.sharder.Sharder`]): 2025-07-17T07:36:43.0779734Z a dict describes how to shard a module, there're currently two ways to shard a module: 2025-07-17T07:36:43.0780415Z 1. directly shard a module parameter by a `ShardingSpec`, keyed by the name of 2025-07-17T07:36:43.0780915Z a parameter to a `ShardingSpec`. 2025-07-17T07:36:43.0781391Z 2. shard a submodule by applying a `Sharder` on it, keyed by the name of a module 2025-07-17T07:36:43.0781874Z to a `Sharder` object. 2025-07-17T07:36:43.0782411Z output_plan (Dict[str, :class:`torch.distributed._shard.sharding_spec.ShardingSpec`), optional): 2025-07-17T07:36:43.0783119Z a dict specifies the layout of a module's output which produces a ShardedTensor, 2025-07-17T07:36:43.0783724Z keyed by the name of module to ShardingSpec("" in key means the root module). 2025-07-17T07:36:43.0784176Z Default: `None` 2025-07-17T07:36:43.0784591Z return_local_tensor (List[str], optional): a list of string, each element enables 2025-07-17T07:36:43.0785197Z a module's sharded output to be returned as a Tensor from its local shards to 2025-07-17T07:36:43.0785808Z ensure further processing in a data parallel fashion. ("" in list means the 2025-07-17T07:36:43.0786420Z root module). 2025-07-17T07:36:43.0786667Z Default: None 2025-07-17T07:36:43.0786899Z Example: 2025-07-17T07:36:43.0787301Z Suppose we want to shard a module with two linear layers and then run it with DDP, we also 2025-07-17T07:36:43.0787988Z want to convert the output of the second linear layer back to DDP, we can do it as follows: 2025-07-17T07:36:43.0788382Z 2025-07-17T07:36:43.0788548Z >>> # xdoctest: +REQUIRES(module:torch._C._distributed_c10d) 2025-07-17T07:36:43.0788937Z >>> class MyModule(nn.Module): 2025-07-17T07:36:43.0789265Z >>> def __init__(self) -> None: 2025-07-17T07:36:43.0789705Z >>> super().__init__() 2025-07-17T07:36:43.0789987Z >>> self.fc1 = nn.Linear() 2025-07-17T07:36:43.0790290Z >>> self.gelu = nn.GELU() 2025-07-17T07:36:43.0790593Z >>> self.fc2 = nn.Linear() 2025-07-17T07:36:43.0790883Z >>> self.relu = nn.Linear() 2025-07-17T07:36:43.0791176Z >>> 2025-07-17T07:36:43.0791391Z >>> def forward(self, input): 2025-07-17T07:36:43.0791752Z >>> return self.relu(self.fc2(self.gelu(self.fc1(input)))) 2025-07-17T07:36:43.0792051Z 2025-07-17T07:36:43.0792056Z 2025-07-17T07:36:43.0792185Z >>> # xdoctest: +SKIP("Undefined spec1, spec2) 2025-07-17T07:36:43.0792536Z >>> sharding_plan = ShardingPlan( 2025-07-17T07:36:43.0792835Z >>> plan={ 2025-07-17T07:36:43.0793062Z >>> "fc1.weight": spec1, 2025-07-17T07:36:43.0793360Z >>> "fc2.weight": spec2 2025-07-17T07:36:43.0793636Z >>> }, 2025-07-17T07:36:43.0793853Z >>> output_plan={ 2025-07-17T07:36:43.0794167Z >>> "fc2": output_spec 2025-07-17T07:36:43.0794444Z >>> }, 2025-07-17T07:36:43.0794670Z >>> return_local_tensor=["fc2"] 2025-07-17T07:36:43.0794968Z >>> ) 2025-07-17T07:36:43.0795080Z 2025-07-17T07:36:43.0795341Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.0795716Z 2025-07-17T07:36:43.1678545Z msg = Cannot scrape callname=post_localSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/post_localSGD_hook.py line=72. 2025-07-17T07:36:43.1679684Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.1680077Z 2025-07-17T07:36:43.1680190Z Run post-localSGD algorithm. 2025-07-17T07:36:43.1680387Z 2025-07-17T07:36:43.1680620Z This DDP communication hook is used for running post-localSGD algorithm, 2025-07-17T07:36:43.1681135Z by combining with a model averaging component (e.g., 2025-07-17T07:36:43.1681735Z :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`) 2025-07-17T07:36:43.1682297Z that runs after the optimizer step. 2025-07-17T07:36:43.1682503Z 2025-07-17T07:36:43.1682608Z Args: 2025-07-17T07:36:43.1682983Z state (PostLocalSGDState): State information to run post-localSGD. 2025-07-17T07:36:43.1683628Z Users mainly need to tune ``start_localSGD_iter`` to determine when to start local SGD. 2025-07-17T07:36:43.1684444Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-07-17T07:36:43.1685237Z Note that since DDP comm hook only supports single process single device mode, 2025-07-17T07:36:43.1685815Z only exactly one tensor is stored in this bucket. 2025-07-17T07:36:43.1686091Z 2025-07-17T07:36:43.1686175Z Returns: 2025-07-17T07:36:43.1686544Z Future handler of the communication, which updates the gradients in place. 2025-07-17T07:36:43.1686905Z 2025-07-17T07:36:43.1687027Z Example:: 2025-07-17T07:36:43.1687244Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.1687674Z >>> state = PostLocalSGDState(process_group=process_group, subgroup=subgroup, 2025-07-17T07:36:43.1688174Z start_localSGD_iter=10) 2025-07-17T07:36:43.1688571Z >>> ddp_model.register_comm_hook(state, post_localSGD_hook) 2025-07-17T07:36:43.1689388Z >>> # Also need to establish a model averaging module and run model averaging after ``optimizer.step()``. 2025-07-17T07:36:43.1690197Z >>> # Please refer to the examples in ``torch.distributed.algorithms.model_averaging.averagers`` module. 2025-07-17T07:36:43.1690658Z 2025-07-17T07:36:43.1690924Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.1691294Z 2025-07-17T07:36:43.1732829Z msg = Cannot scrape callname=powerSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py line=342. 2025-07-17T07:36:43.1734039Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.1734428Z 2025-07-17T07:36:43.1734579Z Implement PowerSGD algorithm. 2025-07-17T07:36:43.1734771Z 2025-07-17T07:36:43.1735028Z This DDP communication hook implements PowerSGD gradient compression 2025-07-17T07:36:43.1735628Z algorithm described in the `paper `_. 2025-07-17T07:36:43.1736202Z Once gradient tensors are aggregated across all workers, this hook applies 2025-07-17T07:36:43.1736661Z compression as follows: 2025-07-17T07:36:43.1736824Z 2025-07-17T07:36:43.1737277Z 1. Views the input flattened 1D gradient tensor as a list of per-parameter tensors, and divides all the tensors into two groups: 2025-07-17T07:36:43.1737830Z 2025-07-17T07:36:43.1738258Z 1.1 The tensors that should be compressed before allreduce, because the compression can give enough saving in bandwidth. 2025-07-17T07:36:43.1738791Z 2025-07-17T07:36:43.1739199Z 1.2 Rest of the tensors will be directly allreduced without compression, including all the vector tensors (for biases). 2025-07-17T07:36:43.1739738Z 2025-07-17T07:36:43.1739844Z 2. Handles uncompressed tensors: 2025-07-17T07:36:43.1740037Z 2025-07-17T07:36:43.1740563Z 2.1. Allocate contiguous memory for those uncompressed tensors, and allreduces all the uncompressed tensors as a batch, without compression; 2025-07-17T07:36:43.1741196Z 2025-07-17T07:36:43.1741546Z 2.2. Copies the individual uncompressed tensors from the contiguous memory back to the input tensor. 2025-07-17T07:36:43.1742022Z 2025-07-17T07:36:43.1742265Z 3. Handles the tensors that should be compressed by PowerSGD compression: 2025-07-17T07:36:43.1742613Z 2025-07-17T07:36:43.1742847Z 3.1. For each tensor M, creates two low-rank tensors P and Q for decomposing M, 2025-07-17T07:36:43.1743524Z such that M = PQ^T, where Q is initialized from a standard normal distribution and orthogonalized; 2025-07-17T07:36:43.1743945Z 2025-07-17T07:36:43.1744105Z 3.2. Computes each P in Ps, which is equal to MQ; 2025-07-17T07:36:43.1744358Z 2025-07-17T07:36:43.1744473Z 3.3. Allreduces Ps as a batch; 2025-07-17T07:36:43.1744670Z 2025-07-17T07:36:43.1744785Z 3.4. Orthogonalizes each P in Ps; 2025-07-17T07:36:43.1745006Z 2025-07-17T07:36:43.1745198Z 3.5. Computes each Q in Qs, which is approximately equal to M^TP; 2025-07-17T07:36:43.1745511Z 2025-07-17T07:36:43.1745629Z 3.6. Allreduces Qs as a batch; 2025-07-17T07:36:43.1745822Z 2025-07-17T07:36:43.1746128Z 3.7. Computes each M among all the compressed tensors, which is approximately equal to PQ^T. 2025-07-17T07:36:43.1746541Z 2025-07-17T07:36:43.1747007Z Note that this communication hook enforces vanilla allreduce for the first ``state.start_powerSGD_iter`` iterations. 2025-07-17T07:36:43.1747851Z This not only gives the user more control over the tradeoff between speedup and accuracy, 2025-07-17T07:36:43.1748688Z but also helps abstract away some complexity of the internal optimization of DDP for future communication hook developers. 2025-07-17T07:36:43.1749235Z 2025-07-17T07:36:43.1749329Z Args: 2025-07-17T07:36:43.1749864Z state (PowerSGDState): State information to configure the compression rate and support error feedback, warm start, etc. 2025-07-17T07:36:43.1750775Z To tune the compression configs, mainly need to tune ``matrix_approximation_rank``, ``start_powerSGD_iter`` 2025-07-17T07:36:43.1751443Z and ``min_compression_rate``. 2025-07-17T07:36:43.1752063Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-07-17T07:36:43.1752854Z Note that since DDP comm hook only supports single process single device mode, 2025-07-17T07:36:43.1753380Z only exactly one tensor is stored in this bucket. 2025-07-17T07:36:43.1753639Z 2025-07-17T07:36:43.1753736Z Returns: 2025-07-17T07:36:43.1754091Z Future handler of the communication, which updates the gradients in place. 2025-07-17T07:36:43.1754465Z 2025-07-17T07:36:43.1754667Z Example:: 2025-07-17T07:36:43.1754895Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.1755330Z >>> state = PowerSGDState(process_group=process_group, matrix_approximation_rank=1, 2025-07-17T07:36:43.1755890Z start_powerSGD_iter=10, min_compression_rate=0.5) 2025-07-17T07:36:43.1756339Z >>> ddp_model.register_comm_hook(state, powerSGD_hook) 2025-07-17T07:36:43.1756605Z 2025-07-17T07:36:43.1756868Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.1757232Z 2025-07-17T07:36:43.1784399Z msg = Cannot scrape callname=PeriodicModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/averagers.py line=38. 2025-07-17T07:36:43.1785516Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.1785904Z 2025-07-17T07:36:43.1786095Z Averages parameters periodically after the warm-up stage. 2025-07-17T07:36:43.1786388Z 2025-07-17T07:36:43.1786668Z This can be used for running `post-local SGD `_, 2025-07-17T07:36:43.1787230Z by running :class:`~torch.nn.DistributedDataParallel` (DDP) 2025-07-17T07:36:43.1787758Z using the subgroups created by :meth:`~torch.distributed.new_subgroups`. 2025-07-17T07:36:43.1788123Z 2025-07-17T07:36:43.1788205Z Args: 2025-07-17T07:36:43.1788487Z period (int): The number of steps per model averaging. 2025-07-17T07:36:43.1789022Z Usually the period should be greater than ``1`` to reduce the communication cost. 2025-07-17T07:36:43.1789537Z Otherwise, only DDP needs to be used. 2025-07-17T07:36:43.1789983Z warmup_steps (int): The number of warm-up steps. During this stage, 2025-07-17T07:36:43.1790414Z model averaging is skipped. 2025-07-17T07:36:43.1790847Z process_group: The process group to be used for all-reduce. 2025-07-17T07:36:43.1791292Z If ``None``, the default process group, which 2025-07-17T07:36:43.1791738Z is created by :func:`torch.distributed.init_process_group`, 2025-07-17T07:36:43.1792149Z will be used. (default: ``None``) 2025-07-17T07:36:43.1792386Z 2025-07-17T07:36:43.1792478Z Example:: 2025-07-17T07:36:43.1792612Z 2025-07-17T07:36:43.1792732Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:43.1793059Z >>> import torch 2025-07-17T07:36:43.1793312Z >>> import torch.distributed as dist 2025-07-17T07:36:43.1793847Z >>> import torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook as post_localSGD 2025-07-17T07:36:43.1794552Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-07-17T07:36:43.1795032Z >>> import torch.nn as nn 2025-07-17T07:36:43.1795303Z >>> 2025-07-17T07:36:43.1795599Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-07-17T07:36:43.1796002Z >>> torch.cuda.set_device(rank) 2025-07-17T07:36:43.1796324Z >>> module = nn.Linear(1, 1, bias=False).cuda() 2025-07-17T07:36:43.1796722Z >>> model = nn.parallel.DistributedDataParallel( 2025-07-17T07:36:43.1797128Z >>> module, device_ids=[rank], output_device=rank 2025-07-17T07:36:43.1797452Z >>> ) 2025-07-17T07:36:43.1797719Z >>> # Register a post-localSGD communication hook. 2025-07-17T07:36:43.1798429Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-07-17T07:36:43.1798995Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-07-17T07:36:43.1799354Z >>> 2025-07-17T07:36:43.1799736Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-07-17T07:36:43.1800281Z >>> # After 100 steps, run model averaging every 4 steps. 2025-07-17T07:36:43.1800853Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-07-17T07:36:43.1801611Z >>> averager = averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-07-17T07:36:43.1802086Z >>> for step in range(0, 200): 2025-07-17T07:36:43.1802380Z >>> optimizer.zero_grad() 2025-07-17T07:36:43.1802688Z >>> loss = loss_fn(output, labels) 2025-07-17T07:36:43.1803007Z >>> loss.backward() 2025-07-17T07:36:43.1803274Z >>> optimizer.step() 2025-07-17T07:36:43.1803669Z >>> # Will average model parameters globally every 4 steps. Thus, 2025-07-17T07:36:43.1804463Z >>> # inter-node communication only occurs every 4 iterations after 2025-07-17T07:36:43.1805019Z >>> # the initial ``warmup_steps`` period. 2025-07-17T07:36:43.1805807Z >>> averager.average_parameters(model.parameters()) 2025-07-17T07:36:43.1806353Z 2025-07-17T07:36:43.1806683Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.1807051Z 2025-07-17T07:36:43.1807971Z msg = Cannot scrape callname=HierarchicalModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/hierarchical_model_averager.py line=19. 2025-07-17T07:36:43.1809204Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.1809581Z 2025-07-17T07:36:43.1809931Z Runs hierarchical model averaging (`hierarchical SGD `_). 2025-07-17T07:36:43.1810388Z 2025-07-17T07:36:43.1810693Z Process groups of different sizes are organized in a hierarchy, and they average parameters 2025-07-17T07:36:43.1811326Z by using different periods concurrently after the warm-up stage. 2025-07-17T07:36:43.1812054Z This is an extension of :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager` 2025-07-17T07:36:43.1812919Z that supports `post-local SGD `_, which essentially only supports 2025-07-17T07:36:43.1813670Z a two-level hierarchy: the intra-machine level and the global level, where the intra-machine 2025-07-17T07:36:43.1814449Z level is usually embedded in :meth:`~torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook`. 2025-07-17T07:36:43.1815215Z Similarly, the process groups within this class do not have such an intra-machine process 2025-07-17T07:36:43.1815909Z subgroup, which should be embedded by the post-local SGD communication hook instead. 2025-07-17T07:36:43.1816307Z 2025-07-17T07:36:43.1816387Z Args: 2025-07-17T07:36:43.1816767Z period_group_size_dict: An ordered dict mapping keys of model averaging period to 2025-07-17T07:36:43.1817352Z process group size, used for initializing process groups of 2025-07-17T07:36:43.1817879Z different sizes in a hierarchy to average parameters concurrently. 2025-07-17T07:36:43.1818436Z Particularly, at each iteration, there will be at most a single 2025-07-17T07:36:43.1819000Z process group that runs averaging -- the period of such group should 2025-07-17T07:36:43.1819560Z have the largest period which the current step can be divided by. 2025-07-17T07:36:43.1820045Z For example, if the dict has three keys: 2, 4, and 8, 2025-07-17T07:36:43.1820534Z then this means totally three process groups will be created to 2025-07-17T07:36:43.1821168Z average parameters every 2, 4, and 8 iterations, respectively. 2025-07-17T07:36:43.1821684Z At the 4th iteration, only the second process group will run 2025-07-17T07:36:43.1822158Z averaging, because the first process group should be a 2025-07-17T07:36:43.1822677Z subset of the second process group, and no need to execute the first 2025-07-17T07:36:43.1823143Z process group redundantly. 2025-07-17T07:36:43.1823564Z On the other hand, the third process group can only be triggered 2025-07-17T07:36:43.1824166Z every 8 iterations, so it will not be triggered at the 4th iteration. 2025-07-17T07:36:43.1824822Z warmup_steps (int): The number of warm-up steps. During this stage, model averaging is skipped. 2025-07-17T07:36:43.1825696Z process_group (ProcessGroup, optional): The overall process group containing all the processes that runs model averaging. 2025-07-17T07:36:43.1826425Z If ``None``, the default process group, which is created 2025-07-17T07:36:43.1826928Z by :func:`torch.distributed.init_process_group`, will be used. 2025-07-17T07:36:43.1827379Z (default: ``None``) 2025-07-17T07:36:43.1827609Z 2025-07-17T07:36:43.1827717Z Example:: 2025-07-17T07:36:43.1827947Z >>> # xdoctest: +SKIP('undefined rank') 2025-07-17T07:36:43.1828295Z >>> from collections import OrderedDict 2025-07-17T07:36:43.1828618Z >>> import torch 2025-07-17T07:36:43.1828882Z >>> import torch.distributed as dist 2025-07-17T07:36:43.1829383Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-07-17T07:36:43.1829889Z >>> PostLocalSGDState, 2025-07-17T07:36:43.1830170Z >>> post_localSGD_hook, 2025-07-17T07:36:43.1830448Z >>> ) 2025-07-17T07:36:43.1830948Z >>> import torch.distributed.algorithms.model_averaging.hierarchical_model_averager as hierarchicalSGD 2025-07-17T07:36:43.1831559Z >>> import torch.nn as nn 2025-07-17T07:36:43.1831819Z >>> 2025-07-17T07:36:43.1832113Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-07-17T07:36:43.1832516Z >>> torch.cuda.set_device(rank) 2025-07-17T07:36:43.1832845Z >>> module = nn.Linear(1, 1, bias=False).to(rank) 2025-07-17T07:36:43.1833249Z >>> model = nn.parallel.DistributedDataParallel( 2025-07-17T07:36:43.1833651Z >>> module, device_ids=[rank], output_device=rank 2025-07-17T07:36:43.1833971Z >>> ) 2025-07-17T07:36:43.1834241Z >>> # Register a post-localSGD communication hook. 2025-07-17T07:36:43.1834766Z >>> # Assume that each machine has 4 GPUs, then each intra-machine subgroup has a size of 4. 2025-07-17T07:36:43.1835281Z >>> subgroup, _ = dist.new_subgroups() 2025-07-17T07:36:43.1835811Z >>> state = PostLocalSGDState(process_group=None, subgroup=subgroup, start_localSGD_iter=100) 2025-07-17T07:36:43.1836403Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-07-17T07:36:43.1836767Z >>> 2025-07-17T07:36:43.1837152Z >>> # Average parameters among each group of 8 processes every 4 iterations, and among all 2025-07-17T07:36:43.1837671Z >>> # the 16 processes every 16 iterations. 2025-07-17T07:36:43.1838086Z >>> averager = hierarchicalSGD.HierarchicalModelAverager( 2025-07-17T07:36:43.1838606Z >>> period_group_size_dict=OrderedDict([(4, 8), (16, 16)]), warmup_steps=100) 2025-07-17T07:36:43.1839274Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-07-17T07:36:43.1839973Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-07-17T07:36:43.1840516Z >>> # After 100 steps, run model averaging at two levels. 2025-07-17T07:36:43.1840939Z >>> for step in range(0, 200): 2025-07-17T07:36:43.1841248Z >>> optimizer.zero_grad() 2025-07-17T07:36:43.1841552Z >>> loss = loss_fn(output, labels) 2025-07-17T07:36:43.1841855Z >>> loss.backward() 2025-07-17T07:36:43.1842125Z >>> optimizer.step() 2025-07-17T07:36:43.1842459Z >>> # Average parameters after ``optimizer.step()``. 2025-07-17T07:36:43.1843012Z >>> # Thus, the inter-node communication only occurs periodically after ``warmup_steps``. 2025-07-17T07:36:43.1843564Z >>> averager.average_parameters(model.parameters()) 2025-07-17T07:36:43.1843846Z 2025-07-17T07:36:43.1843937Z .. warning :: 2025-07-17T07:36:43.1844407Z The last group size in the dict must be the size of the provided ``process_group``, 2025-07-17T07:36:43.1845006Z which indicates model averaging at the highest level of the hierarchy. 2025-07-17T07:36:43.1845753Z If ``process_group`` is not provided, then the last group size should be equal to the world size. 2025-07-17T07:36:43.1846187Z 2025-07-17T07:36:43.1846275Z .. warning :: 2025-07-17T07:36:43.1846643Z `HierarchicalModelAverager` is experimental and subject to change. 2025-07-17T07:36:43.1846989Z 2025-07-17T07:36:43.1847236Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.1847613Z 2025-07-17T07:36:43.2325773Z msg = Cannot scrape callname=BroadcastingTorchSaveReader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=40. 2025-07-17T07:36:43.2326870Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.2327260Z 2025-07-17T07:36:43.2327560Z StorageReader for reading a Torch Save file. This reader will read the entire checkpoint 2025-07-17T07:36:43.2328502Z on the coordinator rank, and then broadcast and shard each tensor to all ranks. 2025-07-17T07:36:43.2328993Z 2025-07-17T07:36:43.2329292Z . N.B. Intended to be used with DynamicMetaLoadPlanner 2025-07-17T07:36:43.2329817Z 2025-07-17T07:36:43.2329981Z .. warning:: 2025-07-17T07:36:43.2330300Z Current implementation only supports loading Tensors. 2025-07-17T07:36:43.2330591Z 2025-07-17T07:36:43.2330703Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:43.2331018Z >>> sd = {"mode": model} 2025-07-17T07:36:43.2331264Z >>> dcp.load( 2025-07-17T07:36:43.2331524Z >>> sd, 2025-07-17T07:36:43.2331824Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-07-17T07:36:43.2332203Z >>> planner=DynamicMetaLoadPlanner(), 2025-07-17T07:36:43.2332546Z >>> checkpoint_id="path_to_model.pt" 2025-07-17T07:36:43.2332847Z >>> ) 2025-07-17T07:36:43.2332958Z 2025-07-17T07:36:43.2333221Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.2333601Z 2025-07-17T07:36:43.2334302Z msg = Cannot scrape callname=DynamicMetaLoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=151. 2025-07-17T07:36:43.2335368Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.2335744Z 2025-07-17T07:36:43.2336119Z Extension of DefaultLoadPlanner, which creates a new Metadata object based on the passed in state dict, 2025-07-17T07:36:43.2336927Z avoiding the need to read metadata from disk. This is useful when reading formats which don't have a 2025-07-17T07:36:43.2337478Z metadata file, like Torch Save files. 2025-07-17T07:36:43.2337702Z 2025-07-17T07:36:43.2337881Z . N.B. Intended to be used with BroadcastingTorchSaveReader 2025-07-17T07:36:43.2338168Z 2025-07-17T07:36:43.2338270Z .. warning:: 2025-07-17T07:36:43.2338560Z Current implementation only supports loading Tensors. 2025-07-17T07:36:43.2338857Z 2025-07-17T07:36:43.2338968Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:43.2339282Z >>> sd = {"mode": model} 2025-07-17T07:36:43.2339532Z >>> dcp.load( 2025-07-17T07:36:43.2339736Z >>> sd, 2025-07-17T07:36:43.2340006Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-07-17T07:36:43.2340585Z >>> planner=DynamicMetaLoadPlanner(), 2025-07-17T07:36:43.2340919Z >>> checkpoint_id="path_to_model.pt" 2025-07-17T07:36:43.2341224Z >>> ) 2025-07-17T07:36:43.2341335Z 2025-07-17T07:36:43.2341598Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.2341968Z 2025-07-17T07:36:43.2433615Z msg = Cannot scrape callname=load_sharded_optimizer_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/optimizer.py line=221. 2025-07-17T07:36:43.2434714Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.2435101Z 2025-07-17T07:36:43.2435427Z Load a state_dict in conjunction with FSDP sharded optimizer state. 2025-07-17T07:36:43.2435762Z 2025-07-17T07:36:43.2435920Z This is the current recommended way to checkpoint FSDP. 2025-07-17T07:36:43.2436294Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.2436591Z >>> import torch.distributed.checkpoint as dist_cp 2025-07-17T07:36:43.2436942Z >>> # Save 2025-07-17T07:36:43.2437167Z >>> model: torch.nn.Model 2025-07-17T07:36:43.2437442Z >>> optim_params = model.parameters() 2025-07-17T07:36:43.2437800Z >>> optim = torch.optim.SGD(optim_params, lr=0.01) 2025-07-17T07:36:43.2438138Z >>> # Save 2025-07-17T07:36:43.2438462Z >>> with FSDP.state_dict_type(model, StateDictType.SHARDED_STATE_DICT): 2025-07-17T07:36:43.2438885Z >>> state_dict = { 2025-07-17T07:36:43.2439194Z >>> "optimizer": FSDP.optim_state_dict(model, optim), 2025-07-17T07:36:43.2439573Z >>> "model": model.state_dict() 2025-07-17T07:36:43.2439855Z >>> } 2025-07-17T07:36:43.2440074Z >>> dist_cp.save_state_dict( 2025-07-17T07:36:43.2440372Z >>> state_dict=optim_state, 2025-07-17T07:36:43.2440737Z >>> storage_writer=dist_cp.FileSystemWriter("checkpoint"), 2025-07-17T07:36:43.2441160Z >>> planner=dist_cp.DefaultSavePlanner(), 2025-07-17T07:36:43.2441488Z >>> ) 2025-07-17T07:36:43.2441682Z >>> 2025-07-17T07:36:43.2441880Z >>> # Load 2025-07-17T07:36:43.2442254Z >>> with FSDP.state_dict_type(model_tp, StateDictType.SHARDED_STATE_DICT): 2025-07-17T07:36:43.2442716Z >>> model_state_dict = model_tp.state_dict() 2025-07-17T07:36:43.2443049Z >>> checkpoint = { 2025-07-17T07:36:43.2443312Z >>> "model": model_state_dict 2025-07-17T07:36:43.2443588Z >>> } 2025-07-17T07:36:43.2443809Z >>> dist_cp.load_state_dict( 2025-07-17T07:36:43.2444117Z >>> state_dict=checkpoint, 2025-07-17T07:36:43.2444503Z >>> storage_reader=dist_cp.FileSystemReader(checkpoint_file), 2025-07-17T07:36:43.2444926Z >>> planner=dist_cp.DefaultLoadPlanner(), 2025-07-17T07:36:43.2445252Z >>> ) 2025-07-17T07:36:43.2445617Z >>> model.load_state_dict(checkpoint["model_state"]) 2025-07-17T07:36:43.2445954Z >>> 2025-07-17T07:36:43.2446249Z >>> optim_state = dist_cp.load_sharded_optimizer_state_dict( 2025-07-17T07:36:43.2446639Z >>> model_state_dict, 2025-07-17T07:36:43.2446924Z >>> optimizer_key="optimizer", 2025-07-17T07:36:43.2447324Z >>> storage_reader=dist_cp.FileSystemReader("checkpoint"), 2025-07-17T07:36:43.2447699Z >>> ) 2025-07-17T07:36:43.2447885Z >>> 2025-07-17T07:36:43.2448141Z >>> flattened_osd = FSDP.optim_state_dict_to_load( 2025-07-17T07:36:43.2448518Z >>> model, optim, optim_state["optimizer"] 2025-07-17T07:36:43.2448837Z >>> ) 2025-07-17T07:36:43.2449023Z >>> 2025-07-17T07:36:43.2449254Z >>> optim.load_state_dict(flattened_osd) 2025-07-17T07:36:43.2449477Z 2025-07-17T07:36:43.2449737Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.2450102Z 2025-07-17T07:36:43.2464994Z msg = Cannot scrape callname=SavePlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=122. 2025-07-17T07:36:43.2466171Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.2466561Z 2025-07-17T07:36:43.2466993Z Abstract class defining the protocol used by save_state_dict to plan the save process. 2025-07-17T07:36:43.2467413Z 2025-07-17T07:36:43.2467703Z SavePlanners are stateful objects that can be used to customize the whole save process. 2025-07-17T07:36:43.2468116Z 2025-07-17T07:36:43.2468405Z SavePlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-07-17T07:36:43.2480040Z will be visible to the whole process. 2025-07-17T07:36:43.2480470Z 2025-07-17T07:36:43.2480978Z A planner subclass can expect the following sequence of calls during save_state_dict: 2025-07-17T07:36:43.2481667Z 2025-07-17T07:36:43.2481806Z 1) set_up_planner - called on all ranks. 2025-07-17T07:36:43.2482306Z Signals the start of a checkpoint save. 2025-07-17T07:36:43.2482552Z 2025-07-17T07:36:43.2482673Z 2) create_local_plan - called on all ranks. 2025-07-17T07:36:43.2483194Z Process the state_dict and produces a `SavePlan` that will be sent for global planning. 2025-07-17T07:36:43.2483604Z 2025-07-17T07:36:43.2483785Z 3) create_global_plan - called on the coordinator rank only. 2025-07-17T07:36:43.2484284Z Takes the SavePlan from all ranks and make any global decision. 2025-07-17T07:36:43.2484607Z 2025-07-17T07:36:43.2484716Z 4) finish_plan - called on all ranks. 2025-07-17T07:36:43.2485147Z This gives each rank a chance to adjust to global planning decisions. 2025-07-17T07:36:43.2485557Z 2025-07-17T07:36:43.2485708Z 5) resolve_data - called multiple times on each rank 2025-07-17T07:36:43.2486175Z Lookups a value on the `state_dict` for the storage layer to write. 2025-07-17T07:36:43.2486492Z 2025-07-17T07:36:43.2486818Z Users are recommended to extend DefaultSavePlanner instead of this interface directly as 2025-07-17T07:36:43.2487482Z most changes can be expressed by changes in a single method. 2025-07-17T07:36:43.2487772Z 2025-07-17T07:36:43.2487890Z There are 3 usual patterns of extension: 2025-07-17T07:36:43.2488126Z 2025-07-17T07:36:43.2488381Z Rewriting state_dict. This is the simplest way to extend the save process as it 2025-07-17T07:36:43.2488988Z doesn't requite understanding the intrincacies of how SavePlan works: 2025-07-17T07:36:43.2489327Z 2025-07-17T07:36:43.2489438Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:43.2489791Z >>> class RenamePlanner(DefaultSavePlanner): 2025-07-17T07:36:43.2490132Z >>> def set_up_planner( 2025-07-17T07:36:43.2490398Z >>> self, 2025-07-17T07:36:43.2490633Z >>> state_dict: STATE_DICT_TYPE, 2025-07-17T07:36:43.2490978Z >>> storage_meta: Optional[StorageMeta], 2025-07-17T07:36:43.2491321Z >>> is_coordinator: bool, 2025-07-17T07:36:43.2491592Z >>> ) -> None: 2025-07-17T07:36:43.2491862Z >>> # prefix all keys with `foo_`` 2025-07-17T07:36:43.2492352Z >>> super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator) 2025-07-17T07:36:43.2492753Z 2025-07-17T07:36:43.2493083Z Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted 2025-07-17T07:36:43.2493546Z 2025-07-17T07:36:43.2493658Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:43.2494001Z >>> class FP16Planner(DefaultSavePlanner): 2025-07-17T07:36:43.2494341Z >>> def create_local_plan(self): 2025-07-17T07:36:43.2494652Z >>> plan = super().create_local_plan() 2025-07-17T07:36:43.2494978Z >>> for p in plan: 2025-07-17T07:36:43.2495271Z >>> if p.tensor_data is not None: 2025-07-17T07:36:43.2495641Z >>> p.tensor_data.properties.dtype = torch.float16 2025-07-17T07:36:43.2496007Z >>> return plan 2025-07-17T07:36:43.2496254Z >>> 2025-07-17T07:36:43.2496476Z >>> def resolve_data(self, write_item): 2025-07-17T07:36:43.2496824Z >>> item = super().resolve_data(write_item) 2025-07-17T07:36:43.2497341Z >>> return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16) 2025-07-17T07:36:43.2497728Z 2025-07-17T07:36:43.2498080Z Using the global planning step to make central decisions that can't be made individually by each rank 2025-07-17T07:36:43.2498639Z 2025-07-17T07:36:43.2498750Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:43.2499088Z >>> from itertools import zip_longest 2025-07-17T07:36:43.2499413Z >>> from dataclasses import replace 2025-07-17T07:36:43.2499783Z >>> class DDPLoadBalancingPlanner(DefaultSavePlanner): 2025-07-17T07:36:43.2500337Z >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0 2025-07-17T07:36:43.2500924Z >>> # This sample doesn't handle ShardedTensors 2025-07-17T07:36:43.2501294Z >>> def create_global_plan(self, all_plans): 2025-07-17T07:36:43.2501745Z >>> iters = [iter(all_plans[0].items)] * len(all_plans) 2025-07-17T07:36:43.2502112Z >>> items_per_rank = [ 2025-07-17T07:36:43.2502436Z >>> [item for item in items if item is not None] 2025-07-17T07:36:43.2502834Z >>> for items in zip(*zip_longest(*iters), strict=True) 2025-07-17T07:36:43.2503204Z >>> ] 2025-07-17T07:36:43.2503466Z >>> all_plans = [ 2025-07-17T07:36:43.2503728Z >>> replace(plan, items=items) 2025-07-17T07:36:43.2504135Z >>> for plan, items in zip(all_plans, items_per_rank, strict=True) 2025-07-17T07:36:43.2504532Z >>> ] 2025-07-17T07:36:43.2504804Z >>> return super().create_global_plan(all_plans) 2025-07-17T07:36:43.2505051Z 2025-07-17T07:36:43.2505313Z Finally, some planners need to save additional metadata in the checkpoint, this is 2025-07-17T07:36:43.2505972Z accomplished by having each rank contribute their data items in the local plan and 2025-07-17T07:36:43.2506476Z the global planner aggregate them: 2025-07-17T07:36:43.2506683Z 2025-07-17T07:36:43.2506795Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:43.2507168Z >>> class SaveExtraDataPlanner(DefaultSavePlanner): 2025-07-17T07:36:43.2507566Z >>> def create_local_plan(self) -> SavePlan: 2025-07-17T07:36:43.2507928Z >>> plan = super().create_local_plan() 2025-07-17T07:36:43.2508313Z >>> return replace(plan, planner_data="per-rank-data") 2025-07-17T07:36:43.2508680Z >>> 2025-07-17T07:36:43.2509091Z >>> def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]: 2025-07-17T07:36:43.2509697Z >>> global_plan, metadata = super().create_global_plan(all_plans) 2025-07-17T07:36:43.2510254Z >>> merged_data = [p.planner_data for p in global_plan] 2025-07-17T07:36:43.2510699Z >>> metadata = replace(metadata, planner_data=merged_data) 2025-07-17T07:36:43.2511084Z >>> return global_plan, metadata 2025-07-17T07:36:43.2511307Z 2025-07-17T07:36:43.2511560Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.2511939Z 2025-07-17T07:36:43.2512569Z msg = Cannot scrape callname=LoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=305. 2025-07-17T07:36:43.2513550Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.2513926Z 2025-07-17T07:36:43.2514222Z Abstract class defining the protocol used by load_state_dict to plan the load process. 2025-07-17T07:36:43.2514626Z 2025-07-17T07:36:43.2514923Z LoadPlanner are stateful objects that can be used to customize the whole load process. 2025-07-17T07:36:43.2515331Z 2025-07-17T07:36:43.2515605Z LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-07-17T07:36:43.2516118Z will be visible to the whole process. 2025-07-17T07:36:43.2516329Z 2025-07-17T07:36:43.2516613Z A planner subclass can expect the following sequence of calls during load_state_dict: 2025-07-17T07:36:43.2517014Z 2025-07-17T07:36:43.2517143Z 1) set_up_planner - called on all ranks. 2025-07-17T07:36:43.2517479Z Signals the start of loading a checkpoint. 2025-07-17T07:36:43.2517727Z 2025-07-17T07:36:43.2517841Z 2) create_local_plan - called on all ranks. 2025-07-17T07:36:43.2518423Z Process the state_dict and produces a `LoadPlan` that will be sent for global planning. 2025-07-17T07:36:43.2518826Z 2025-07-17T07:36:43.2519005Z 3) create_global_plan - called on the coordinator rank only. 2025-07-17T07:36:43.2519497Z Takes the LoadPlan from all ranks and make any global decision. 2025-07-17T07:36:43.2519819Z 2025-07-17T07:36:43.2519958Z 4) load_bytes - called multiple times on each rank 2025-07-17T07:36:43.2520386Z This is called once per non-tensor value in state_dict. 2025-07-17T07:36:43.2520663Z 2025-07-17T07:36:43.2520882Z 5) resolve_tensor and commit_tensor - called multiple times on each rank 2025-07-17T07:36:43.2521465Z They are called in pair for each Tensor value in state_dict. 2025-07-17T07:36:43.2521770Z 2025-07-17T07:36:43.2522069Z Users are recommended to extend DefaultLoadPlanner instead of this interface directly as 2025-07-17T07:36:43.2522676Z most changes can be expressed by changes in a single method. 2025-07-17T07:36:43.2522967Z 2025-07-17T07:36:43.2523096Z There are two usual patterns of extension: 2025-07-17T07:36:43.2523340Z 2025-07-17T07:36:43.2523590Z Rewriting state_dict. This is the simplest way to extend the load process as it 2025-07-17T07:36:43.2524223Z doesn't requite understanding the intrincacies of how LoadPlan works. We need 2025-07-17T07:36:43.2524829Z to keep a reference to the original state_dict as load happens in place so 2025-07-17T07:36:43.2525286Z we need to be able to perform it in place 2025-07-17T07:36:43.2525608Z 2025-07-17T07:36:43.2525723Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:43.2526075Z >>> class RenamePlanner(DefaultLoadPlanner): 2025-07-17T07:36:43.2526403Z >>> def set_up_planner( 2025-07-17T07:36:43.2526676Z >>> self, 2025-07-17T07:36:43.2526927Z >>> state_dict: STATE_DICT_TYPE, 2025-07-17T07:36:43.2527230Z >>> metadata: Metadata, 2025-07-17T07:36:43.2527524Z >>> is_coordinator: bool, 2025-07-17T07:36:43.2527867Z >>> ) -> None: 2025-07-17T07:36:43.2528122Z >>> self.original_state_dict = state_dict 2025-07-17T07:36:43.2528533Z >>> state_dict = {"foo_" + k: v for k, v in state_dict.items()} 2025-07-17T07:36:43.2528906Z >>> 2025-07-17T07:36:43.2529137Z >>> if self.flatten_sharded_tensors: 2025-07-17T07:36:43.2529502Z >>> state_dict = _flatten_sharded_tensors(state_dict) 2025-07-17T07:36:43.2529852Z >>> 2025-07-17T07:36:43.2530073Z >>> if self.flatten_state_dict: 2025-07-17T07:36:43.2530459Z >>> state_dict, self.mappings = flatten_state_dict(state_dict) 2025-07-17T07:36:43.2530848Z >>> 2025-07-17T07:36:43.2531072Z >>> self.state_dict = state_dict 2025-07-17T07:36:43.2531382Z >>> self.metadata = metadata 2025-07-17T07:36:43.2531717Z >>> self.is_coordinator = is_coordinator 2025-07-17T07:36:43.2532032Z >>> 2025-07-17T07:36:43.2532250Z >>> def load_bytes(self, read_item, value): 2025-07-17T07:36:43.2532581Z >>> # Remove the "foo_" prefix 2025-07-17T07:36:43.2533082Z >>> self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False) 2025-07-17T07:36:43.2533517Z 2025-07-17T07:36:43.2533521Z 2025-07-17T07:36:43.2533790Z Modifying resolve_tensor and commit_tensor to handle load time transformation. 2025-07-17T07:36:43.2534163Z 2025-07-17T07:36:43.2534272Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:43.2534644Z >>> class MetaModelMaterialize(DefaultSavePlanner): 2025-07-17T07:36:43.2535029Z >>> def resolve_tensor(self, read_item): 2025-07-17T07:36:43.2535373Z >>> tensor = super().resolve_tensor(read_item) 2025-07-17T07:36:43.2535762Z >>> return torch.empty_like(tensor, device="cpu") 2025-07-17T07:36:43.2536102Z >>> 2025-07-17T07:36:43.2536346Z >>> def commit_tensor(self, read_item, tensor): 2025-07-17T07:36:43.2536732Z >>> self.state_dict[read_item.dest_index.fqn] = tensor 2025-07-17T07:36:43.2537014Z 2025-07-17T07:36:43.2537261Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.2537705Z 2025-07-17T07:36:43.2663623Z msg = Cannot scrape callname=get_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict.py line=1118. 2025-07-17T07:36:43.2664718Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.2665161Z 2025-07-17T07:36:43.2665323Z Return the model state_dict and optimizers state_dict. 2025-07-17T07:36:43.2665672Z 2025-07-17T07:36:43.2665892Z ``get_state_dict`` can process any module that is parallelized by PyTorch 2025-07-17T07:36:43.2666559Z FSDP/fully_shard, DDP/replicate, tensor_parallel/parallelize_module, and any 2025-07-17T07:36:43.2667377Z combination of these parallelisms. The main functions of ``get_state_dict`` 2025-07-17T07:36:43.2668020Z are: 1.) returning a model and optimizer state_dict that can be resharded 2025-07-17T07:36:43.2668583Z with a different number of trainers and/or different parallelisms. 2025-07-17T07:36:43.2669237Z 2.) hiding the parallelism-specific state_dict APIs. Users don't have to call 2025-07-17T07:36:43.2669764Z these APIs. 2025-07-17T07:36:43.2670142Z 3.) sanity checking the result state_dict. 2025-07-17T07:36:43.2670442Z 2025-07-17T07:36:43.2670661Z The keys of the result state dictionary are the canonical FQNs (Fully 2025-07-17T07:36:43.2671306Z Qualified Names). A canonical FQN refers to the FQN based on a parameter's 2025-07-17T07:36:43.2671950Z position in an nn.Module hierarchy. More specifically, a canonical FQN to a 2025-07-17T07:36:43.2672519Z parameter is the FQN returned by ``module.named_parameters()`` or 2025-07-17T07:36:43.2673112Z ``module.named_buffers()`` when the module is not distributed by any 2025-07-17T07:36:43.2673747Z parallelisms. Since the optimizer internally uses parameter IDs to represent 2025-07-17T07:36:43.2674401Z a parameter, there will be a conversion from the parameter IDs to the 2025-07-17T07:36:43.2674876Z canonical FQNs when calling this API. 2025-07-17T07:36:43.2675155Z 2025-07-17T07:36:43.2675388Z ``get_state_dict`` can also process a module that is not parallelized. In 2025-07-17T07:36:43.2675995Z such a case, ``get_state_dict`` only performs one function -- converting the 2025-07-17T07:36:43.2676500Z optimizer parameter IDs to the canonical FQNs. 2025-07-17T07:36:43.2676791Z 2025-07-17T07:36:43.2676887Z Example: 2025-07-17T07:36:43.2677092Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.2677473Z >>> import torch 2025-07-17T07:36:43.2677862Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-07-17T07:36:43.2678481Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-07-17T07:36:43.2679080Z >>> from torch.distributed.checkpoint.state_dict import get_state_dict 2025-07-17T07:36:43.2679430Z 2025-07-17T07:36:43.2679553Z >>> fsdp_model = FSDP(copy.deepcopy(model)) 2025-07-17T07:36:43.2680047Z >>> fsdp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-07-17T07:36:43.2680517Z >>> ddp_model = DDP(copy.deepcopy(model)) 2025-07-17T07:36:43.2680935Z >>> ddp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-07-17T07:36:43.2681292Z 2025-07-17T07:36:43.2681296Z 2025-07-17T07:36:43.2681529Z >>> ddp_state_dict, ddp_optim_state_dict = get_state_dict(ddp_model, ddp_optim) 2025-07-17T07:36:43.2682114Z >>> fsdp_state_dict, fsdp_optim_state_dict = get_state_dict( 2025-07-17T07:36:43.2682493Z ... fsdp_model, fsdp_optim 2025-07-17T07:36:43.2682838Z ... ) 2025-07-17T07:36:43.2682954Z 2025-07-17T07:36:43.2683175Z >>> # if we simply call ddp_model.state_dict() and fsdp_model.state_dict(), 2025-07-17T07:36:43.2683721Z >>> # the asserts will fail. 2025-07-17T07:36:43.2684044Z >>> assert ddp_state_dict == fsdp_state_dict 2025-07-17T07:36:43.2684495Z >>> assert ddp_optim_state == fsdp_optim_state_dict 2025-07-17T07:36:43.2684748Z 2025-07-17T07:36:43.2684752Z 2025-07-17T07:36:43.2684842Z Args: 2025-07-17T07:36:43.2685090Z model (nn.Module): the nn.Module to the model. 2025-07-17T07:36:43.2685766Z optimizers (Union[None, Optimizer, Iterable[Optimizer]]): 2025-07-17T07:36:43.2686295Z The optimizers that are used to optimize ``model``. 2025-07-17T07:36:43.2686897Z submodules (deprecated): Optional[set[nn.Module]]: only return the model parameters 2025-07-17T07:36:43.2687414Z that belong to the submodules. 2025-07-17T07:36:43.2687865Z options (StateDictOptions): the options to control how 2025-07-17T07:36:43.2688417Z model state_dict and optimizer state_dict should be returned. See 2025-07-17T07:36:43.2688852Z `StateDictOptions` for the details. 2025-07-17T07:36:43.2689147Z 2025-07-17T07:36:43.2689233Z Returns: 2025-07-17T07:36:43.2689630Z ``Tuple`` that contain model state_dict and optimizer state_dict. 2025-07-17T07:36:43.2690007Z 2025-07-17T07:36:43.2690232Z :rtype: typing.Tuple[typing.Dict[str, ValueType], OptimizerStateType] 2025-07-17T07:36:43.2690609Z 2025-07-17T07:36:43.2690899Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.2691286Z 2025-07-17T07:36:43.2701388Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_loader.py line=62. 2025-07-17T07:36:43.2702692Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.2703112Z 2025-07-17T07:36:43.2703318Z Load a checkpoint into a distributed state dict in SPMD style. 2025-07-17T07:36:43.2703619Z 2025-07-17T07:36:43.2703838Z Each rank must have the same keys in their ``state_dict`` provided to this 2025-07-17T07:36:43.2704410Z API. Mismatched keys may result in hangs or errors. If unsure, you can use 2025-07-17T07:36:43.2704986Z the ``utils._assert_same_keys`` API to check (but may incur communication 2025-07-17T07:36:43.2705396Z costs). 2025-07-17T07:36:43.2705521Z 2025-07-17T07:36:43.2705695Z Each rank will try to read the least amount of data necessary 2025-07-17T07:36:43.2706222Z to fulfill the requested `state_dict`. When loading :class:`ShardedTensor` 2025-07-17T07:36:43.2706821Z or :class:`DTensor` instances, each rank only reads data for their local shards. 2025-07-17T07:36:43.2707181Z 2025-07-17T07:36:43.2707434Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-07-17T07:36:43.2708071Z load will first call ``state_dict`` before attempting deserialization, followed by 2025-07-17T07:36:43.2708615Z ``load_state_dict`` once the deserialization is complete. 2025-07-17T07:36:43.2709151Z For each non-``Stateful`` object, load will deserialize the object, and then replace 2025-07-17T07:36:43.2709701Z it in the ``state_dict`` with the deserialized object. 2025-07-17T07:36:43.2709974Z 2025-07-17T07:36:43.2710078Z .. warning:: 2025-07-17T07:36:43.2710377Z All tensors in ``state_dict`` must be allocated on their 2025-07-17T07:36:43.2710807Z destination device *prior to* calling this function. 2025-07-17T07:36:43.2711087Z 2025-07-17T07:36:43.2711338Z All non-tensor data is loaded using `torch.load()` and modified in place 2025-07-17T07:36:43.2711781Z on state_dict. 2025-07-17T07:36:43.2711932Z 2025-07-17T07:36:43.2712016Z .. warning:: 2025-07-17T07:36:43.2712343Z Users must call `load_state_dict` on the root module to ensure load 2025-07-17T07:36:43.2712835Z pos-processing and non-tensor data properly propagates. 2025-07-17T07:36:43.2713135Z 2025-07-17T07:36:43.2713215Z .. note: 2025-07-17T07:36:43.2713557Z If no process group is initialized, this function will assume the intent 2025-07-17T07:36:43.2714114Z is to load a checkpoint into the local process. This can be useful in the 2025-07-17T07:36:43.2714703Z case of local inference, and when using regular Tensors (as opposed to DTensor 2025-07-17T07:36:43.2715164Z or ShardedTensor) 2025-07-17T07:36:43.2715318Z 2025-07-17T07:36:43.2715409Z .. note: 2025-07-17T07:36:43.2715666Z Rank 0 is assumed to be the coordinator rank. 2025-07-17T07:36:43.2715927Z 2025-07-17T07:36:43.2716114Z Args: 2025-07-17T07:36:43.2716449Z state_dict (Dict[str, Any]): The state_dict to load the checkpoint into. 2025-07-17T07:36:43.2716910Z checkpoint_id (Union[str, os.PathLike, None]): 2025-07-17T07:36:43.2717377Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-07-17T07:36:43.2717908Z depends on the storage. It can be a path to a folder or to a file. 2025-07-17T07:36:43.2718396Z It can also be a key if the storage is a key-value store. 2025-07-17T07:36:43.2718761Z (Default: ``None``) 2025-07-17T07:36:43.2719069Z storage_reader (Optional[StorageReader]): 2025-07-17T07:36:43.2719585Z Instance of StorageWriter used to perform reads. If this is not 2025-07-17T07:36:43.2720098Z specified, DCP will automatically infer the reader based on the 2025-07-17T07:36:43.2720626Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-07-17T07:36:43.2721055Z be raised. (Default: ``None``) 2025-07-17T07:36:43.2721373Z planner (Optional[LoadPlanner]): 2025-07-17T07:36:43.2721793Z Instance of LoadPlanner. If this is not specified, the default 2025-07-17T07:36:43.2722238Z planner will be used. (Default: ``None``) 2025-07-17T07:36:43.2722607Z process_group (Optional[ProcessGroup]): 2025-07-17T07:36:43.2723013Z ProcessGroup to be used for cross-rank synchronization. 2025-07-17T07:36:43.2723408Z (Default: ``None``) 2025-07-17T07:36:43.2723793Z no_dist (bool): If ``True``, this function will assume the intent is to load 2025-07-17T07:36:43.2724368Z a checkpoint without using cross-rank synchronization. (Default: ``False``) 2025-07-17T07:36:43.2724858Z Returns: 2025-07-17T07:36:43.2725068Z None. 2025-07-17T07:36:43.2725205Z 2025-07-17T07:36:43.2725287Z Examples 2025-07-17T07:36:43.2725599Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.2725872Z >>> my_model = MyModule() 2025-07-17T07:36:43.2726179Z >>> optimizer = Adagrad(my_model.parameters()) 2025-07-17T07:36:43.2726560Z >>> model_state_dict = my_model.state_dict() 2025-07-17T07:36:43.2727029Z >>> fs_storage_reader = torch.distributed.checkpoint.FileSystemReader( 2025-07-17T07:36:43.2727523Z ... "/checkpoint/1" 2025-07-17T07:36:43.2727768Z ... ) 2025-07-17T07:36:43.2727899Z 2025-07-17T07:36:43.2728050Z >>> torch.distributed.checkpoint.load_state_dict( 2025-07-17T07:36:43.2728472Z >>> state_dict=model_state_dict, 2025-07-17T07:36:43.2728794Z >>> storage_reader=fs_storage_reader, 2025-07-17T07:36:43.2729101Z >>> ) 2025-07-17T07:36:43.2729215Z 2025-07-17T07:36:43.2729420Z >>> # module.load_state_dict() function might have customized steps 2025-07-17T07:36:43.2729860Z >>> # to flush the state_dict, must call it to 2025-07-17T07:36:43.2730194Z >>> # ensure correct behavior. 2025-07-17T07:36:43.2730520Z >>> my_model.load_state_dict(model_state_dict) 2025-07-17T07:36:43.2730755Z 2025-07-17T07:36:43.2730852Z .. note:: 2025-07-17T07:36:43.2731167Z load_state_dict uses collectives to coordinate reads across ranks. 2025-07-17T07:36:43.2731709Z For NCCL-based process groups, internal tensor representations of 2025-07-17T07:36:43.2732268Z objects must be moved to the GPU device before communication takes place. 2025-07-17T07:36:43.2732823Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-07-17T07:36:43.2733404Z and it is the user's responsibility to ensure that this is set so that each 2025-07-17T07:36:43.2733928Z rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-07-17T07:36:43.2734384Z 2025-07-17T07:36:43.2734688Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.2735061Z 2025-07-17T07:36:43.2736279Z msg = Cannot scrape callname=save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=96. 2025-07-17T07:36:43.2737260Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.2737758Z 2025-07-17T07:36:43.2737873Z Save a distributed model in SPMD style. 2025-07-17T07:36:43.2738093Z 2025-07-17T07:36:43.2738297Z This function is different from ``torch.save()`` as it handles 2025-07-17T07:36:43.2738843Z ``ShardedTensor`` , and ``DTensor`` by having each rank only save their local shards. 2025-07-17T07:36:43.2739249Z 2025-07-17T07:36:43.2739511Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-07-17T07:36:43.2740027Z save will call ``state_dict`` before serialization. 2025-07-17T07:36:43.2740294Z 2025-07-17T07:36:43.2740382Z .. warning:: 2025-07-17T07:36:43.2740806Z There is no guarantees of Backwards Compatibility across PyTorch versions 2025-07-17T07:36:43.2741251Z for saved state_dicts. 2025-07-17T07:36:43.2741432Z 2025-07-17T07:36:43.2741516Z .. warning:: 2025-07-17T07:36:43.2741853Z If using the `process_group` argument, make sure that only its ranks 2025-07-17T07:36:43.2742504Z call `save_state_dict` and that all data in state_dict belong to it. 2025-07-17T07:36:43.2743041Z 2025-07-17T07:36:43.2743204Z .. note:: 2025-07-17T07:36:43.2743636Z When saving checkpoint for FSDP's `ShardingStrategy.HYBRID_SHARD`, only one of 2025-07-17T07:36:43.2744274Z the shard_group should be calling `save_state_dict` and the corresponding process 2025-07-17T07:36:43.2744754Z group needs to be passed in. 2025-07-17T07:36:43.2744959Z 2025-07-17T07:36:43.2745042Z .. note:: 2025-07-17T07:36:43.2745426Z If no process group is available, this function assumes the intention is to save the 2025-07-17T07:36:43.2745912Z state_dict in the local process. 2025-07-17T07:36:43.2746133Z 2025-07-17T07:36:43.2746222Z .. note: 2025-07-17T07:36:43.2746475Z Rank 0 is assumed to be the coordinator rank. 2025-07-17T07:36:43.2746718Z 2025-07-17T07:36:43.2746722Z 2025-07-17T07:36:43.2746813Z Args: 2025-07-17T07:36:43.2747067Z state_dict (Dict[str, Any]): The state_dict to save. 2025-07-17T07:36:43.2747478Z checkpoint_id (Union[str, os.PathLike, None]): 2025-07-17T07:36:43.2747941Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-07-17T07:36:43.2748457Z depends on the storage. It can be a path to a folder or to a file. 2025-07-17T07:36:43.2748945Z It can also be a key if the storage is a key-value store. 2025-07-17T07:36:43.2749321Z (Default: ``None``) 2025-07-17T07:36:43.2749624Z storage_writer (Optional[StorageWriter]): 2025-07-17T07:36:43.2750059Z Instance of StorageWriter used to perform writes. If this is not 2025-07-17T07:36:43.2750589Z specified, DCP will automatically infer the writer based on the 2025-07-17T07:36:43.2751112Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-07-17T07:36:43.2751528Z be raised. (Default: ``None``) 2025-07-17T07:36:43.2751849Z planner (Optional[SavePlanner]): 2025-07-17T07:36:43.2752257Z Instance of SavePlanner. If this is not specified, the default 2025-07-17T07:36:43.2752705Z planner will be used. (Default: ``None``) 2025-07-17T07:36:43.2753055Z process_group (Optional[ProcessGroup]): 2025-07-17T07:36:43.2753471Z ProcessGroup to be used for cross-rank synchronization. 2025-07-17T07:36:43.2753861Z (Default: ``None``) 2025-07-17T07:36:43.2754111Z no_dist (bool): 2025-07-17T07:36:43.2754422Z If ``True``, this function will assume the intent is to load 2025-07-17T07:36:43.2754879Z a checkpoint without using cross-rank synchronization. 2025-07-17T07:36:43.2755259Z (Default: ``False``) 2025-07-17T07:36:43.2755443Z 2025-07-17T07:36:43.2755526Z Returns: 2025-07-17T07:36:43.2755804Z Metadata: Metadata object for the saved checkpoint. 2025-07-17T07:36:43.2756065Z 2025-07-17T07:36:43.2756158Z Example: 2025-07-17T07:36:43.2756365Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.2756638Z >>> my_model = MyModule() 2025-07-17T07:36:43.2756817Z 2025-07-17T07:36:43.2756935Z >>> state_dict = {"model": my_model} 2025-07-17T07:36:43.2757249Z 2025-07-17T07:36:43.2757479Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-07-17T07:36:43.2757928Z ... "/checkpoint/1" 2025-07-17T07:36:43.2758185Z ... ) 2025-07-17T07:36:43.2758440Z >>> torch.distributed.checkpoint.save( 2025-07-17T07:36:43.2758781Z >>> state_dict=state_dict, 2025-07-17T07:36:43.2759095Z >>> storage_writer=fs_storage_writer, 2025-07-17T07:36:43.2759393Z >>> ) 2025-07-17T07:36:43.2759519Z 2025-07-17T07:36:43.2759603Z .. note:: 2025-07-17T07:36:43.2759935Z save_state_dict uses collectives to coordinate writes across ranks. 2025-07-17T07:36:43.2760552Z For NCCL-based process groups, internal tensor representations of 2025-07-17T07:36:43.2761098Z objects must be moved to the GPU device before communication takes place. 2025-07-17T07:36:43.2761669Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-07-17T07:36:43.2762211Z and it is the user's responsibility to ensure that this is set so that 2025-07-17T07:36:43.2762722Z each rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-07-17T07:36:43.2763042Z 2025-07-17T07:36:43.2763293Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.2763672Z 2025-07-17T07:36:43.2764322Z msg = Cannot scrape callname=async_save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=221. 2025-07-17T07:36:43.2765396Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.2766048Z Asynchronous version of ``save``. This code first de-stages the state_dict on to the 2025-07-17T07:36:43.2766710Z staging storage (defaults to CPU memory), and then calls the `save` in a separate thread. 2025-07-17T07:36:43.2767126Z 2025-07-17T07:36:43.2767214Z .. warning:: 2025-07-17T07:36:43.2767511Z This feature is experimental and subject to change. 2025-07-17T07:36:43.2767919Z MUST CALL CLOSE AFTER LAST CHECKPOINT IS SAVED 2025-07-17T07:36:43.2768179Z 2025-07-17T07:36:43.2768260Z Args: 2025-07-17T07:36:43.2768534Z state_dict (Dict[str, Any]): The state_dict to save. 2025-07-17T07:36:43.2768946Z checkpoint_id (Union[str, os.PathLike, None]): 2025-07-17T07:36:43.2769399Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-07-17T07:36:43.2769934Z depends on the storage. It can be a path to a folder or to a file. 2025-07-17T07:36:43.2770590Z It can also be a key if the storage is a key-value store. 2025-07-17T07:36:43.2770962Z (Default: ``None``) 2025-07-17T07:36:43.2771283Z storage_writer (Optional[StorageWriter]): 2025-07-17T07:36:43.2771741Z Instance of StorageWriter used to perform 'stage' and 'save'. If 2025-07-17T07:36:43.2772312Z this is not specified, DCP will automatically infer the writer based on the 2025-07-17T07:36:43.2772872Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-07-17T07:36:43.2773305Z be raised. (Default: ``None``) 2025-07-17T07:36:43.2773637Z planner (Optional[SavePlanner]): 2025-07-17T07:36:43.2774048Z Instance of SavePlanner. If this is not specified, the default 2025-07-17T07:36:43.2774495Z planner will be used. (Default: ``None``) 2025-07-17T07:36:43.2774867Z process_group (Optional[ProcessGroup]): 2025-07-17T07:36:43.2775295Z ProcessGroup to be used for cross-rank synchronization. 2025-07-17T07:36:43.2775676Z (Default: ``None``) 2025-07-17T07:36:43.2776019Z async_checkpointer_type (AsyncCheckpointerType): 2025-07-17T07:36:43.2776466Z whether to do checkpoint in separate thread or process 2025-07-17T07:36:43.2776882Z (Default: ``AsyncCheckpointerType.THREAD``) 2025-07-17T07:36:43.2777249Z async_stager (AsyncStager): 2025-07-17T07:36:43.2777712Z provides staging implementation. If storage_writer implements AsyncStager 2025-07-17T07:36:43.2778475Z and async_stager is provided, async_stager will be used for staging 2025-07-17T07:36:43.2778899Z 2025-07-17T07:36:43.2778984Z Returns: 2025-07-17T07:36:43.2779334Z Future: A future holding the resultant Metadata object from `save`. 2025-07-17T07:36:43.2779662Z 2025-07-17T07:36:43.2779759Z Example: 2025-07-17T07:36:43.2779977Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.2780265Z >>> my_model = MyModule() 2025-07-17T07:36:43.2780454Z 2025-07-17T07:36:43.2780588Z >>> state_dict = {"model": my_model} 2025-07-17T07:36:43.2780802Z 2025-07-17T07:36:43.2781112Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-07-17T07:36:43.2781549Z ... "/checkpoint/1" 2025-07-17T07:36:43.2781819Z ... ) 2025-07-17T07:36:43.2782162Z >>> checkpoint_future = torch.distributed.checkpoint.async_save( 2025-07-17T07:36:43.2782590Z >>> state_dict=state_dict, 2025-07-17T07:36:43.2782919Z >>> storage_writer=fs_storage_writer, 2025-07-17T07:36:43.2783238Z >>> ) 2025-07-17T07:36:43.2783435Z >>> 2025-07-17T07:36:43.2783658Z >>> # ... do some work ... 2025-07-17T07:36:43.2783981Z >>> 2025-07-17T07:36:43.2784202Z >>> checkpoint_future.result() 2025-07-17T07:36:43.2784423Z 2025-07-17T07:36:43.2784501Z 2025-07-17T07:36:43.2784868Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.2785232Z 2025-07-17T07:36:43.3080852Z msg = Cannot scrape callname=construct_and_record_rdzv_event in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/elastic/events/__init__.py line=94. 2025-07-17T07:36:43.3081933Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.3082314Z 2025-07-17T07:36:43.3082516Z Initialize rendezvous event object and record its operations. 2025-07-17T07:36:43.3082844Z 2025-07-17T07:36:43.3082927Z Args: 2025-07-17T07:36:43.3083172Z run_id (str): The run id of the rendezvous. 2025-07-17T07:36:43.3083551Z message (str): The message describing the event. 2025-07-17T07:36:43.3084057Z node_state (NodeState): The state of the node (INIT, RUNNING, SUCCEEDED, FAILED). 2025-07-17T07:36:43.3084618Z name (str): Event name. (E.g. Current action being performed). 2025-07-17T07:36:43.3085029Z hostname (str): Hostname of the node. 2025-07-17T07:36:43.3085431Z pid (Optional[int]): The process id of the node. 2025-07-17T07:36:43.3085950Z master_endpoint (str): The master endpoint for the rendezvous store, if known. 2025-07-17T07:36:43.3086580Z local_id (Optional[int]): The local_id of the node, if defined in dynamic_rendezvous.py 2025-07-17T07:36:43.3087112Z rank (Optional[int]): The rank of the node, if known. 2025-07-17T07:36:43.3087510Z Returns: 2025-07-17T07:36:43.3087764Z None 2025-07-17T07:36:43.3087952Z Example: 2025-07-17T07:36:43.3088198Z >>> # See DynamicRendezvousHandler class 2025-07-17T07:36:43.3088517Z >>> def _record( 2025-07-17T07:36:43.3088740Z ... self, 2025-07-17T07:36:43.3088975Z ... message: str, 2025-07-17T07:36:43.3089279Z ... node_state: NodeState = NodeState.RUNNING, 2025-07-17T07:36:43.3089640Z ... rank: Optional[int] = None, 2025-07-17T07:36:43.3089931Z ... ) -> None: 2025-07-17T07:36:43.3090189Z ... construct_and_record_rdzv_event( 2025-07-17T07:36:43.3090574Z ... name=f"{self.__class__.__name__}.{get_method_name()}", 2025-07-17T07:36:43.3090981Z ... run_id=self._settings.run_id, 2025-07-17T07:36:43.3091309Z ... message=message, 2025-07-17T07:36:43.3091599Z ... node_state=node_state, 2025-07-17T07:36:43.3091912Z ... hostname=self._this_node.addr, 2025-07-17T07:36:43.3092244Z ... pid=self._this_node.pid, 2025-07-17T07:36:43.3092581Z ... local_id=self._this_node.local_id, 2025-07-17T07:36:43.3093101Z ... rank=rank, 2025-07-17T07:36:43.3093338Z ... ) 2025-07-17T07:36:43.3093478Z 2025-07-17T07:36:43.3093727Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.3094094Z 2025-07-17T07:36:43.6729023Z msg = Cannot scrape callname=MixedPrecision in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=114. 2025-07-17T07:36:43.6730018Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.6730401Z 2025-07-17T07:36:43.6730579Z This configures FSDP-native mixed precision training. 2025-07-17T07:36:43.6730871Z 2025-07-17T07:36:43.6731218Z Attributes: 2025-07-17T07:36:43.6731589Z param_dtype (Optional[torch.dtype]): This specifies the dtype for model 2025-07-17T07:36:43.6732147Z parameters during forward and backward and thus the dtype for 2025-07-17T07:36:43.6732674Z forward and backward computation. Outside forward and backward, the 2025-07-17T07:36:43.6733221Z *sharded* parameters are kept in full precision (e.g. for the 2025-07-17T07:36:43.6733736Z optimizer step), and for model checkpointing, the parameters are 2025-07-17T07:36:43.6734204Z always saved in full precision. (Default: ``None``) 2025-07-17T07:36:43.6734690Z reduce_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-07-17T07:36:43.6735238Z gradient reduction (i.e. reduce-scatter or all-reduce). If this is 2025-07-17T07:36:43.6735746Z ``None`` but ``param_dtype`` is not ``None``, then this takes on 2025-07-17T07:36:43.6736224Z the ``param_dtype`` value, still running gradient reduction in low 2025-07-17T07:36:43.6736914Z precision. This is permitted to differ from ``param_dtype``, e.g. 2025-07-17T07:36:43.6737551Z to force gradient reduction to run in full precision. (Default: 2025-07-17T07:36:43.6738057Z ``None``) 2025-07-17T07:36:43.6738414Z buffer_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-07-17T07:36:43.6739008Z buffers. FSDP does not shard buffers. Rather, FSDP casts them to 2025-07-17T07:36:43.6739590Z ``buffer_dtype`` in the first forward pass and keeps them in that 2025-07-17T07:36:43.6740176Z dtype thereafter. For model checkpointing, the buffers are saved 2025-07-17T07:36:43.6740688Z in full precision except for ``LOCAL_STATE_DICT``. (Default: 2025-07-17T07:36:43.6741216Z ``None``) 2025-07-17T07:36:43.6741562Z keep_low_precision_grads (bool): If ``False``, then FSDP upcasts 2025-07-17T07:36:43.6742132Z gradients to full precision after the backward pass in preparation 2025-07-17T07:36:43.6742740Z for the optimizer step. If ``True``, then FSDP keeps the gradients 2025-07-17T07:36:43.6743328Z in the dtype used for gradient reduction, which can save memory if 2025-07-17T07:36:43.6743855Z using a custom optimizer that supports running in low precision. 2025-07-17T07:36:43.6744343Z (Default: ``False``) 2025-07-17T07:36:43.6744788Z cast_forward_inputs (bool): If ``True``, then this FSDP module casts 2025-07-17T07:36:43.6745323Z its forward args and kwargs to ``param_dtype``. This is to ensure 2025-07-17T07:36:43.6745909Z that parameter and input dtypes match for forward computation, as 2025-07-17T07:36:43.6746506Z required by many ops. This may need to be set to ``True`` when only 2025-07-17T07:36:43.6747081Z applying mixed precision to some but not all FSDP modules, in which 2025-07-17T07:36:43.6747663Z case a mixed-precision FSDP submodule needs to recast its inputs. 2025-07-17T07:36:43.6748149Z (Default: ``False``) 2025-07-17T07:36:43.6748551Z cast_root_forward_inputs (bool): If ``True``, then the root FSDP module 2025-07-17T07:36:43.6749152Z casts its forward args and kwargs to ``param_dtype``, overriding 2025-07-17T07:36:43.6749707Z the value of ``cast_forward_inputs``. For non-root FSDP modules, 2025-07-17T07:36:43.6750370Z this does not do anything. (Default: ``True``) 2025-07-17T07:36:43.6750840Z _module_classes_to_ignore: (Sequence[Type[nn.Module]]): This specifies 2025-07-17T07:36:43.6751429Z module classes to ignore for mixed precision when using an 2025-07-17T07:36:43.6751961Z ``auto_wrap_policy``: Modules of these classes will have FSDP 2025-07-17T07:36:43.6752484Z applied to them separately with mixed precision disabled (meaning 2025-07-17T07:36:43.6753076Z that the final FSDP construction would deviate from the specified 2025-07-17T07:36:43.6753639Z policy). If ``auto_wrap_policy`` is not specified, then this does 2025-07-17T07:36:43.6754288Z not do anything. This API is experimental and subject to change. 2025-07-17T07:36:43.6754718Z (Default: ``(_BatchNorm,)``) 2025-07-17T07:36:43.6754983Z 2025-07-17T07:36:43.6755176Z .. note:: This API is experimental and subject to change. 2025-07-17T07:36:43.6755452Z 2025-07-17T07:36:43.6755735Z .. note:: Only floating point tensors are cast to their specified dtypes. 2025-07-17T07:36:43.6756083Z 2025-07-17T07:36:43.6756265Z .. note:: In ``summon_full_params``, parameters are forced to full 2025-07-17T07:36:43.6756743Z precision, but buffers are not. 2025-07-17T07:36:43.6756949Z 2025-07-17T07:36:43.6757152Z .. note:: Layer norm and batch norm accumulate in ``float32`` even when 2025-07-17T07:36:43.6757753Z their inputs are in a low precision like ``float16`` or ``bfloat16``. 2025-07-17T07:36:43.6758376Z Disabling FSDP's mixed precision for those norm modules only means that 2025-07-17T07:36:43.6759012Z the affine parameters are kept in ``float32``. However, this incurs 2025-07-17T07:36:43.6759246Z separate all-gathers and reduce-scatters for those norm modules, which 2025-07-17T07:36:43.6759461Z may be inefficient, so if the workload permits, the user should prefer 2025-07-17T07:36:43.6759683Z to still apply mixed precision to those modules. 2025-07-17T07:36:43.6759692Z 2025-07-17T07:36:43.6759896Z .. note:: By default, if the user passes a model with any ``_BatchNorm`` 2025-07-17T07:36:43.6760113Z modules and specifies an ``auto_wrap_policy``, then the batch norm 2025-07-17T07:36:43.6760367Z modules will have FSDP applied to them separately with mixed precision 2025-07-17T07:36:43.6760565Z disabled. See the ``_module_classes_to_ignore`` argument. 2025-07-17T07:36:43.6760571Z 2025-07-17T07:36:43.6760788Z .. note:: ``MixedPrecision`` has ``cast_root_forward_inputs=True`` and 2025-07-17T07:36:43.6761001Z ``cast_forward_inputs=False`` by default. For the root FSDP instance, 2025-07-17T07:36:43.6761232Z its ``cast_root_forward_inputs`` takes precedence over its 2025-07-17T07:36:43.6761420Z ``cast_forward_inputs``. For non-root FSDP instances, their 2025-07-17T07:36:43.6761633Z ``cast_root_forward_inputs`` values are ignored. The default setting is 2025-07-17T07:36:43.6761871Z sufficient for the typical case where each FSDP instance has the same 2025-07-17T07:36:43.6762152Z ``MixedPrecision`` configuration and only needs to cast inputs to the 2025-07-17T07:36:43.6762331Z ``param_dtype`` at the beginning of the model's forward pass. 2025-07-17T07:36:43.6762336Z 2025-07-17T07:36:43.6762550Z .. note:: For nested FSDP instances with different ``MixedPrecision`` 2025-07-17T07:36:43.6762848Z configurations, we recommend setting individual ``cast_forward_inputs`` 2025-07-17T07:36:43.6763060Z values to configure casting inputs or not before each instance's 2025-07-17T07:36:43.6763248Z forward. In such a case, since the casts happen before each FSDP 2025-07-17T07:36:43.6763495Z instance's forward, a parent FSDP instance should have its non-FSDP 2025-07-17T07:36:43.6763762Z submodules run before its FSDP submodules to avoid the activation dtype 2025-07-17T07:36:43.6763968Z being changed due to a different ``MixedPrecision`` configuration. 2025-07-17T07:36:43.6763973Z 2025-07-17T07:36:43.6764130Z Example:: 2025-07-17T07:36:43.6764135Z 2025-07-17T07:36:43.6764326Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:43.6764500Z >>> model = nn.Sequential(nn.Linear(3, 3), nn.Linear(3, 3)) 2025-07-17T07:36:43.6764608Z >>> model[1] = FSDP( 2025-07-17T07:36:43.6764695Z >>> model[1], 2025-07-17T07:36:43.6764996Z >>> mixed_precision=MixedPrecision(param_dtype=torch.float16, cast_forward_inputs=True), 2025-07-17T07:36:43.6765088Z >>> ) 2025-07-17T07:36:43.6765263Z >>> model = FSDP( 2025-07-17T07:36:43.6765436Z >>> model, 2025-07-17T07:36:43.6765817Z >>> mixed_precision=MixedPrecision(param_dtype=torch.bfloat16, cast_forward_inputs=True), 2025-07-17T07:36:43.6765899Z >>> ) 2025-07-17T07:36:43.6765903Z 2025-07-17T07:36:43.6766123Z The above shows a working example. On the other hand, if ``model[1]`` 2025-07-17T07:36:43.6766337Z were replaced with ``model[0]``, meaning that the submodule using 2025-07-17T07:36:43.6766560Z different ``MixedPrecision`` ran its forward first, then ``model[1]`` 2025-07-17T07:36:43.6766857Z would incorrectly see ``float16`` activations instead of ``bfloat16`` 2025-07-17T07:36:43.6766938Z ones. 2025-07-17T07:36:43.6766943Z 2025-07-17T07:36:43.6766946Z 2025-07-17T07:36:43.6767197Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.6767215Z 2025-07-17T07:36:43.6767803Z msg = Cannot scrape callname=FullStateDictConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=295. 2025-07-17T07:36:43.6768059Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.6768068Z 2025-07-17T07:36:43.6768278Z ``FullStateDictConfig`` is a config class meant to be used with 2025-07-17T07:36:43.6768470Z ``StateDictType.FULL_STATE_DICT``. We recommend enabling both 2025-07-17T07:36:43.6768669Z ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state 2025-07-17T07:36:43.6768972Z dicts to save GPU memory and CPU memory, respectively. This config class 2025-07-17T07:36:43.6769167Z is meant to be used via the :func:`state_dict_type` context manager as 2025-07-17T07:36:43.6769264Z follows: 2025-07-17T07:36:43.6769268Z 2025-07-17T07:36:43.6769392Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:43.6769624Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-07-17T07:36:43.6769761Z >>> fsdp = FSDP(model, auto_wrap_policy=...) 2025-07-17T07:36:43.6770129Z >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True) 2025-07-17T07:36:43.6770402Z >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg): 2025-07-17T07:36:43.6770521Z >>> state = fsdp.state_dict() 2025-07-17T07:36:43.6770726Z >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0. 2025-07-17T07:36:43.6770974Z >>> # To reload checkpoint for inference, finetuning, transfer learning, etc: 2025-07-17T07:36:43.6771211Z >>> model = model_fn() # Initialize model in preparation for wrapping with FSDP 2025-07-17T07:36:43.6771311Z >>> if dist.get_rank() == 0: 2025-07-17T07:36:43.6771501Z >>> # Load checkpoint only on rank 0 to avoid memory redundancy 2025-07-17T07:36:43.6771637Z >>> state_dict = torch.load("my_checkpoint.pt") 2025-07-17T07:36:43.6771751Z >>> model.load_state_dict(state_dict) 2025-07-17T07:36:43.6771993Z >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument 2025-07-17T07:36:43.6772227Z >>> # communicates loaded checkpoint states from rank 0 to rest of the world. 2025-07-17T07:36:43.6772328Z >>> fsdp = FSDP( 2025-07-17T07:36:43.6772411Z ... model, 2025-07-17T07:36:43.6772539Z ... device_id=torch.cuda.current_device(), 2025-07-17T07:36:43.6772715Z ... auto_wrap_policy=..., 2025-07-17T07:36:43.6772817Z ... sync_module_states=True, 2025-07-17T07:36:43.6772896Z ... ) 2025-07-17T07:36:43.6773230Z >>> # After this point, all ranks have FSDP model with loaded checkpoint. 2025-07-17T07:36:43.6773234Z 2025-07-17T07:36:43.6773320Z Attributes: 2025-07-17T07:36:43.6773514Z rank0_only (bool): If ``True``, then only rank 0 saves the full state 2025-07-17T07:36:43.6773725Z dict, and nonzero ranks save an empty dict. If ``False``, then all 2025-07-17T07:36:43.6773879Z ranks save the full state dict. (Default: ``False``) 2025-07-17T07:36:43.6773883Z 2025-07-17T07:36:43.6774148Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.6774152Z 2025-07-17T07:36:43.6869276Z msg = Cannot scrape callname=FullyShardedDataParallel.set_state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=637. 2025-07-17T07:36:43.6869562Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.6869806Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-07-17T07:36:43.6869818Z 2025-07-17T07:36:43.6870249Z Also takes (optional) configuration for the model's and optimizer's state dict. 2025-07-17T07:36:43.6870468Z The target module does not have to be a FSDP module. If the target 2025-07-17T07:36:43.6870674Z module is a FSDP module, its ``state_dict_type`` will also be changed. 2025-07-17T07:36:43.6870679Z 2025-07-17T07:36:43.6870918Z .. note:: This API should be called for only the top-level (root) 2025-07-17T07:36:43.6871041Z module. 2025-07-17T07:36:43.6871046Z 2025-07-17T07:36:43.6871257Z .. note:: This API enables users to transparently use the conventional 2025-07-17T07:36:43.6871473Z ``state_dict`` API to take model checkpoints in cases where the 2025-07-17T07:36:43.6871698Z root FSDP module is wrapped by another ``nn.Module``. For example, 2025-07-17T07:36:43.6871946Z the following will ensure ``state_dict`` is called on all non-FSDP 2025-07-17T07:36:43.6872179Z instances, while dispatching into `sharded_state_dict` implementation 2025-07-17T07:36:43.6872264Z for FSDP: 2025-07-17T07:36:43.6872281Z 2025-07-17T07:36:43.6872368Z Example:: 2025-07-17T07:36:43.6872372Z 2025-07-17T07:36:43.6872501Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:43.6872615Z >>> model = DDP(FSDP(...)) 2025-07-17T07:36:43.6872721Z >>> FSDP.set_state_dict_type( 2025-07-17T07:36:43.6872808Z >>> model, 2025-07-17T07:36:43.6872998Z >>> StateDictType.SHARDED_STATE_DICT, 2025-07-17T07:36:43.6873233Z >>> state_dict_config = ShardedStateDictConfig(offload_to_cpu=True), 2025-07-17T07:36:43.6873570Z >>> optim_state_dict_config = OptimStateDictConfig(offload_to_cpu=True), 2025-07-17T07:36:43.6873709Z >>> ) 2025-07-17T07:36:43.6873920Z >>> param_state_dict = model.state_dict() 2025-07-17T07:36:43.6874209Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-07-17T07:36:43.6874215Z 2025-07-17T07:36:43.6874327Z Args: 2025-07-17T07:36:43.6874462Z module (torch.nn.Module): Root module. 2025-07-17T07:36:43.6874748Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-07-17T07:36:43.6874980Z state_dict_config (Optional[StateDictConfig]): the configuration for the 2025-07-17T07:36:43.6875088Z target ``state_dict_type``. 2025-07-17T07:36:43.6875348Z optim_state_dict_config (Optional[OptimStateDictConfig]): the configuration 2025-07-17T07:36:43.6875465Z for the optimizer state dict. 2025-07-17T07:36:43.6875469Z 2025-07-17T07:36:43.6875565Z Returns: 2025-07-17T07:36:43.6875788Z A StateDictSettings that include the previous state_dict type and 2025-07-17T07:36:43.6875896Z configuration for the module. 2025-07-17T07:36:43.6876118Z 2025-07-17T07:36:43.6876369Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.6876374Z 2025-07-17T07:36:43.6877216Z msg = Cannot scrape callname=FullyShardedDataParallel.state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=795. 2025-07-17T07:36:43.6877474Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.6877718Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-07-17T07:36:43.6877723Z 2025-07-17T07:36:43.6878116Z This context manager has the same functions as :meth:`set_state_dict_type`. Read the document of 2025-07-17T07:36:43.6878245Z :meth:`set_state_dict_type` for the detail. 2025-07-17T07:36:43.6878249Z 2025-07-17T07:36:43.6878350Z Example:: 2025-07-17T07:36:43.6878355Z 2025-07-17T07:36:43.6878480Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:43.6878585Z >>> model = DDP(FSDP(...)) 2025-07-17T07:36:43.6878705Z >>> with FSDP.state_dict_type( 2025-07-17T07:36:43.6878791Z >>> model, 2025-07-17T07:36:43.6878917Z >>> StateDictType.SHARDED_STATE_DICT, 2025-07-17T07:36:43.6879008Z >>> ): 2025-07-17T07:36:43.6879123Z >>> checkpoint = model.state_dict() 2025-07-17T07:36:43.6879128Z 2025-07-17T07:36:43.6879220Z Args: 2025-07-17T07:36:43.6879337Z module (torch.nn.Module): Root module. 2025-07-17T07:36:43.6879565Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-07-17T07:36:43.6879807Z state_dict_config (Optional[StateDictConfig]): the model ``state_dict`` 2025-07-17T07:36:43.6879961Z configuration for the target ``state_dict_type``. 2025-07-17T07:36:43.6880191Z optim_state_dict_config (Optional[OptimStateDictConfig]): the optimizer 2025-07-17T07:36:43.6880399Z ``state_dict`` configuration for the target ``state_dict_type``. 2025-07-17T07:36:43.6880478Z 2025-07-17T07:36:43.6880737Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.6880741Z 2025-07-17T07:36:43.6928469Z msg = Cannot scrape callname=FullyShardedDataParallel.optim_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1808. 2025-07-17T07:36:43.6928807Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.6928813Z 2025-07-17T07:36:43.6929061Z Transform the state-dict of an optimizer corresponding to a sharded model. 2025-07-17T07:36:43.6929066Z 2025-07-17T07:36:43.6929254Z The given state-dict can be transformed to one of three types: 2025-07-17T07:36:43.6929630Z 1) full optimizer state_dict, 2) sharded optimizer state_dict, 3) local optimizer state_dict. 2025-07-17T07:36:43.6929643Z 2025-07-17T07:36:43.6929871Z For full optimizer state_dict, all states are unflattened and not sharded. 2025-07-17T07:36:43.6930094Z Rank0 only and CPU only can be specified via :meth:`state_dict_type` to 2025-07-17T07:36:43.6930181Z avoid OOM. 2025-07-17T07:36:43.6930186Z 2025-07-17T07:36:43.6930483Z For sharded optimizer state_dict, all states are unflattened but sharded. 2025-07-17T07:36:43.6930696Z CPU only can be specified via :meth:`state_dict_type` to further save 2025-07-17T07:36:43.6930778Z memory. 2025-07-17T07:36:43.6930783Z 2025-07-17T07:36:43.6930994Z For local state_dict, no transformation will be performed. But a state 2025-07-17T07:36:43.6931327Z will be converted from nn.Tensor to ShardedTensor to represent its sharding 2025-07-17T07:36:43.6931498Z nature (this is not supported yet). 2025-07-17T07:36:43.6931505Z 2025-07-17T07:36:43.6931667Z Example:: 2025-07-17T07:36:43.6931674Z 2025-07-17T07:36:43.6931878Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:43.6932306Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-07-17T07:36:43.6932474Z >>> from torch.distributed.fsdp import StateDictType 2025-07-17T07:36:43.6932758Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-07-17T07:36:43.6933162Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-07-17T07:36:43.6933339Z >>> # Save a checkpoint 2025-07-17T07:36:43.6933477Z >>> model, optim = ... 2025-07-17T07:36:43.6933591Z >>> FSDP.set_state_dict_type( 2025-07-17T07:36:43.6933673Z >>> model, 2025-07-17T07:36:43.6933787Z >>> StateDictType.FULL_STATE_DICT, 2025-07-17T07:36:43.6933925Z >>> FullStateDictConfig(rank0_only=False), 2025-07-17T07:36:43.6934144Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-07-17T07:36:43.6934238Z >>> ) 2025-07-17T07:36:43.6934345Z >>> state_dict = model.state_dict() 2025-07-17T07:36:43.6934509Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-07-17T07:36:43.6934665Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-07-17T07:36:43.6934760Z >>> # Load a checkpoint 2025-07-17T07:36:43.6934856Z >>> model, optim = ... 2025-07-17T07:36:43.6935015Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-07-17T07:36:43.6935119Z >>> FSDP.set_state_dict_type( 2025-07-17T07:36:43.6935203Z >>> model, 2025-07-17T07:36:43.6935330Z >>> StateDictType.FULL_STATE_DICT, 2025-07-17T07:36:43.6935454Z >>> FullStateDictConfig(rank0_only=False), 2025-07-17T07:36:43.6935605Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-07-17T07:36:43.6935686Z >>> ) 2025-07-17T07:36:43.6935803Z >>> model.load_state_dict(state_dict) 2025-07-17T07:36:43.6935964Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-07-17T07:36:43.6936077Z >>> model, optim, optim_state_dict 2025-07-17T07:36:43.6936158Z >>> ) 2025-07-17T07:36:43.6936294Z >>> optim.load_state_dict(optim_state_dict) 2025-07-17T07:36:43.6936303Z 2025-07-17T07:36:43.6936384Z Args: 2025-07-17T07:36:43.6936576Z model (torch.nn.Module): Root module (which may or may not be a 2025-07-17T07:36:43.6936788Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-07-17T07:36:43.6936917Z were passed into the optimizer ``optim``. 2025-07-17T07:36:43.6937108Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-07-17T07:36:43.6937199Z parameters. 2025-07-17T07:36:43.6937409Z optim_state_dict (Dict[str, Any]): the target optimizer state_dict to 2025-07-17T07:36:43.6937629Z transform. If the value is None, optim.state_dict() will be used. ( 2025-07-17T07:36:43.6937723Z Default: ``None``) 2025-07-17T07:36:43.6937961Z group (dist.ProcessGroup): Model's process group across which parameters 2025-07-17T07:36:43.6938158Z are sharded or ``None`` if using the default process group. ( 2025-07-17T07:36:43.6938252Z Default: ``None``) 2025-07-17T07:36:43.6938257Z 2025-07-17T07:36:43.6938357Z Returns: 2025-07-17T07:36:43.6938545Z Dict[str, Any]: A :class:`dict` containing the optimizer state for 2025-07-17T07:36:43.6938705Z ``model``. The sharding of the optimizer state is based on 2025-07-17T07:36:43.6938813Z ``state_dict_type``. 2025-07-17T07:36:43.6938818Z 2025-07-17T07:36:43.6939068Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.6939073Z 2025-07-17T07:36:43.6939962Z msg = Cannot scrape callname=FullyShardedDataParallel.optim_state_dict_to_load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1906. 2025-07-17T07:36:43.6940224Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.6940228Z 2025-07-17T07:36:43.6940597Z Convert an optimizer state-dict so that it can be loaded into the optimizer associated with the FSDP model. 2025-07-17T07:36:43.6940602Z 2025-07-17T07:36:43.6940764Z Given a ``optim_state_dict`` that is transformed through 2025-07-17T07:36:43.6941032Z :meth:`optim_state_dict`, it gets converted to the flattened optimizer 2025-07-17T07:36:43.6941250Z state_dict that can be loaded to ``optim`` which is the optimizer for 2025-07-17T07:36:43.6941433Z ``model``. ``model`` must be sharded by FullyShardedDataParallel. 2025-07-17T07:36:43.6941438Z 2025-07-17T07:36:43.6941575Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:43.6941805Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-07-17T07:36:43.6941956Z >>> from torch.distributed.fsdp import StateDictType 2025-07-17T07:36:43.6942188Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-07-17T07:36:43.6942384Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-07-17T07:36:43.6942479Z >>> # Save a checkpoint 2025-07-17T07:36:43.6942583Z >>> model, optim = ... 2025-07-17T07:36:43.6942684Z >>> FSDP.set_state_dict_type( 2025-07-17T07:36:43.6942769Z >>> model, 2025-07-17T07:36:43.6942894Z >>> StateDictType.FULL_STATE_DICT, 2025-07-17T07:36:43.6943019Z >>> FullStateDictConfig(rank0_only=False), 2025-07-17T07:36:43.6943170Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-07-17T07:36:43.6943250Z >>> ) 2025-07-17T07:36:43.6943355Z >>> state_dict = model.state_dict() 2025-07-17T07:36:43.6943477Z >>> original_osd = optim.state_dict() 2025-07-17T07:36:43.6943600Z >>> optim_state_dict = FSDP.optim_state_dict( 2025-07-17T07:36:43.6943682Z >>> model, 2025-07-17T07:36:43.6943777Z >>> optim, 2025-07-17T07:36:43.6943885Z >>> optim_state_dict=original_osd 2025-07-17T07:36:43.6943966Z >>> ) 2025-07-17T07:36:43.6944118Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-07-17T07:36:43.6944212Z >>> # Load a checkpoint 2025-07-17T07:36:43.6944320Z >>> model, optim = ... 2025-07-17T07:36:43.6944468Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-07-17T07:36:43.6944571Z >>> FSDP.set_state_dict_type( 2025-07-17T07:36:43.6944664Z >>> model, 2025-07-17T07:36:43.6944776Z >>> StateDictType.FULL_STATE_DICT, 2025-07-17T07:36:43.6944899Z >>> FullStateDictConfig(rank0_only=False), 2025-07-17T07:36:43.6945047Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-07-17T07:36:43.6945130Z >>> ) 2025-07-17T07:36:43.6945240Z >>> model.load_state_dict(state_dict) 2025-07-17T07:36:43.6945394Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-07-17T07:36:43.6945503Z >>> model, optim, optim_state_dict 2025-07-17T07:36:43.6945582Z >>> ) 2025-07-17T07:36:43.6945713Z >>> optim.load_state_dict(optim_state_dict) 2025-07-17T07:36:43.6945721Z 2025-07-17T07:36:43.6945799Z Args: 2025-07-17T07:36:43.6945999Z model (torch.nn.Module): Root module (which may or may not be a 2025-07-17T07:36:43.6946193Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-07-17T07:36:43.6946319Z were passed into the optimizer ``optim``. 2025-07-17T07:36:43.6946507Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-07-17T07:36:43.6946593Z parameters. 2025-07-17T07:36:43.6946801Z optim_state_dict (Dict[str, Any]): The optimizer states to be loaded. 2025-07-17T07:36:43.6947005Z is_named_optimizer (bool): Is this optimizer a NamedOptimizer or 2025-07-17T07:36:43.6947193Z KeyedOptimizer. Only set to True if ``optim`` is TorchRec's 2025-07-17T07:36:43.6947374Z KeyedOptimizer or torch.distributed's NamedOptimizer. 2025-07-17T07:36:43.6947563Z load_directly (bool): If this is set to True, this API will also 2025-07-17T07:36:43.6947760Z call optim.load_state_dict(result) before returning the result. 2025-07-17T07:36:43.6947986Z Otherwise, users are responsible to call ``optim.load_state_dict()`` 2025-07-17T07:36:43.6948082Z (Default: ``False``) 2025-07-17T07:36:43.6948315Z group (dist.ProcessGroup): Model's process group across which parameters 2025-07-17T07:36:43.6948571Z are sharded or ``None`` if using the default process group. ( 2025-07-17T07:36:43.6948664Z Default: ``None``) 2025-07-17T07:36:43.6948668Z 2025-07-17T07:36:43.6948931Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.6948935Z 2025-07-17T07:36:43.7483576Z msg = Cannot scrape callname=_RemoteModule.__init__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=129. 2025-07-17T07:36:43.7484623Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.7485013Z 2025-07-17T07:36:43.7485507Z RemoteModule instance can only be created after RPC initialization. 2025-07-17T07:36:43.7485870Z 2025-07-17T07:36:43.7486062Z It creates a user-specified module on a specified remote node. 2025-07-17T07:36:43.7486603Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-07-17T07:36:43.7487059Z executed on the remote node. 2025-07-17T07:36:43.7487475Z It takes care of autograd recording to ensure the backward pass propagates 2025-07-17T07:36:43.7487978Z gradients back to the corresponding remote module. 2025-07-17T07:36:43.7488591Z It can be shared across processors using `RPC framework `__, 2025-07-17T07:36:43.7489256Z without incurring any overheads of copying the actual module, 2025-07-17T07:36:43.7489762Z which is equivalent to an :class:`~torch.distributed.rpc.RRef` 2025-07-17T07:36:43.7490182Z pointing to the remote module. 2025-07-17T07:36:43.7490366Z 2025-07-17T07:36:43.7490604Z The arguments of ``forward_async`` and ``forward`` are the same as 2025-07-17T07:36:43.7491112Z the ``forward`` method of the module returned by the ``module_cls``. 2025-07-17T07:36:43.7491436Z 2025-07-17T07:36:43.7491738Z Apart from ``forward_async`` and ``forward``, no other methods are supported from nn.Module for now. 2025-07-17T07:36:43.7492366Z 2025-07-17T07:36:43.7492797Z Particularly, to create a hybrid model, typically the local modules should be 2025-07-17T07:36:43.7493750Z created outside of remote modules, rather than as submodules of any remote module (by calling ``add_module``). 2025-07-17T07:36:43.7494328Z Hybrid Example: 2025-07-17T07:36:43.7494584Z >>> class HybridModel(nn.Module): 2025-07-17T07:36:43.7494922Z >>> def __init__(self) -> None: 2025-07-17T07:36:43.7495237Z >>> nn.Module.__init__(self) 2025-07-17T07:36:43.7495592Z >>> self.remote_embedding = RemoteModule(...) 2025-07-17T07:36:43.7495972Z >>> self.local_linear = nn.Linear(...) 2025-07-17T07:36:43.7496203Z 2025-07-17T07:36:43.7496415Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-07-17T07:36:43.7496963Z that has ``forward`` method signature, ``def forward(input: Tensor) -> Tensor:``, 2025-07-17T07:36:43.7497532Z the generated ``RemoteModule`` will have 2 methods in signature of 2025-07-17T07:36:43.7497983Z ``def forward(input: Tensor) -> Tensor:`` and 2025-07-17T07:36:43.7498367Z ``def forward_async(input: Tensor) -> Future[Tensor]:``. 2025-07-17T07:36:43.7498645Z 2025-07-17T07:36:43.7498740Z .. note:: 2025-07-17T07:36:43.7498998Z If the remote module is placed on a cuda device, 2025-07-17T07:36:43.7499483Z any input CPU tensors will be automatically moved to the same cuda device, 2025-07-17T07:36:43.7500354Z and GPU tensors are returned over the wire according to the device map of the remote worker on TensorPipe RPC backend. 2025-07-17T07:36:43.7501027Z 2025-07-17T07:36:43.7501143Z Args: 2025-07-17T07:36:43.7501563Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-07-17T07:36:43.7502332Z The device can be a local device or a remote device specified by one of the following remote 2025-07-17T07:36:43.7502841Z formats: 2025-07-17T07:36:43.7502992Z 2025-07-17T07:36:43.7503130Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-07-17T07:36:43.7503688Z 2. "/" (ex: "trainer0/cuda:0"). 2025-07-17T07:36:43.7503944Z 2025-07-17T07:36:43.7504183Z In addition, the device field can be optional and the default value is "cpu". 2025-07-17T07:36:43.7504662Z module_cls (nn.Module): For example, 2025-07-17T07:36:43.7504994Z >>> class MyModule(nn.Module): 2025-07-17T07:36:43.7505293Z >>> def forward(input): 2025-07-17T07:36:43.7505591Z >>> return input + 1 2025-07-17T07:36:43.7505876Z >>> 2025-07-17T07:36:43.7506084Z >>> module_cls = MyModule 2025-07-17T07:36:43.7506474Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-07-17T07:36:43.7507038Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-07-17T07:36:43.7507623Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-07-17T07:36:43.7508244Z to be created. The type object should be decorated by @torch.jit.interface. 2025-07-17T07:36:43.7508818Z If not provided, the generated RemoteModule is not torchscript-able. 2025-07-17T07:36:43.7509395Z Warning, this is an experimental API and susceptible to frequent changes. 2025-07-17T07:36:43.7509744Z 2025-07-17T07:36:43.7509841Z Returns: 2025-07-17T07:36:43.7510190Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-07-17T07:36:43.7510886Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-07-17T07:36:43.7511506Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-07-17T07:36:43.7512028Z on the user-provided module on the remote side. 2025-07-17T07:36:43.7512294Z 2025-07-17T07:36:43.7512385Z Example:: 2025-07-17T07:36:43.7512659Z Run the following code in two different processes: 2025-07-17T07:36:43.7512918Z 2025-07-17T07:36:43.7513041Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:43.7513338Z >>> # On worker 0: 2025-07-17T07:36:43.7513590Z >>> import torch 2025-07-17T07:36:43.7513867Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:43.7514194Z >>> from torch import nn, Tensor 2025-07-17T07:36:43.7514622Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-07-17T07:36:43.7515041Z >>> 2025-07-17T07:36:43.7515284Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-07-17T07:36:43.7515656Z >>> remote_linear_module = RemoteModule( 2025-07-17T07:36:43.7516007Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-07-17T07:36:43.7516313Z >>> ) 2025-07-17T07:36:43.7516534Z >>> input = torch.randn(128, 20) 2025-07-17T07:36:43.7516892Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-07-17T07:36:43.7517243Z >>> ret = ret_fut.wait() 2025-07-17T07:36:43.7517517Z >>> rpc.shutdown() 2025-07-17T07:36:43.7517683Z 2025-07-17T07:36:43.7517766Z >>> # On worker 1: 2025-07-17T07:36:43.7518004Z >>> import torch 2025-07-17T07:36:43.7518270Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:43.7518618Z >>> 2025-07-17T07:36:43.7518871Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-07-17T07:36:43.7519202Z >>> rpc.shutdown() 2025-07-17T07:36:43.7519363Z 2025-07-17T07:36:43.7519610Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.7519978Z 2025-07-17T07:36:43.7520738Z msg = Cannot scrape callname=_RemoteModule.init_from_module_rref in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=506. 2025-07-17T07:36:43.7521814Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.7522204Z 2025-07-17T07:36:43.7522519Z Besides the constructor, a RemoteModule instance can also be initialized given a module RRef. 2025-07-17T07:36:43.7522955Z 2025-07-17T07:36:43.7523283Z This alternate initialization method can be particularly useful if we want to create multiple 2025-07-17T07:36:43.7524104Z RemoteModule instances that share the same underlying module and reduce memory consumption. 2025-07-17T07:36:43.7524546Z 2025-07-17T07:36:43.7524820Z Moreover, this also provides a workaround for passing script RemoteModule over RPC, 2025-07-17T07:36:43.7525448Z which is not supported. The recommended way is as follows: 2025-07-17T07:36:43.7525738Z 2025-07-17T07:36:43.7525864Z 1. the sender creates a RemoteModule; 2025-07-17T07:36:43.7526217Z 2. the sender sends its ``module_rref`` over RPC; 2025-07-17T07:36:43.7526804Z 3. the receiver calls this method to initialize another RemoteModule using the same ``module_rref``. 2025-07-17T07:36:43.7527255Z 2025-07-17T07:36:43.7527357Z Example:: 2025-07-17T07:36:43.7527691Z Run the following code in two different processes: 2025-07-17T07:36:43.7527950Z 2025-07-17T07:36:43.7528059Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:43.7528374Z >>> # On worker 0: 2025-07-17T07:36:43.7528621Z >>> import torch 2025-07-17T07:36:43.7528887Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:43.7529228Z >>> from torch import nn, Tensor 2025-07-17T07:36:43.7529651Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-07-17T07:36:43.7530059Z >>> 2025-07-17T07:36:43.7530311Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-07-17T07:36:43.7530668Z >>> remote_module = RemoteModule( 2025-07-17T07:36:43.7530995Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-07-17T07:36:43.7531312Z >>> ) 2025-07-17T07:36:43.7531512Z >>> 2025-07-17T07:36:43.7531735Z >>> remote_module1 = rpc.rpc_sync( 2025-07-17T07:36:43.7532031Z >>> "worker1/cpu", 2025-07-17T07:36:43.7532328Z >>> RemoteModule.init_from_module_rref, 2025-07-17T07:36:43.7532716Z >>> ("worker1/cpu", remote_module1.get_module_rref()), 2025-07-17T07:36:43.7533054Z >>> ) 2025-07-17T07:36:43.7533266Z >>> rpc.shutdown() 2025-07-17T07:36:43.7533418Z 2025-07-17T07:36:43.7533522Z >>> # On worker 1: 2025-07-17T07:36:43.7533755Z >>> import torch 2025-07-17T07:36:43.7534030Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:43.7534343Z >>> 2025-07-17T07:36:43.7534580Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-07-17T07:36:43.7534920Z >>> rpc.shutdown() 2025-07-17T07:36:43.7535069Z 2025-07-17T07:36:43.7535159Z Args: 2025-07-17T07:36:43.7535556Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-07-17T07:36:43.7536259Z The device can be a local device or a remote device specified by one of the following remote 2025-07-17T07:36:43.7536754Z formats: 2025-07-17T07:36:43.7536887Z 2025-07-17T07:36:43.7537037Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-07-17T07:36:43.7537465Z 2. "/" (ex: "trainer0/cuda:0"). 2025-07-17T07:36:43.7537739Z 2025-07-17T07:36:43.7537978Z In addition, the device field can be optional and the default value is "cpu". 2025-07-17T07:36:43.7538596Z module_rref (RRef[nn.Module]): The module reference shared by both the caller and 2025-07-17T07:36:43.7539074Z the created remote module. 2025-07-17T07:36:43.7539558Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-07-17T07:36:43.7540189Z to be created. The type object should be decorated by @torch.jit.interface. 2025-07-17T07:36:43.7540751Z If not provided, the generated RemoteModule is not torchscript-able. 2025-07-17T07:36:43.7541325Z Warning, this is an experimental API and susceptible to frequent changes. 2025-07-17T07:36:43.7541685Z 2025-07-17T07:36:43.7541770Z Returns: 2025-07-17T07:36:43.7542141Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-07-17T07:36:43.7542729Z user-provided ``module_rref``, it has a blocking ``forward`` method and an 2025-07-17T07:36:43.7543356Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-07-17T07:36:43.7543985Z on the user-provided module on the remote side. 2025-07-17T07:36:43.7544237Z 2025-07-17T07:36:43.7544486Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.7544869Z 2025-07-17T07:36:43.7545483Z msg = Cannot scrape callname=RemoteModule in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=598. 2025-07-17T07:36:43.7546472Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.7546847Z 2025-07-17T07:36:43.7547090Z A RemoteModule instance can only be created after RPC initialization. 2025-07-17T07:36:43.7547432Z 2025-07-17T07:36:43.7547694Z It creates a user-specified module on a specified remote node. 2025-07-17T07:36:43.7548226Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-07-17T07:36:43.7548688Z executed on the remote node. 2025-07-17T07:36:43.7549121Z It takes care of autograd recording to ensure the backward pass propagates 2025-07-17T07:36:43.7549618Z gradients back to the corresponding remote module. 2025-07-17T07:36:43.7549896Z 2025-07-17T07:36:43.7550110Z It generates two methods ``forward_async`` and ``forward`` based on the 2025-07-17T07:36:43.7550654Z signature of the ``forward`` method of ``module_cls``. ``forward_async`` 2025-07-17T07:36:43.7551235Z runs asynchronously and returns a Future. The arguments of ``forward_async`` 2025-07-17T07:36:43.7551789Z and ``forward`` are the same as the ``forward`` method of the module 2025-07-17T07:36:43.7552213Z returned by the ``module_cls``. 2025-07-17T07:36:43.7552411Z 2025-07-17T07:36:43.7552619Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-07-17T07:36:43.7553173Z that has ``forward`` method signature: ``def forward(input: Tensor) -> Tensor:``, 2025-07-17T07:36:43.7553767Z the generated ``RemoteModule`` will have 2 methods with the signatures: 2025-07-17T07:36:43.7554122Z 2025-07-17T07:36:43.7554242Z | ``def forward(input: Tensor) -> Tensor:`` 2025-07-17T07:36:43.7554635Z | ``def forward_async(input: Tensor) -> Future[Tensor]:`` 2025-07-17T07:36:43.7554905Z 2025-07-17T07:36:43.7554983Z Args: 2025-07-17T07:36:43.7555392Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-07-17T07:36:43.7556144Z The format should be "/", where the device field can be parsed as torch.device type. 2025-07-17T07:36:43.7556772Z E.g., "trainer0/cpu", "trainer0", "ps0/cuda:0". 2025-07-17T07:36:43.7557259Z In addition, the device field can be optional and the default value is "cpu". 2025-07-17T07:36:43.7557871Z module_cls (nn.Module): Class for the module to be created remotely. For example, 2025-07-17T07:36:43.7558236Z 2025-07-17T07:36:43.7558363Z >>> class MyModule(nn.Module): 2025-07-17T07:36:43.7558665Z >>> def forward(input): 2025-07-17T07:36:43.7558967Z >>> return input + 1 2025-07-17T07:36:43.7559252Z >>> 2025-07-17T07:36:43.7559462Z >>> module_cls = MyModule 2025-07-17T07:36:43.7559664Z 2025-07-17T07:36:43.7559857Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-07-17T07:36:43.7560358Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-07-17T07:36:43.7560660Z 2025-07-17T07:36:43.7560756Z Returns: 2025-07-17T07:36:43.7561105Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-07-17T07:36:43.7561694Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-07-17T07:36:43.7562314Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-07-17T07:36:43.7562845Z on the user-provided module on the remote side. 2025-07-17T07:36:43.7563092Z 2025-07-17T07:36:43.7563178Z Example:: 2025-07-17T07:36:43.7563451Z Run the following code in two different processes: 2025-07-17T07:36:43.7563771Z 2025-07-17T07:36:43.7563894Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:43.7564193Z >>> # On worker 0: 2025-07-17T07:36:43.7564441Z >>> import torch 2025-07-17T07:36:43.7564720Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:43.7565049Z >>> from torch import nn, Tensor 2025-07-17T07:36:43.7565557Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-07-17T07:36:43.7565984Z >>> 2025-07-17T07:36:43.7566228Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-07-17T07:36:43.7566597Z >>> remote_linear_module = RemoteModule( 2025-07-17T07:36:43.7566950Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-07-17T07:36:43.7567331Z >>> ) 2025-07-17T07:36:43.7567541Z >>> input = torch.randn(128, 20) 2025-07-17T07:36:43.7567895Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-07-17T07:36:43.7568264Z >>> ret = ret_fut.wait() 2025-07-17T07:36:43.7568524Z >>> rpc.shutdown() 2025-07-17T07:36:43.7568693Z 2025-07-17T07:36:43.7568779Z >>> # On worker 1: 2025-07-17T07:36:43.7569018Z >>> import torch 2025-07-17T07:36:43.7569279Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:43.7569592Z >>> 2025-07-17T07:36:43.7569839Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-07-17T07:36:43.7570327Z >>> rpc.shutdown() 2025-07-17T07:36:43.7570493Z 2025-07-17T07:36:43.7570683Z Furthermore, a more practical example that is combined with 2025-07-17T07:36:43.7571477Z `DistributedDataParallel `__ (DDP) 2025-07-17T07:36:43.7572396Z can be found in this `tutorial `__. 2025-07-17T07:36:43.7572841Z 2025-07-17T07:36:43.7573091Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.7573466Z 2025-07-17T07:36:43.7730863Z msg = Cannot scrape callname=DistributedOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/optimizer.py line=129. 2025-07-17T07:36:43.7731908Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.7732310Z 2025-07-17T07:36:43.7732560Z DistributedOptimizer takes remote references to parameters scattered 2025-07-17T07:36:43.7733155Z across workers and applies the given optimizer locally for each parameter. 2025-07-17T07:36:43.7733506Z 2025-07-17T07:36:43.7733736Z This class uses :meth:`~torch.distributed.autograd.get_gradients` in order 2025-07-17T07:36:43.7734239Z to retrieve the gradients for specific parameters. 2025-07-17T07:36:43.7734498Z 2025-07-17T07:36:43.7734609Z Concurrent calls to 2025-07-17T07:36:43.7734951Z :meth:`~torch.distributed.optim.DistributedOptimizer.step`, 2025-07-17T07:36:43.7735413Z either from the same or different clients, will 2025-07-17T07:36:43.7735889Z be serialized on each worker -- as each worker's optimizer can only work 2025-07-17T07:36:43.7736442Z on one set of gradients at a time. However, there is no guarantee that 2025-07-17T07:36:43.7736996Z the full forward-backward-optimizer sequence will execute for one client 2025-07-17T07:36:43.7737573Z at a time. This means that the gradients being applied may not correspond 2025-07-17T07:36:43.7738130Z to the latest forward pass executed on a given worker. Also, there is no 2025-07-17T07:36:43.7738571Z guaranteed ordering across workers. 2025-07-17T07:36:43.7738788Z 2025-07-17T07:36:43.7739043Z `DistributedOptimizer` creates the local optimizer with TorchScript enabled 2025-07-17T07:36:43.7739650Z by default, so that optimizer updates are not blocked by the Python Global 2025-07-17T07:36:43.7740241Z Interpreter Lock (GIL) in the case of multithreaded training (e.g. Distributed 2025-07-17T07:36:43.7740826Z Model Parallel). This feature is currently enabled for most optimizers. You 2025-07-17T07:36:43.7741431Z can also follow `the recipe`__ in PyTorch tutorials to enable TorchScript support 2025-07-17T07:36:43.7742081Z for your own custom optimizers. 2025-07-17T07:36:43.7742292Z 2025-07-17T07:36:43.7742386Z Args: 2025-07-17T07:36:43.7742690Z optimizer_class (optim.Optimizer): the class of optimizer to 2025-07-17T07:36:43.7743110Z instantiate on each worker. 2025-07-17T07:36:43.7743527Z params_rref (list[RRef]): list of RRefs to local or remote parameters 2025-07-17T07:36:43.7743934Z to optimize. 2025-07-17T07:36:43.7755715Z args: arguments to pass to the optimizer constructor on each worker. 2025-07-17T07:36:43.7756753Z kwargs: arguments to pass to the optimizer constructor on each worker. 2025-07-17T07:36:43.7757102Z 2025-07-17T07:36:43.7757210Z Example:: 2025-07-17T07:36:43.7757604Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:43.7757994Z >>> import torch.distributed.autograd as dist_autograd 2025-07-17T07:36:43.7758399Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:43.7758728Z >>> from torch import optim 2025-07-17T07:36:43.7759115Z >>> from torch.distributed.optim import DistributedOptimizer 2025-07-17T07:36:43.7759504Z >>> 2025-07-17T07:36:43.7759742Z >>> with dist_autograd.context() as context_id: 2025-07-17T07:36:43.7760092Z >>> # Forward pass. 2025-07-17T07:36:43.7760460Z >>> rref1 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 3)) 2025-07-17T07:36:43.7760966Z >>> rref2 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 1)) 2025-07-17T07:36:43.7761407Z >>> loss = rref1.to_here() + rref2.to_here() 2025-07-17T07:36:43.7761730Z >>> 2025-07-17T07:36:43.7761943Z >>> # Backward pass. 2025-07-17T07:36:43.7762251Z >>> dist_autograd.backward(context_id, [loss.sum()]) 2025-07-17T07:36:43.7762601Z >>> 2025-07-17T07:36:43.7762806Z >>> # Optimizer. 2025-07-17T07:36:43.7763072Z >>> dist_optim = DistributedOptimizer( 2025-07-17T07:36:43.7763399Z >>> optim.SGD, 2025-07-17T07:36:43.7763648Z >>> [rref1, rref2], 2025-07-17T07:36:43.7763896Z >>> lr=0.05, 2025-07-17T07:36:43.7764131Z >>> ) 2025-07-17T07:36:43.7764364Z >>> dist_optim.step(context_id) 2025-07-17T07:36:43.7764570Z 2025-07-17T07:36:43.7764727Z __ https://github.com/pytorch/tutorials/pull/1465 2025-07-17T07:36:43.7764999Z 2025-07-17T07:36:43.7765247Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.7765712Z 2025-07-17T07:36:43.7766448Z msg = Cannot scrape callname=PostLocalSGDOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/post_localSGD_optimizer.py line=9. 2025-07-17T07:36:43.7767527Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.7767909Z 2025-07-17T07:36:43.7768303Z Wraps an arbitrary :class:`torch.optim.Optimizer` and runs `post-local SGD `_, 2025-07-17T07:36:43.7768943Z This optimizer runs local optimizer at every step. 2025-07-17T07:36:43.7769540Z After the warm-up stage, it averages parameters periodically after the local optimizer is applied. 2025-07-17T07:36:43.7770185Z 2025-07-17T07:36:43.7770265Z Args: 2025-07-17T07:36:43.7770486Z optim: The local optimizer. 2025-07-17T07:36:43.7770885Z averager: A model averager instance to run post-localSGD algorithm. 2025-07-17T07:36:43.7771231Z 2025-07-17T07:36:43.7771322Z Example:: 2025-07-17T07:36:43.7771440Z 2025-07-17T07:36:43.7771577Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:43.7771894Z >>> import torch 2025-07-17T07:36:43.7772162Z >>> import torch.distributed as dist 2025-07-17T07:36:43.7772656Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-07-17T07:36:43.7773144Z >>> import torch.nn as nn 2025-07-17T07:36:43.7773524Z >>> from torch.distributed.optim import PostLocalSGDOptimizer 2025-07-17T07:36:43.7774101Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-07-17T07:36:43.7774602Z >>> PostLocalSGDState, 2025-07-17T07:36:43.7774987Z >>> post_localSGD_hook, 2025-07-17T07:36:43.7775259Z >>> ) 2025-07-17T07:36:43.7775465Z >>> 2025-07-17T07:36:43.7775721Z >>> model = nn.parallel.DistributedDataParallel( 2025-07-17T07:36:43.7776128Z >>> module, device_ids=[rank], output_device=rank 2025-07-17T07:36:43.7776464Z >>> ) 2025-07-17T07:36:43.7776656Z >>> 2025-07-17T07:36:43.7776917Z >>> # Register a post-localSGD communication hook. 2025-07-17T07:36:43.7777466Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-07-17T07:36:43.7778031Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-07-17T07:36:43.7778393Z >>> 2025-07-17T07:36:43.7778778Z >>> # Create a post-localSGD optimizer that wraps a local optimizer. 2025-07-17T07:36:43.7779349Z >>> # Note that ``warmup_steps`` used in ``PostLocalSGDOptimizer`` must be the same as 2025-07-17T07:36:43.7779870Z >>> # ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-07-17T07:36:43.7780365Z >>> local_optim = torch.optim.SGD(params=model.parameters(), lr=0.01) 2025-07-17T07:36:43.7780814Z >>> opt = PostLocalSGDOptimizer( 2025-07-17T07:36:43.7781118Z >>> optim=local_optim, 2025-07-17T07:36:43.7781549Z >>> averager=averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-07-17T07:36:43.7781999Z >>> ) 2025-07-17T07:36:43.7782190Z >>> 2025-07-17T07:36:43.7782530Z >>> # In the first 100 steps, DDP runs global gradient averaging at every step. 2025-07-17T07:36:43.7783179Z >>> # After 100 steps, DDP runs gradient averaging within each subgroup (intra-node by default), 2025-07-17T07:36:43.7783980Z >>> # and post-localSGD optimizer runs global model averaging every 4 steps after applying the local optimizer. 2025-07-17T07:36:43.7784573Z >>> for step in range(0, 200): 2025-07-17T07:36:43.7784871Z >>> opt.zero_grad() 2025-07-17T07:36:43.7785153Z >>> loss = loss_fn(output, labels) 2025-07-17T07:36:43.7785478Z >>> loss.backward() 2025-07-17T07:36:43.7785739Z >>> opt.step() 2025-07-17T07:36:43.7785887Z 2025-07-17T07:36:43.7786149Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.7786514Z 2025-07-17T07:36:43.7864038Z msg = Cannot scrape callname=ZeroRedundancyOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/zero_redundancy_optimizer.py line=284. 2025-07-17T07:36:43.7865477Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.7865854Z 2025-07-17T07:36:43.7866267Z Wrap an arbitrary :class:`optim.Optimizer ` and shards its states across ranks in the group. 2025-07-17T07:36:43.7866799Z 2025-07-17T07:36:43.7867047Z The sharing is done as described by `ZeRO `_. 2025-07-17T07:36:43.7867417Z 2025-07-17T07:36:43.7867561Z The local optimizer instance in each rank is only 2025-07-17T07:36:43.7868062Z responsible for updating approximately ``1 / world_size`` parameters and 2025-07-17T07:36:43.7868610Z hence only needs to keep ``1 / world_size`` optimizer states. After 2025-07-17T07:36:43.7869168Z parameters are updated locally, each rank will broadcast its parameters to 2025-07-17T07:36:43.7869716Z all other peers to keep all model replicas in the same state. 2025-07-17T07:36:43.7870337Z ``ZeroRedundancyOptimizer`` can be used in conjunction with 2025-07-17T07:36:43.7870896Z :class:`torch.nn.parallel.DistributedDataParallel` to reduce per-rank peak 2025-07-17T07:36:43.7871374Z memory consumption. 2025-07-17T07:36:43.7871520Z 2025-07-17T07:36:43.7871794Z ``ZeroRedundancyOptimizer`` uses a sorted-greedy algorithm to pack a number 2025-07-17T07:36:43.7872389Z of parameters at each rank. Each parameter belongs to a single rank and is 2025-07-17T07:36:43.7872978Z not divided among ranks. The partition is arbitrary and might not match the 2025-07-17T07:36:43.7873468Z the parameter registration or usage order. 2025-07-17T07:36:43.7873860Z 2025-07-17T07:36:43.7873960Z Arguments: 2025-07-17T07:36:43.7874267Z params (``Iterable``): an ``Iterable`` of :class:`torch.Tensor` s 2025-07-17T07:36:43.7874769Z or :class:`dict` s giving all parameters, which will be sharded 2025-07-17T07:36:43.7875173Z across ranks. 2025-07-17T07:36:43.7875324Z 2025-07-17T07:36:43.7875411Z Keyword Args: 2025-07-17T07:36:43.7875765Z optimizer_class (:class:`torch.nn.Optimizer`): the class of the local 2025-07-17T07:36:43.7876198Z optimizer. 2025-07-17T07:36:43.7876551Z process_group (``ProcessGroup``, optional): ``torch.distributed`` 2025-07-17T07:36:43.7877136Z ``ProcessGroup`` (default: ``dist.group.WORLD`` initialized by 2025-07-17T07:36:43.7877603Z :meth:`torch.distributed.init_process_group`). 2025-07-17T07:36:43.7878093Z parameters_as_bucket_view (bool, optional): if ``True``, parameters are 2025-07-17T07:36:43.7878639Z packed into buckets to speed up communication, and ``param.data`` 2025-07-17T07:36:43.7879183Z fields point to bucket views at different offsets; if ``False``, 2025-07-17T07:36:43.7879711Z each individual parameter is communicated separately, and each 2025-07-17T07:36:43.7880181Z ``params.data`` stays intact (default: ``False``). 2025-07-17T07:36:43.7880626Z overlap_with_ddp (bool, optional): if ``True``, :meth:`step` is 2025-07-17T07:36:43.7881133Z overlapped with :class:`DistributedDataParallel` 's gradient 2025-07-17T07:36:43.7881663Z synchronization; this requires (1) either a functional optimizer 2025-07-17T07:36:43.7882164Z for the ``optimizer_class`` argument or one with a functional 2025-07-17T07:36:43.7882645Z equivalent and (2) registering a DDP communication hook 2025-07-17T07:36:43.7883137Z constructed from one of the functions in ``ddp_zero_hook.py``; 2025-07-17T07:36:43.7883605Z parameters are packed into buckets matching those in 2025-07-17T07:36:43.7884039Z :class:`DistributedDataParallel`, meaning that the 2025-07-17T07:36:43.7884462Z ``parameters_as_bucket_view`` argument is ignored. 2025-07-17T07:36:43.7884912Z If ``False``, :meth:`step` runs disjointly after the backward pass 2025-07-17T07:36:43.7885297Z (per normal). 2025-07-17T07:36:43.7885627Z (default: ``False``) 2025-07-17T07:36:43.7886019Z **defaults: any trailing arguments, which are forwarded to the local 2025-07-17T07:36:43.7886423Z optimizer. 2025-07-17T07:36:43.7886575Z 2025-07-17T07:36:43.7886666Z Example:: 2025-07-17T07:36:43.7886786Z 2025-07-17T07:36:43.7886892Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.7887162Z >>> import torch.nn as nn 2025-07-17T07:36:43.7887538Z >>> from torch.distributed.optim import ZeroRedundancyOptimizer 2025-07-17T07:36:43.7888054Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-07-17T07:36:43.7888597Z >>> model = nn.Sequential(*[nn.Linear(2000, 2000).to(rank) for _ in range(20)]) 2025-07-17T07:36:43.7889055Z >>> ddp = DDP(model, device_ids=[rank]) 2025-07-17T07:36:43.7889397Z >>> opt = ZeroRedundancyOptimizer( 2025-07-17T07:36:43.7889719Z >>> ddp.parameters(), 2025-07-17T07:36:43.7890014Z >>> optimizer_class=torch.optim.Adam, 2025-07-17T07:36:43.7890332Z >>> lr=0.01 2025-07-17T07:36:43.7890557Z >>> ) 2025-07-17T07:36:43.7890766Z >>> ddp(inputs).sum().backward() 2025-07-17T07:36:43.7891061Z >>> opt.step() 2025-07-17T07:36:43.7891214Z 2025-07-17T07:36:43.7891298Z .. warning:: 2025-07-17T07:36:43.7891639Z Currently, ``ZeroRedundancyOptimizer`` requires that all of the 2025-07-17T07:36:43.7892094Z passed-in parameters are the same dense type. 2025-07-17T07:36:43.7892364Z 2025-07-17T07:36:43.7892448Z .. warning:: 2025-07-17T07:36:43.7892786Z If you pass ``overlap_with_ddp=True``, be wary of the following: Given 2025-07-17T07:36:43.7893303Z the way that overlapping :class:`DistributedDataParallel` with 2025-07-17T07:36:43.7893861Z :class:`ZeroRedundancyOptimizer` is currently implemented, the first 2025-07-17T07:36:43.7894562Z two or three training iterations do not perform parameter updates in 2025-07-17T07:36:43.7895073Z the optimizer step, depending on if ``static_graph=False`` or 2025-07-17T07:36:43.7895560Z ``static_graph=True``, respectively. This is because it needs 2025-07-17T07:36:43.7896040Z information about the gradient bucketing strategy used by 2025-07-17T07:36:43.7896561Z :class:`DistributedDataParallel`, which is not finalized until the 2025-07-17T07:36:43.7897083Z second forward pass if ``static_graph=False`` or until the third 2025-07-17T07:36:43.7897657Z forward pass if ``static_graph=True``. To adjust for this, one option 2025-07-17T07:36:43.7898093Z is to prepend dummy inputs. 2025-07-17T07:36:43.7898280Z 2025-07-17T07:36:43.7898532Z .. warning:: ZeroRedundancyOptimizer is experimental and subject to change. 2025-07-17T07:36:43.7898911Z 2025-07-17T07:36:43.7899161Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.7899541Z 2025-07-17T07:36:43.8165262Z msg = Cannot scrape callname=_CustomReducer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py line=29. 2025-07-17T07:36:43.8166348Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.8166723Z 2025-07-17T07:36:43.8166965Z Custom reducer class that can be used to specify a custom operation that 2025-07-17T07:36:43.8167549Z reduces losses of multiple microbatches into one value. 2025-07-17T07:36:43.8167839Z 2025-07-17T07:36:43.8167924Z Example: 2025-07-17T07:36:43.8168137Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.8168406Z >>> sum_reducer = _CustomReducer( 2025-07-17T07:36:43.8168705Z >>> torch.tensor(0.0), 2025-07-17T07:36:43.8168971Z >>> lambda a, b: a + b 2025-07-17T07:36:43.8169206Z >>> ) 2025-07-17T07:36:43.8169330Z 2025-07-17T07:36:43.8169580Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.8170096Z 2025-07-17T07:36:43.8667797Z msg = Cannot scrape callname=async_execution in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/functions.py line=6. 2025-07-17T07:36:43.8669229Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.8669625Z 2025-07-17T07:36:43.8669867Z A decorator for a function indicating that the return value of the function 2025-07-17T07:36:43.8670564Z is guaranteed to be a :class:`~torch.futures.Future` object and this 2025-07-17T07:36:43.8671118Z function can run asynchronously on the RPC callee. More specifically, the 2025-07-17T07:36:43.8671733Z callee extracts the :class:`~torch.futures.Future` returned by the wrapped 2025-07-17T07:36:43.8672321Z function and installs subsequent processing steps as a callback to that 2025-07-17T07:36:43.8672903Z :class:`~torch.futures.Future`. The installed callback will read the value 2025-07-17T07:36:43.8673443Z from the :class:`~torch.futures.Future` when completed and send the 2025-07-17T07:36:43.8673940Z value back as the RPC response. That also means the returned 2025-07-17T07:36:43.8674461Z :class:`~torch.futures.Future` only exists on the callee side and is never 2025-07-17T07:36:43.8675019Z sent through RPC. This decorator is useful when the wrapped function's 2025-07-17T07:36:43.8675552Z (``fn``) execution needs to pause and resume due to, e.g., containing 2025-07-17T07:36:43.8676087Z :meth:`~torch.distributed.rpc.rpc_async` or waiting for other signals. 2025-07-17T07:36:43.8676423Z 2025-07-17T07:36:43.8676658Z .. note:: To enable asynchronous execution, applications must pass the 2025-07-17T07:36:43.8677209Z function object returned by this decorator to RPC APIs. If RPC detected 2025-07-17T07:36:43.8677771Z attributes installed by this decorator, it knows that this function 2025-07-17T07:36:43.8678290Z returns a ``Future`` object and will handle that accordingly. 2025-07-17T07:36:43.8679094Z However, this does not mean this decorator has to be outmost one when 2025-07-17T07:36:43.8679652Z defining a function. For example, when combined with ``@staticmethod`` 2025-07-17T07:36:43.8680208Z or ``@classmethod``, ``@rpc.functions.async_execution`` needs to be the 2025-07-17T07:36:43.8680755Z inner decorator to allow the target function be recognized as a static 2025-07-17T07:36:43.8681305Z or class function. This target function can still execute asynchronously 2025-07-17T07:36:43.8681877Z because, when accessed, the static or class method preserves attributes 2025-07-17T07:36:43.8682375Z installed by ``@rpc.functions.async_execution``. 2025-07-17T07:36:43.8682634Z 2025-07-17T07:36:43.8682728Z 2025-07-17T07:36:43.8682832Z Example:: 2025-07-17T07:36:43.8683141Z The returned :class:`~torch.futures.Future` object can come from 2025-07-17T07:36:43.8683589Z :meth:`~torch.distributed.rpc.rpc_async`, 2025-07-17T07:36:43.8684052Z :meth:`~torch.futures.Future.then`, or :class:`~torch.futures.Future` 2025-07-17T07:36:43.8684565Z constructor. The example below shows directly using the 2025-07-17T07:36:43.8684989Z :class:`~torch.futures.Future` returned by 2025-07-17T07:36:43.8685424Z :meth:`~torch.futures.Future.then`. 2025-07-17T07:36:43.8685646Z 2025-07-17T07:36:43.8685775Z >>> from torch.distributed import rpc 2025-07-17T07:36:43.8686071Z >>> 2025-07-17T07:36:43.8686298Z >>> # omitting setup and shutdown RPC 2025-07-17T07:36:43.8686604Z >>> 2025-07-17T07:36:43.8686797Z >>> # On all workers 2025-07-17T07:36:43.8687074Z >>> @rpc.functions.async_execution 2025-07-17T07:36:43.8687401Z >>> def async_add_chained(to, x, y, z): 2025-07-17T07:36:43.8687801Z >>> # This function runs on "worker1" and returns immediately when 2025-07-17T07:36:43.8688296Z >>> # the callback is installed through the `then(cb)` API. In the 2025-07-17T07:36:43.8688806Z >>> # mean time, the `rpc_async` to "worker2" can run concurrently. 2025-07-17T07:36:43.8689257Z >>> # When the return value of that `rpc_async` arrives at 2025-07-17T07:36:43.8689715Z >>> # "worker1", "worker1" will run the lambda function accordingly 2025-07-17T07:36:43.8690249Z >>> # and set the value for the previously returned `Future`, which 2025-07-17T07:36:43.8690732Z >>> # will then trigger RPC to send the result back to "worker0". 2025-07-17T07:36:43.8691188Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-07-17T07:36:43.8691580Z >>> lambda fut: fut.wait() + z 2025-07-17T07:36:43.8691879Z >>> ) 2025-07-17T07:36:43.8692078Z >>> 2025-07-17T07:36:43.8692280Z >>> # On worker0 2025-07-17T07:36:43.8692528Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.8692780Z >>> ret = rpc.rpc_sync( 2025-07-17T07:36:43.8693042Z >>> "worker1", 2025-07-17T07:36:43.8693289Z >>> async_add_chained, 2025-07-17T07:36:43.8693573Z >>> args=("worker2", torch.ones(2), 1, 1) 2025-07-17T07:36:43.8693889Z >>> ) 2025-07-17T07:36:43.8694121Z >>> print(ret) # prints tensor([3., 3.]) 2025-07-17T07:36:43.8694343Z 2025-07-17T07:36:43.8694575Z When combined with TorchScript decorators, this decorator must be the 2025-07-17T07:36:43.8694996Z outmost one. 2025-07-17T07:36:43.8695145Z 2025-07-17T07:36:43.8695247Z >>> from torch import Tensor 2025-07-17T07:36:43.8695553Z >>> from torch.futures import Future 2025-07-17T07:36:43.8695879Z >>> from torch.distributed import rpc 2025-07-17T07:36:43.8696187Z >>> 2025-07-17T07:36:43.8696411Z >>> # omitting setup and shutdown RPC 2025-07-17T07:36:43.8696703Z >>> 2025-07-17T07:36:43.8696909Z >>> # On all workers 2025-07-17T07:36:43.8697174Z >>> @torch.jit.script 2025-07-17T07:36:43.8697475Z >>> def script_add(x: Tensor, y: Tensor) -> Tensor: 2025-07-17T07:36:43.8697816Z >>> return x + y 2025-07-17T07:36:43.8698056Z >>> 2025-07-17T07:36:43.8698284Z >>> @rpc.functions.async_execution 2025-07-17T07:36:43.8698677Z >>> @torch.jit.script 2025-07-17T07:36:43.8699031Z >>> def async_add(to: str, x: Tensor, y: Tensor) -> Future[Tensor]: 2025-07-17T07:36:43.8699471Z >>> return rpc.rpc_async(to, script_add, (x, y)) 2025-07-17T07:36:43.8699792Z >>> 2025-07-17T07:36:43.8699991Z >>> # On worker0 2025-07-17T07:36:43.8700232Z >>> ret = rpc.rpc_sync( 2025-07-17T07:36:43.8700481Z >>> "worker1", 2025-07-17T07:36:43.8700720Z >>> async_add, 2025-07-17T07:36:43.8700991Z >>> args=("worker2", torch.ones(2), 1) 2025-07-17T07:36:43.8701291Z >>> ) 2025-07-17T07:36:43.8701532Z >>> print(ret) # prints tensor([2., 2.]) 2025-07-17T07:36:43.8701754Z 2025-07-17T07:36:43.8702067Z When combined with static or class method, this decorator must be the 2025-07-17T07:36:43.8702498Z inner one. 2025-07-17T07:36:43.8702627Z 2025-07-17T07:36:43.8702741Z >>> from torch.distributed import rpc 2025-07-17T07:36:43.8703048Z >>> 2025-07-17T07:36:43.8703274Z >>> # omitting setup and shutdown RPC 2025-07-17T07:36:43.8703567Z >>> 2025-07-17T07:36:43.8703771Z >>> # On all workers 2025-07-17T07:36:43.8704040Z >>> class AsyncExecutionClass: 2025-07-17T07:36:43.8704312Z >>> 2025-07-17T07:36:43.8704519Z >>> @staticmethod 2025-07-17T07:36:43.8704801Z >>> @rpc.functions.async_execution 2025-07-17T07:36:43.8705125Z >>> def static_async_add(to, x, y, z): 2025-07-17T07:36:43.8705522Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-07-17T07:36:43.8705920Z >>> lambda fut: fut.wait() + z 2025-07-17T07:36:43.8706213Z >>> ) 2025-07-17T07:36:43.8706433Z >>> 2025-07-17T07:36:43.8706639Z >>> @classmethod 2025-07-17T07:36:43.8706914Z >>> @rpc.functions.async_execution 2025-07-17T07:36:43.8707243Z >>> def class_async_add(cls, to, x, y, z): 2025-07-17T07:36:43.8707596Z >>> ret_fut = torch.futures.Future() 2025-07-17T07:36:43.8707969Z >>> rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-07-17T07:36:43.8708368Z >>> lambda fut: ret_fut.set_result(fut.wait() + z) 2025-07-17T07:36:43.8708711Z >>> ) 2025-07-17T07:36:43.8708940Z >>> return ret_fut 2025-07-17T07:36:43.8709187Z >>> 2025-07-17T07:36:43.8709413Z >>> @rpc.functions.async_execution 2025-07-17T07:36:43.8709757Z >>> def bound_async_add(self, to, x, y, z): 2025-07-17T07:36:43.8710149Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-07-17T07:36:43.8710545Z >>> lambda fut: fut.wait() + z 2025-07-17T07:36:43.8710848Z >>> ) 2025-07-17T07:36:43.8711063Z >>> 2025-07-17T07:36:43.8711253Z >>> # On worker0 2025-07-17T07:36:43.8711494Z >>> ret = rpc.rpc_sync( 2025-07-17T07:36:43.8711753Z >>> "worker1", 2025-07-17T07:36:43.8712018Z >>> AsyncExecutionClass.static_async_add, 2025-07-17T07:36:43.8712140Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-07-17T07:36:43.8712223Z >>> ) 2025-07-17T07:36:43.8712336Z >>> print(ret) # prints tensor([4., 4.]) 2025-07-17T07:36:43.8712427Z >>> 2025-07-17T07:36:43.8712521Z >>> ret = rpc.rpc_sync( 2025-07-17T07:36:43.8712604Z >>> "worker1", 2025-07-17T07:36:43.8712737Z >>> AsyncExecutionClass.class_async_add, 2025-07-17T07:36:43.8712846Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-07-17T07:36:43.8712925Z >>> ) 2025-07-17T07:36:43.8713048Z >>> print(ret) # prints tensor([4., 4.]) 2025-07-17T07:36:43.8713052Z 2025-07-17T07:36:43.8713211Z This decorator also works with RRef helpers, i.e., . 2025-07-17T07:36:43.8713359Z :meth:`torch.distributed.rpc.RRef.rpc_sync`, 2025-07-17T07:36:43.8713514Z :meth:`torch.distributed.rpc.RRef.rpc_async`, and 2025-07-17T07:36:43.8713659Z :meth:`torch.distributed.rpc.RRef.remote`. 2025-07-17T07:36:43.8713664Z 2025-07-17T07:36:43.8713845Z >>> from torch.distributed import rpc 2025-07-17T07:36:43.8713962Z >>> 2025-07-17T07:36:43.8714252Z >>> # reuse the AsyncExecutionClass class above 2025-07-17T07:36:43.8714416Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-07-17T07:36:43.8714654Z >>> ret = rref.rpc_sync().static_async_add("worker2", torch.ones(2), 1, 2) 2025-07-17T07:36:43.8714838Z >>> print(ret) # prints tensor([4., 4.]) 2025-07-17T07:36:43.8714947Z >>> 2025-07-17T07:36:43.8715164Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-07-17T07:36:43.8715598Z >>> ret = rref.rpc_async().static_async_add("worker2", torch.ones(2), 1, 2).wait() 2025-07-17T07:36:43.8715817Z >>> print(ret) # prints tensor([4., 4.]) 2025-07-17T07:36:43.8715969Z >>> 2025-07-17T07:36:43.8716240Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-07-17T07:36:43.8716468Z >>> ret = rref.remote().static_async_add("worker2", torch.ones(2), 1, 2).to_here() 2025-07-17T07:36:43.8716592Z >>> print(ret) # prints tensor([4., 4.]) 2025-07-17T07:36:43.8716597Z 2025-07-17T07:36:43.8716853Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.8716858Z 2025-07-17T07:36:43.8717634Z msg = Cannot scrape callname=TensorPipeRpcBackendOptions.set_device_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/options.py line=113. 2025-07-17T07:36:43.8717892Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.8717896Z 2025-07-17T07:36:43.8718094Z Set device mapping between each RPC caller and callee pair. This 2025-07-17T07:36:43.8718281Z function can be called multiple times to incrementally add 2025-07-17T07:36:43.8718392Z device placement configurations. 2025-07-17T07:36:43.8718397Z 2025-07-17T07:36:43.8718480Z Args: 2025-07-17T07:36:43.8718587Z to (str): Callee name. 2025-07-17T07:36:43.8718779Z device_map (Dict of int, str, or torch.device): Device placement 2025-07-17T07:36:43.8718969Z mappings from this worker to the callee. This map must be 2025-07-17T07:36:43.8719059Z invertible. 2025-07-17T07:36:43.8719064Z 2025-07-17T07:36:43.8719145Z Example: 2025-07-17T07:36:43.8719266Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:43.8719351Z >>> # both workers 2025-07-17T07:36:43.8719437Z >>> def add(x, y): 2025-07-17T07:36:43.8719582Z >>> print(x) # tensor([1., 1.], device='cuda:1') 2025-07-17T07:36:43.8719681Z >>> return x + y, (x + y).to(2) 2025-07-17T07:36:43.8719761Z >>> 2025-07-17T07:36:43.8719861Z >>> # on worker 0 2025-07-17T07:36:43.8719995Z >>> options = TensorPipeRpcBackendOptions( 2025-07-17T07:36:43.8720107Z >>> num_worker_threads=8, 2025-07-17T07:36:43.8720217Z >>> device_maps={"worker1": {0: 1}} 2025-07-17T07:36:43.8720344Z >>> # maps worker0's cuda:0 to worker1's cuda:1 2025-07-17T07:36:43.8720437Z >>> ) 2025-07-17T07:36:43.8720561Z >>> options.set_device_map("worker1", {1: 2}) 2025-07-17T07:36:43.8720681Z >>> # maps worker0's cuda:1 to worker1's cuda:2 2025-07-17T07:36:43.8720778Z >>> 2025-07-17T07:36:43.8720866Z >>> rpc.init_rpc( 2025-07-17T07:36:43.8720950Z >>> "worker0", 2025-07-17T07:36:43.8721044Z >>> rank=0, 2025-07-17T07:36:43.8721133Z >>> world_size=2, 2025-07-17T07:36:43.8721256Z >>> backend=rpc.BackendType.TENSORPIPE, 2025-07-17T07:36:43.8721371Z >>> rpc_backend_options=options 2025-07-17T07:36:43.8721450Z >>> ) 2025-07-17T07:36:43.8721541Z >>> 2025-07-17T07:36:43.8721631Z >>> x = torch.ones(2) 2025-07-17T07:36:43.8721785Z >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1)) 2025-07-17T07:36:43.8721977Z >>> # The first argument will be moved to cuda:1 on worker1. When 2025-07-17T07:36:43.8722161Z >>> # sending the return value back, it will follow the invert of 2025-07-17T07:36:43.8722331Z >>> # the device map, and hence will be moved back to cuda:0 and 2025-07-17T07:36:43.8722435Z >>> # cuda:1 on worker0 2025-07-17T07:36:43.8722576Z >>> print(rets[0]) # tensor([2., 2.], device='cuda:0') 2025-07-17T07:36:43.8722789Z >>> print(rets[1]) # tensor([2., 2.], device='cuda:1') 2025-07-17T07:36:43.8722794Z 2025-07-17T07:36:43.8723043Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.8723047Z 2025-07-17T07:36:43.8746874Z msg = Cannot scrape callname=_server_process_global_profile in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/server_process_global_profiler.py line=19. 2025-07-17T07:36:43.8747141Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.8747146Z 2025-07-17T07:36:43.8747341Z It has the same API as ``torch.autograd.profiler.profile`` class, 2025-07-17T07:36:43.8747734Z except that it enables profiling on all threads running RPC server request callbacks. 2025-07-17T07:36:43.8747740Z 2025-07-17T07:36:43.8748017Z Context manager that manages autograd profiler state and holds a summary of results. 2025-07-17T07:36:43.8748263Z Under the hood it just records events of functions being executed in C++ and 2025-07-17T07:36:43.8748496Z exposes those events to Python. You can wrap any code into it and it will 2025-07-17T07:36:43.8748664Z only report runtime of PyTorch functions. 2025-07-17T07:36:43.8748936Z Note: profiler is thread local and is automatically propagated into the async tasks 2025-07-17T07:36:43.8748940Z 2025-07-17T07:36:43.8749018Z Args: 2025-07-17T07:36:43.8749294Z enabled (bool, optional): Setting this to False makes this context manager a no-op. 2025-07-17T07:36:43.8749388Z Default: ``True``. 2025-07-17T07:36:43.8749393Z 2025-07-17T07:36:43.8749675Z use_cuda (bool, optional): Enables timing of CUDA events as well using the cudaEvent API. 2025-07-17T07:36:43.8749883Z Adds approximately 4us of overhead to each tensor operation. 2025-07-17T07:36:43.8749974Z Default: ``False`` 2025-07-17T07:36:43.8749979Z 2025-07-17T07:36:43.8750213Z record_shapes (bool, optional): If shapes recording is set, information 2025-07-17T07:36:43.8750441Z about input dimensions will be collected. This allows one to see which 2025-07-17T07:36:43.8750647Z dimensions have been used under the hood and further group by them 2025-07-17T07:36:43.8750871Z using prof.key_averages(group_by_input_shape=True). Please note that 2025-07-17T07:36:43.8751090Z shape recording might skew your profiling data. It is recommended to 2025-07-17T07:36:43.8751320Z use separate runs with and without shape recording to validate the timing. 2025-07-17T07:36:43.8751551Z Most likely the skew will be negligible for bottom most events (in a case 2025-07-17T07:36:43.8751764Z of nested function calls). But for higher level functions the total 2025-07-17T07:36:43.8751972Z self cpu time might be artificially increased because of the shape 2025-07-17T07:36:43.8752057Z collection. 2025-07-17T07:36:43.8752062Z 2025-07-17T07:36:43.8752323Z profile_memory (bool, optional): Whether to report memory usage, default: ``False`` 2025-07-17T07:36:43.8752333Z 2025-07-17T07:36:43.8752436Z .. warning:: 2025-07-17T07:36:43.8752635Z Enabling memory profiling incurs additional profiler overhead 2025-07-17T07:36:43.8752639Z 2025-07-17T07:36:43.8752756Z .. warning:: 2025-07-17T07:36:43.8753040Z Due to some CUDA multiprocessing limitations (see :ref:`multiprocessing-cuda-note`), 2025-07-17T07:36:43.8753231Z one cannot use the profiler with ``use_cuda = True`` to benchmark 2025-07-17T07:36:43.8753472Z DataLoaders with ``num_workers > 0``. If you wish to benchmark data loading, 2025-07-17T07:36:43.8753630Z please use ``use_cuda = False`` or ``num_workers = 0``. 2025-07-17T07:36:43.8753634Z 2025-07-17T07:36:43.8753734Z Example: 2025-07-17T07:36:43.8753828Z >>> # xdoctest: +SKIP 2025-07-17T07:36:43.8753913Z >>> # On worker 0: 2025-07-17T07:36:43.8754014Z >>> import torch 2025-07-17T07:36:43.8754134Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:43.8754269Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-07-17T07:36:43.8754460Z >>> x, y = torch.tensor(1), torch.tensor(2) 2025-07-17T07:36:43.8754570Z >>> outer_profile_rref = rpc.remote( 2025-07-17T07:36:43.8754731Z ... dst_worker_name, rpc._server_process_global_profile 2025-07-17T07:36:43.8754823Z ... ) 2025-07-17T07:36:43.8754947Z >>> outer_profile_rref.rpc_sync().__enter__() 2025-07-17T07:36:43.8755107Z >>> rpc.rpc_sync(dst_worker_name, torch.add, (x, y)) 2025-07-17T07:36:43.8755218Z >>> inner_profile_rref = rpc.remote( 2025-07-17T07:36:43.8755372Z ... dst_worker_name, rpc._server_process_global_profile 2025-07-17T07:36:43.8755468Z ... ) 2025-07-17T07:36:43.8755642Z >>> inner_profile_rref.rpc_sync().__enter__() 2025-07-17T07:36:43.8755789Z >>> rpc.rpc_sync(dst_worker_name, torch.sub, (x, y)) 2025-07-17T07:36:43.8755971Z >>> inner_profile_rref.rpc_sync().__exit__(None, None, None) 2025-07-17T07:36:43.8756139Z >>> outer_profile_rref.rpc_sync().__exit__(None, None, None) 2025-07-17T07:36:43.8756298Z >>> print(inner_profile_rref.rpc_sync().key_averages()) 2025-07-17T07:36:43.8756539Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:43.8756844Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-07-17T07:36:43.8757077Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:43.8757262Z sub 85.06% 76.275us 100.00% 89.667us 89.667us 1 2025-07-17T07:36:43.8757450Z empty 14.94% 13.392us 14.94% 13.392us 13.392us 1 2025-07-17T07:36:43.8757678Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:43.8757782Z Self CPU time total: 89.667us 2025-07-17T07:36:43.8757953Z >>> print(outer_profile_rref.rpc_sync().key_averages()) 2025-07-17T07:36:43.8758169Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:43.8758467Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-07-17T07:36:43.8758694Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:43.8758868Z sub 35.65% 76.275us 41.91% 89.667us 89.667us 1 2025-07-17T07:36:43.8759064Z empty 12.67% 27.101us 12.67% 27.101us 13.551us 2 2025-07-17T07:36:43.8759236Z add 51.68% 110.550us 58.09% 124.259us 124.259us 1 2025-07-17T07:36:43.8759453Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:43.8759570Z Self CPU time total: 213.926us 2025-07-17T07:36:43.8759664Z >>> rpc.shutdown() 2025-07-17T07:36:43.8759669Z 2025-07-17T07:36:43.8759755Z >>> # On worker 1: 2025-07-17T07:36:43.8759889Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:43.8760023Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-07-17T07:36:43.8760189Z >>> # wait for worker 0 to finish work, and then shutdown. 2025-07-17T07:36:43.8760280Z >>> rpc.shutdown() 2025-07-17T07:36:43.8760285Z 2025-07-17T07:36:43.8760536Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:43.8760540Z 2025-07-17T07:36:43.9989830Z msg = Cannot scrape callname=local_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_func_map.py line=35. 2025-07-17T07:36:43.9990102Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:43.9990311Z 2025-07-17T07:36:43.9990593Z :meth:`local_map` is an experimental API that allows users to pass :class:`DTensor` s 2025-07-17T07:36:43.9990874Z to a function that is written to be applied on ``torch.Tensor`` s. It is done by extracting 2025-07-17T07:36:43.9991150Z the local components of :class:`DTensor`, call the function, and wrap the outputs to 2025-07-17T07:36:43.9991307Z :class:`DTensor` according to the ``out_placements``. 2025-07-17T07:36:43.9991312Z 2025-07-17T07:36:43.9991391Z Args: 2025-07-17T07:36:43.9991609Z func (Callable): the function to be applied on each local shard of 2025-07-17T07:36:43.9991707Z :class:`DTensor` s. 2025-07-17T07:36:43.9992017Z out_placements (Union[`PlacementType`, Tuple[`PlacementType`, ...]]): 2025-07-17T07:36:43.9992281Z the desired placements of the :class:`DTensor` s in ``func``'s flattened output. 2025-07-17T07:36:43.9992516Z If the flattened ``output`` is a single value, the ``out_placements`` should be 2025-07-17T07:36:43.9992786Z of type `PlacementType`. Otherwise if the flattened ``output`` has multiple 2025-07-17T07:36:43.9993030Z values, the ``out_placements`` should be a tuple of `PlacementType` values 1:1 2025-07-17T07:36:43.9993149Z mapping to the flattened ``output``. 2025-07-17T07:36:43.9993364Z Besides, for :class:`Tensor` output, we use `PlacementType` as its 2025-07-17T07:36:43.9993636Z placements (a `Tuple[Placement]` value). For non-Tensor output, the `PlacementType` 2025-07-17T07:36:43.9993745Z should be `None`. 2025-07-17T07:36:43.9993978Z Note that the only exception is when no :class:`DTensor` argument is passed 2025-07-17T07:36:43.9994199Z in. In this case, even if `out_placements` is not `None`, the result function 2025-07-17T07:36:43.9994465Z should ignore the desired placements because the function is not running with 2025-07-17T07:36:43.9994560Z :class:`DTensor` s. 2025-07-17T07:36:43.9994722Z in_placements (Tuple[`PlacementType`, ...], optional): 2025-07-17T07:36:43.9995016Z the required placements of the :class:`DTensor` s in the flattened inputs of ``func``. 2025-07-17T07:36:43.9995245Z If ``in_placements`` is specified, :meth:`local_map` would examine whether the 2025-07-17T07:36:43.9995485Z placements of each :class:`DTensor` argument is the same as the required 2025-07-17T07:36:43.9995665Z placements or not. If the placements are not the same and 2025-07-17T07:36:43.9995906Z ``redistribute_inputs`` is ``False``, an exception will be raised. Otherwise if 2025-07-17T07:36:43.9996160Z ``redistribute_inputs`` is ``True``, the argument will be first redistributed to 2025-07-17T07:36:43.9996418Z the required sharding placements before passing its local tensor to ``func``. 2025-07-17T07:36:43.9996656Z The only exception is when required placements are not ``None`` and the 2025-07-17T07:36:43.9996891Z argument is a :class:`torch.Tensor`. In this case, the placements examination 2025-07-17T07:36:43.9997107Z will be skipped and the argument will be directly passed to ``func``. 2025-07-17T07:36:43.9997339Z If ``in_placements`` is ``None``, no placements examination will be performed. 2025-07-17T07:36:43.9997430Z Default: None 2025-07-17T07:36:43.9997611Z in_grad_placements (Tuple[`PlacementType`, ...], optional): 2025-07-17T07:36:43.9997832Z the placements hint of the :class:`DTensor` s gradient corresponds 2025-07-17T07:36:43.9998039Z to the flattened input DTensor. This argument is the hint that user 2025-07-17T07:36:43.9998234Z can give to :meth:`to_local` in case the gradient layout of the 2025-07-17T07:36:43.9998451Z local tensor input does not match its :class:`DTensor` input layout. 2025-07-17T07:36:43.9998647Z If not specified, we will assume the gradient layout of the local 2025-07-17T07:36:43.9998875Z tensor input remains the same as the original :class:`DTensor` input 2025-07-17T07:36:43.9999091Z and use that for gradient computation. Default: None. 2025-07-17T07:36:43.9999226Z device_mesh (:class:`DeviceMesh`, optional): 2025-07-17T07:36:43.9999458Z the device mesh that the output :class:`DTensor` s are placed on. If not 2025-07-17T07:36:43.9999709Z specified, this will be inferred from the first input :class:`DTensor`'s device 2025-07-17T07:36:43.9999819Z mesh. Default: None. 2025-07-17T07:36:43.9999824Z 2025-07-17T07:36:43.9999909Z Keyword Args: 2025-07-17T07:36:44.0000029Z redistribute_inputs (bool, optional): 2025-07-17T07:36:44.0000292Z the bool value indicating whether to reshard the input :class:`DTensor` s when 2025-07-17T07:36:44.0000604Z their placements are different from the required input placements. If this 2025-07-17T07:36:44.0000828Z value is ``False`` and some :class:`DTensor` input has a different placement, 2025-07-17T07:36:44.0001002Z an exception will be raised. Default: False. 2025-07-17T07:36:44.0001011Z 2025-07-17T07:36:44.0001095Z Returns: 2025-07-17T07:36:44.0001355Z A ``Callable`` that applies ``func`` to each local shard of the input :class:`DTensor` 2025-07-17T07:36:44.0001591Z and returns a :class:`DTensor` constructed from the return value of ``func``. 2025-07-17T07:36:44.0001596Z 2025-07-17T07:36:44.0001689Z Raises: 2025-07-17T07:36:44.0001927Z AssertionError: For any non-DTensor output, we require its corresponding 2025-07-17T07:36:44.0002179Z output placement in ``out_placements`` be None. An AssertionError will be raised 2025-07-17T07:36:44.0002293Z if this is not the case. 2025-07-17T07:36:44.0002297Z 2025-07-17T07:36:44.0002558Z ValueError: If ``redistribute_inputs=False`` but the input :class:`DTensor` needs 2025-07-17T07:36:44.0002705Z a redistribution according to ``in_placements``. 2025-07-17T07:36:44.0002710Z 2025-07-17T07:36:44.0002805Z Example: 2025-07-17T07:36:44.0002914Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:44.0003063Z >>> def mm_allreduce_forward(device_mesh, W, X): 2025-07-17T07:36:44.0003179Z >>> partial_sum_tensor = torch.mm(W, X) 2025-07-17T07:36:44.0003416Z >>> reduced_tensor = funcol.all_reduce(partial_sum_tensor, "sum", device_mesh) 2025-07-17T07:36:44.0003527Z >>> return reduced_tensor 2025-07-17T07:36:44.0003608Z >>> 2025-07-17T07:36:44.0003731Z >>> W = torch.randn(12, 8, requires_grad=False) 2025-07-17T07:36:44.0003861Z >>> X = torch.randn(8, 16, requires_grad=False) 2025-07-17T07:36:44.0003953Z >>> Y = torch.mm(W, X) 2025-07-17T07:36:44.0004136Z >>> row_wise = [Shard(0)] # row-wise sharding placements on 1-d mesh 2025-07-17T07:36:44.0004329Z >>> col_wise = [Shard(1)] # col-wise sharding placements on 1-d mesh 2025-07-17T07:36:44.0004407Z >>> 2025-07-17T07:36:44.0004684Z >>> # local_mm_allreduce_forward is the function wrapped with DTensor/Tensor convertion 2025-07-17T07:36:44.0004805Z >>> local_mm_allreduce_forward = local_map( 2025-07-17T07:36:44.0004911Z >>> mm_allreduce_forward, 2025-07-17T07:36:44.0005032Z >>> out_placements=[Replicate()], 2025-07-17T07:36:44.0005146Z >>> in_placements=[col_wise, row_wise], 2025-07-17T07:36:44.0005247Z >>> device_mesh=device_mesh, 2025-07-17T07:36:44.0005420Z >>> ) 2025-07-17T07:36:44.0005501Z >>> 2025-07-17T07:36:44.0005600Z >>> W_dt = distribute_tensor( 2025-07-17T07:36:44.0005714Z ... W, device_mesh, (col_wise) 2025-07-17T07:36:44.0005820Z ... ) # col-wisely sharded W tensor 2025-07-17T07:36:44.0005930Z >>> X_dt = distribute_tensor( 2025-07-17T07:36:44.0006029Z ... X, device_mesh, (row_wise) 2025-07-17T07:36:44.0006136Z ... ) # row-wisely sharded X tensor 2025-07-17T07:36:44.0006256Z >>> Y_dt = local_mm_allreduce_forward( 2025-07-17T07:36:44.0006354Z ... device_mesh, W_dt, X_dt 2025-07-17T07:36:44.0006496Z ... ) # apply local_mm_allreduce_forward to DTensors 2025-07-17T07:36:44.0006500Z 2025-07-17T07:36:44.0006808Z .. note:: This API is currently experimental and subject to change 2025-07-17T07:36:44.0006815Z 2025-07-17T07:36:44.0007103Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.0007108Z 2025-07-17T07:36:44.0009444Z msg = Cannot scrape callname=register_sharding in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_register_sharding.py line=25. 2025-07-17T07:36:44.0009710Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.0009715Z 2025-07-17T07:36:44.0010005Z :meth:`register_sharding` is an experimental API that allows users to register sharding 2025-07-17T07:36:44.0010324Z strategies for an operator when the tensor inputs and outputs are DTensor. 2025-07-17T07:36:44.0010573Z It can be useful when: (1) there doesn't exist a default sharding strategy for ``op``, 2025-07-17T07:36:44.0010824Z e.g. when ``op`` is a custom operator that is not supported by :class:`DTensor`; (2) 2025-07-17T07:36:44.0011101Z when users would like to overwrite default sharding strategies of existing operators. 2025-07-17T07:36:44.0011105Z 2025-07-17T07:36:44.0011186Z Args: 2025-07-17T07:36:44.0011326Z op (Union[OpOverload, List[OpOverload]]): 2025-07-17T07:36:44.0011516Z An op or a list of ops to register the customized sharding function. 2025-07-17T07:36:44.0011520Z 2025-07-17T07:36:44.0011614Z Returns: 2025-07-17T07:36:44.0011877Z A function decorator which can be used to wrap a function that defines the sharding 2025-07-17T07:36:44.0012148Z strategy for the operator specified in ``op``. The defined sharding strategy will be 2025-07-17T07:36:44.0012435Z registered to DTensor and will override the default sharding strategy if DTensor has 2025-07-17T07:36:44.0012735Z already implemented the operator. The customized sharding function takes the same inputs 2025-07-17T07:36:44.0012985Z as the original op (except that if an arg is a :class:`torch.Tensor`, it will be 2025-07-17T07:36:44.0013256Z replaced by a tensor-like object that DTensor uses internally). The function should 2025-07-17T07:36:44.0013526Z return a sequence of 2-tuples, each specifying acceptable output placements and its 2025-07-17T07:36:44.0013654Z corresponding intput placements. 2025-07-17T07:36:44.0013658Z 2025-07-17T07:36:44.0013741Z Example: 2025-07-17T07:36:44.0013850Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:44.0013991Z >>> @register_sharding(aten._softmax.default) 2025-07-17T07:36:44.0014156Z >>> def custom_softmax_sharding(x, dim, half_to_float): 2025-07-17T07:36:44.0014307Z >>> softmax_dim = dim if dim >= 0 else dim + x.ndim 2025-07-17T07:36:44.0014417Z >>> acceptable_shardings = [] 2025-07-17T07:36:44.0014496Z >>> 2025-07-17T07:36:44.0014682Z >>> all_replicate = ([Replicate()], [Replicate(), None, None]) 2025-07-17T07:36:44.0014818Z >>> acceptable_shardings.append(all_replicate) 2025-07-17T07:36:44.0014897Z >>> 2025-07-17T07:36:44.0015029Z >>> for sharding_dim in range(x.ndim): 2025-07-17T07:36:44.0015141Z >>> if sharding_dim != softmax_dim: 2025-07-17T07:36:44.0015236Z >>> all_sharded = ( 2025-07-17T07:36:44.0015353Z >>> [Shard(sharding_dim)], 2025-07-17T07:36:44.0015470Z >>> [Shard(sharding_dim), None, None], 2025-07-17T07:36:44.0015564Z >>> ) 2025-07-17T07:36:44.0015727Z >>> acceptable_shardings.append(all_sharded) 2025-07-17T07:36:44.0015808Z >>> 2025-07-17T07:36:44.0015926Z >>> return acceptable_shardings 2025-07-17T07:36:44.0015930Z 2025-07-17T07:36:44.0016130Z .. note:: This API is currently experimental and subject to change 2025-07-17T07:36:44.0016134Z 2025-07-17T07:36:44.0016382Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.0016399Z 2025-07-17T07:36:44.0261269Z msg = Cannot scrape callname=PrepareModuleInput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=428. 2025-07-17T07:36:44.0261766Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.0261771Z 2025-07-17T07:36:44.0262150Z Configure the nn.Module's inputs to convert the input tensors of the nn.Module to DTensors at runtime according to 2025-07-17T07:36:44.0262469Z ``input_layouts``, and perform layout redistribution according to the ``desired_input_layouts``. 2025-07-17T07:36:44.0262473Z 2025-07-17T07:36:44.0262572Z Keyword Args: 2025-07-17T07:36:44.0262770Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-07-17T07:36:44.0263209Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-07-17T07:36:44.0263567Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-07-17T07:36:44.0263681Z as a placeholder. default: None. 2025-07-17T07:36:44.0263927Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-07-17T07:36:44.0264303Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-07-17T07:36:44.0264692Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-07-17T07:36:44.0264833Z input_kwarg_layouts (Dict[str, Placement]): 2025-07-17T07:36:44.0265203Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-07-17T07:36:44.0265306Z default: None 2025-07-17T07:36:44.0265492Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-07-17T07:36:44.0265939Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-07-17T07:36:44.0266174Z have the desired DTensor layouts. default: None. 2025-07-17T07:36:44.0266294Z use_local_output (bool, optional): 2025-07-17T07:36:44.0266650Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-07-17T07:36:44.0266743Z Returns: 2025-07-17T07:36:44.0267118Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs. 2025-07-17T07:36:44.0267124Z 2025-07-17T07:36:44.0267230Z Example:: 2025-07-17T07:36:44.0267334Z >>> # xdoctest: +SKIP(failing) 2025-07-17T07:36:44.0267698Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInput 2025-07-17T07:36:44.0267899Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-07-17T07:36:44.0267984Z >>> ... 2025-07-17T07:36:44.0268285Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-07-17T07:36:44.0268474Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-07-17T07:36:44.0268556Z >>> 2025-07-17T07:36:44.0268905Z >>> # According to the style specified below, the first input of attn will be annotated to Sharded DTensor 2025-07-17T07:36:44.0269046Z >>> # and then redistributed to Replicated DTensor. 2025-07-17T07:36:44.0269197Z >>> parallelize_module( 2025-07-17T07:36:44.0269339Z >>> block, # this can be a submodule or module 2025-07-17T07:36:44.0269424Z >>> tp_mesh, 2025-07-17T07:36:44.0269523Z >>> parallelize_plan={ 2025-07-17T07:36:44.0269652Z >>> "attn": PrepareModuleInput( 2025-07-17T07:36:44.0269785Z >>> input_layouts=(Shard(0), None, None, ...), 2025-07-17T07:36:44.0270165Z >>> desired_input_layouts=(Replicate(), None, None, ...) 2025-07-17T07:36:44.0270271Z >>> ), 2025-07-17T07:36:44.0270353Z >>> } 2025-07-17T07:36:44.0270445Z >>> ) 2025-07-17T07:36:44.0270450Z 2025-07-17T07:36:44.0270778Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.0270899Z 2025-07-17T07:36:44.0271681Z msg = Cannot scrape callname=PrepareModuleOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=597. 2025-07-17T07:36:44.0271942Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.0271947Z 2025-07-17T07:36:44.0272405Z Configure the nn.Module's outputs to convert the output tensors of the nn.Module to DTensors at runtime according to 2025-07-17T07:36:44.0272749Z ``output_layouts``, and perform layout redistribution according to the ``desired_output_layouts``. 2025-07-17T07:36:44.0272754Z 2025-07-17T07:36:44.0272839Z Keyword Args: 2025-07-17T07:36:44.0273122Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-07-17T07:36:44.0273491Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-07-17T07:36:44.0274099Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-07-17T07:36:44.0274287Z ``None`` need to be specified as a placeholder. 2025-07-17T07:36:44.0274563Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-07-17T07:36:44.0274960Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-07-17T07:36:44.0275143Z have the desired DTensor layouts. 2025-07-17T07:36:44.0275341Z use_local_output (bool, optional): 2025-07-17T07:36:44.0276012Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-07-17T07:36:44.0276097Z Returns: 2025-07-17T07:36:44.0276393Z A ParallelStyle object that prepares the sharding layouts of the nn.Module's outputs. 2025-07-17T07:36:44.0276399Z 2025-07-17T07:36:44.0276503Z Example:: 2025-07-17T07:36:44.0276603Z >>> # xdoctest: +SKIP(failing) 2025-07-17T07:36:44.0276915Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleOutput 2025-07-17T07:36:44.0277120Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-07-17T07:36:44.0277201Z >>> ... 2025-07-17T07:36:44.0277519Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-07-17T07:36:44.0277640Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-07-17T07:36:44.0277721Z >>> 2025-07-17T07:36:44.0278135Z >>> # According to the style specified below, the output of the TransformerBlock will be converted to Replicated DTensor 2025-07-17T07:36:44.0278268Z >>> # and then redistributed to Sharded DTensor. 2025-07-17T07:36:44.0278366Z >>> parallelize_module( 2025-07-17T07:36:44.0278513Z >>> block, # this can be a submodule or module 2025-07-17T07:36:44.0278598Z >>> tp_mesh, 2025-07-17T07:36:44.0278744Z >>> parallelize_plan = PrepareModuleOutput( 2025-07-17T07:36:44.0278857Z >>> output_layouts=Replicate(), 2025-07-17T07:36:44.0278978Z >>> desired_output_layouts=Shard(0) 2025-07-17T07:36:44.0279075Z >>> ) 2025-07-17T07:36:44.0279157Z >>> ) 2025-07-17T07:36:44.0279162Z 2025-07-17T07:36:44.0279415Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.0279421Z 2025-07-17T07:36:44.0280153Z msg = Cannot scrape callname=PrepareModuleInputOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=705. 2025-07-17T07:36:44.0280411Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.0280416Z 2025-07-17T07:36:44.0280866Z Configure the nn.Module's inputs (and outputs) to convert the input tensors (and output tensors, respectively) of the nn.Module 2025-07-17T07:36:44.0281282Z to DTensors at runtime according to ``input_layouts`` (and output_layouts, respectively), and perform layout redistribution 2025-07-17T07:36:44.0281671Z according to the ``desired_input_layouts`` (and ``desired_output_layouts``, respectively). This is a combination of 2025-07-17T07:36:44.0281955Z :class:`PrepareModuleInput` and :class:`PrepareModuleOutput`. 2025-07-17T07:36:44.0281960Z 2025-07-17T07:36:44.0282048Z Keyword Args: 2025-07-17T07:36:44.0282258Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-07-17T07:36:44.0282586Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-07-17T07:36:44.0282954Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-07-17T07:36:44.0283068Z as a placeholder. default: None. 2025-07-17T07:36:44.0283364Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-07-17T07:36:44.0283753Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-07-17T07:36:44.0284144Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-07-17T07:36:44.0284280Z input_kwarg_layouts (Dict[str, Placement]): 2025-07-17T07:36:44.0284689Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-07-17T07:36:44.0284780Z default: None 2025-07-17T07:36:44.0284950Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-07-17T07:36:44.0285386Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-07-17T07:36:44.0285532Z have the desired DTensor layouts. default: None. 2025-07-17T07:36:44.0285663Z use_local_input (bool, optional): 2025-07-17T07:36:44.0286019Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-07-17T07:36:44.0286195Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-07-17T07:36:44.0286529Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-07-17T07:36:44.0286909Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-07-17T07:36:44.0287062Z ``None`` need to be specified as a placeholder. 2025-07-17T07:36:44.0287252Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-07-17T07:36:44.0287635Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-07-17T07:36:44.0287757Z have the desired DTensor layouts. 2025-07-17T07:36:44.0287867Z use_local_output (bool, optional): 2025-07-17T07:36:44.0288231Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-07-17T07:36:44.0288312Z Returns: 2025-07-17T07:36:44.0288674Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs and outputs. 2025-07-17T07:36:44.0288683Z 2025-07-17T07:36:44.0288780Z Example:: 2025-07-17T07:36:44.0288881Z >>> # xdoctest: +SKIP(failing) 2025-07-17T07:36:44.0289217Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInputOutput 2025-07-17T07:36:44.0289415Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-07-17T07:36:44.0289495Z >>> ... 2025-07-17T07:36:44.0289806Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-07-17T07:36:44.0289927Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-07-17T07:36:44.0290007Z >>> 2025-07-17T07:36:44.0290353Z >>> # According to the style specified below, the first input of attn will be annotated as Sharded DTensor 2025-07-17T07:36:44.0290705Z >>> # and then redistributed to Replicated DTensor, and the output of the TransformerBlock will be annotated 2025-07-17T07:36:44.0290909Z >>> # as Replicated DTensor and then redistributed to Sharded DTensor. 2025-07-17T07:36:44.0291074Z >>> parallelize_module( 2025-07-17T07:36:44.0291207Z >>> block, # this can be a submodule or module 2025-07-17T07:36:44.0291308Z >>> tp_mesh, 2025-07-17T07:36:44.0291407Z >>> parallelize_plan={ 2025-07-17T07:36:44.0291538Z >>> "attn": PrepareModuleInputOutput( 2025-07-17T07:36:44.0291685Z >>> input_layouts=(Shard(0), None, None, ...), 2025-07-17T07:36:44.0291851Z >>> desired_input_layouts=(Replicate(), None, None, ...), 2025-07-17T07:36:44.0291967Z >>> output_layouts=Replicate(), 2025-07-17T07:36:44.0292102Z >>> desired_output_layouts=Shard(0), 2025-07-17T07:36:44.0292232Z >>> ), 2025-07-17T07:36:44.0292313Z >>> } 2025-07-17T07:36:44.0292407Z >>> ) 2025-07-17T07:36:44.0292412Z 2025-07-17T07:36:44.0292664Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.0292668Z 2025-07-17T07:36:44.1000332Z msg = Cannot scrape callname=LowRankMultivariateNormal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lowrank_multivariate_normal.py line=56. 2025-07-17T07:36:44.1000597Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.1000622Z 2025-07-17T07:36:44.1000937Z Creates a multivariate normal distribution with covariance matrix having a low-rank form 2025-07-17T07:36:44.1001130Z parameterized by :attr:`cov_factor` and :attr:`cov_diag`:: 2025-07-17T07:36:44.1001135Z 2025-07-17T07:36:44.1001305Z covariance_matrix = cov_factor @ cov_factor.T + cov_diag 2025-07-17T07:36:44.1001325Z 2025-07-17T07:36:44.1001409Z Example: 2025-07-17T07:36:44.1001562Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-07-17T07:36:44.1001708Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-07-17T07:36:44.1001822Z >>> m = LowRankMultivariateNormal( 2025-07-17T07:36:44.1001997Z ... torch.zeros(2), torch.tensor([[1.0], [0.0]]), torch.ones(2) 2025-07-17T07:36:44.1002094Z ... ) 2025-07-17T07:36:44.1002380Z >>> m.sample() # normally distributed with mean=`[0,0]`, cov_factor=`[[1],[0]]`, cov_diag=`[1,1]` 2025-07-17T07:36:44.1002480Z tensor([-0.2102, -0.5429]) 2025-07-17T07:36:44.1002485Z 2025-07-17T07:36:44.1002577Z Args: 2025-07-17T07:36:44.1002807Z loc (Tensor): mean of the distribution with shape `batch_shape + event_shape` 2025-07-17T07:36:44.1003071Z cov_factor (Tensor): factor part of low-rank form of covariance matrix with shape 2025-07-17T07:36:44.1003186Z `batch_shape + event_shape + (rank,)` 2025-07-17T07:36:44.1003438Z cov_diag (Tensor): diagonal part of low-rank form of covariance matrix with shape 2025-07-17T07:36:44.1003555Z `batch_shape + event_shape` 2025-07-17T07:36:44.1003559Z 2025-07-17T07:36:44.1003639Z Note: 2025-07-17T07:36:44.1003905Z The computation for determinant and inverse of covariance matrix is avoided when 2025-07-17T07:36:44.1004157Z `cov_factor.shape[1] << cov_factor.shape[0]` thanks to `Woodbury matrix identity 2025-07-17T07:36:44.1004370Z `_ and 2025-07-17T07:36:44.1004671Z `matrix determinant lemma `_. 2025-07-17T07:36:44.1004917Z Thanks to these formulas, we just need to compute the determinant and inverse of 2025-07-17T07:36:44.1005034Z the small size "capacitance" matrix:: 2025-07-17T07:36:44.1005039Z 2025-07-17T07:36:44.1005229Z capacitance = I + cov_factor.T @ inv(cov_diag) @ cov_factor 2025-07-17T07:36:44.1005233Z 2025-07-17T07:36:44.1005552Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.1005557Z 2025-07-17T07:36:44.1025102Z msg = Cannot scrape callname=MixtureSameFamily in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/mixture_same_family.py line=15. 2025-07-17T07:36:44.1025383Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.1025566Z 2025-07-17T07:36:44.1025803Z The `MixtureSameFamily` distribution implements a (batch of) mixture 2025-07-17T07:36:44.1026043Z distribution where all component are from different parameterizations of 2025-07-17T07:36:44.1026277Z the same distribution type. It is parameterized by a `Categorical` 2025-07-17T07:36:44.1026481Z "selecting distribution" (over `k` component) and a component 2025-07-17T07:36:44.1026681Z distribution, i.e., a `Distribution` with a rightmost batch shape 2025-07-17T07:36:44.1026846Z (equal to `[k]`) which indexes each (batch of) component. 2025-07-17T07:36:44.1026851Z 2025-07-17T07:36:44.1026942Z Examples:: 2025-07-17T07:36:44.1027025Z 2025-07-17T07:36:44.1027140Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:44.1027354Z >>> # Construct Gaussian Mixture Model in 1D consisting of 5 equally 2025-07-17T07:36:44.1027462Z >>> # weighted normal distributions 2025-07-17T07:36:44.1027577Z >>> mix = D.Categorical(torch.ones(5,)) 2025-07-17T07:36:44.1027732Z >>> comp = D.Normal(torch.randn(5,), torch.rand(5,)) 2025-07-17T07:36:44.1027847Z >>> gmm = MixtureSameFamily(mix, comp) 2025-07-17T07:36:44.1027852Z 2025-07-17T07:36:44.1028062Z >>> # Construct Gaussian Mixture Model in 2D consisting of 5 equally 2025-07-17T07:36:44.1028188Z >>> # weighted bivariate normal distributions 2025-07-17T07:36:44.1028299Z >>> mix = D.Categorical(torch.ones(5,)) 2025-07-17T07:36:44.1028421Z >>> comp = D.Independent(D.Normal( 2025-07-17T07:36:44.1028543Z ... torch.randn(5,2), torch.rand(5,2)), 1) 2025-07-17T07:36:44.1028656Z >>> gmm = MixtureSameFamily(mix, comp) 2025-07-17T07:36:44.1028664Z 2025-07-17T07:36:44.1028852Z >>> # Construct a batch of 3 Gaussian Mixture Models in 2D each 2025-07-17T07:36:44.1029049Z >>> # consisting of 5 random weighted bivariate normal distributions 2025-07-17T07:36:44.1029177Z >>> mix = D.Categorical(torch.rand(3,5)) 2025-07-17T07:36:44.1029287Z >>> comp = D.Independent(D.Normal( 2025-07-17T07:36:44.1029416Z ... torch.randn(3,5,2), torch.rand(3,5,2)), 1) 2025-07-17T07:36:44.1029548Z >>> gmm = MixtureSameFamily(mix, comp) 2025-07-17T07:36:44.1029552Z 2025-07-17T07:36:44.1029630Z Args: 2025-07-17T07:36:44.1029827Z mixture_distribution: `torch.distributions.Categorical`-like 2025-07-17T07:36:44.1030020Z instance. Manages the probability of selecting component. 2025-07-17T07:36:44.1030181Z The number of categories must match the rightmost batch 2025-07-17T07:36:44.1030376Z dimension of the `component_distribution`. Must have either 2025-07-17T07:36:44.1030516Z scalar `batch_shape` or `batch_shape` matching 2025-07-17T07:36:44.1030646Z `component_distribution.batch_shape[:-1]` 2025-07-17T07:36:44.1030873Z component_distribution: `torch.distributions.Distribution`-like 2025-07-17T07:36:44.1031044Z instance. Right-most batch dimension indexes component. 2025-07-17T07:36:44.1031051Z 2025-07-17T07:36:44.1031298Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.1031303Z 2025-07-17T07:36:44.1185701Z msg = Cannot scrape callname=RelaxedBernoulli in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_bernoulli.py line=120. 2025-07-17T07:36:44.1185963Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.1185983Z 2025-07-17T07:36:44.1186176Z Creates a RelaxedBernoulli distribution, parametrized by 2025-07-17T07:36:44.1186362Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits` 2025-07-17T07:36:44.1186595Z (but not both). This is a relaxed version of the `Bernoulli` distribution, 2025-07-17T07:36:44.1186771Z so the values are in (0, 1), and has reparametrizable samples. 2025-07-17T07:36:44.1186775Z 2025-07-17T07:36:44.1186867Z Example:: 2025-07-17T07:36:44.1186871Z 2025-07-17T07:36:44.1187018Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-07-17T07:36:44.1187275Z >>> m = RelaxedBernoulli(torch.tensor([2.2]), 2025-07-17T07:36:44.1187396Z ... torch.tensor([0.1, 0.2, 0.3, 0.99])) 2025-07-17T07:36:44.1187495Z >>> m.sample() 2025-07-17T07:36:44.1187606Z tensor([ 0.2951, 0.3442, 0.8918, 0.9021]) 2025-07-17T07:36:44.1187610Z 2025-07-17T07:36:44.1187703Z Args: 2025-07-17T07:36:44.1187835Z temperature (Tensor): relaxation temperature 2025-07-17T07:36:44.1188003Z probs (Number, Tensor): the probability of sampling `1` 2025-07-17T07:36:44.1188170Z logits (Number, Tensor): the log-odds of sampling `1` 2025-07-17T07:36:44.1188175Z 2025-07-17T07:36:44.1188493Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.1188498Z 2025-07-17T07:36:44.1205660Z msg = Cannot scrape callname=RelaxedOneHotCategorical in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_categorical.py line=109. 2025-07-17T07:36:44.1205928Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.1205933Z 2025-07-17T07:36:44.1206149Z Creates a RelaxedOneHotCategorical distribution parametrized by 2025-07-17T07:36:44.1206355Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits`. 2025-07-17T07:36:44.1206589Z This is a relaxed version of the :class:`OneHotCategorical` distribution, so 2025-07-17T07:36:44.1206763Z its samples are on simplex, and are reparametrizable. 2025-07-17T07:36:44.1206768Z 2025-07-17T07:36:44.1206855Z Example:: 2025-07-17T07:36:44.1206860Z 2025-07-17T07:36:44.1206995Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-07-17T07:36:44.1207165Z >>> m = RelaxedOneHotCategorical(torch.tensor([2.2]), 2025-07-17T07:36:44.1207290Z ... torch.tensor([0.1, 0.2, 0.3, 0.4])) 2025-07-17T07:36:44.1207389Z >>> m.sample() 2025-07-17T07:36:44.1207500Z tensor([ 0.1294, 0.2324, 0.3859, 0.2523]) 2025-07-17T07:36:44.1207509Z 2025-07-17T07:36:44.1207587Z Args: 2025-07-17T07:36:44.1207733Z temperature (Tensor): relaxation temperature 2025-07-17T07:36:44.1207844Z probs (Tensor): event probabilities 2025-07-17T07:36:44.1208031Z logits (Tensor): unnormalized log probability for each event 2025-07-17T07:36:44.1208036Z 2025-07-17T07:36:44.1208295Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.1208299Z 2025-07-17T07:36:44.5142819Z msg = Cannot scrape callname=assoc_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=245. 2025-07-17T07:36:44.5143992Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.5145038Z Return a new dict with new, potentially nested, key value pair 2025-07-17T07:36:44.5145341Z 2025-07-17T07:36:44.5145446Z >>> purchase = { 2025-07-17T07:36:44.5145686Z ... "name": "Alice", 2025-07-17T07:36:44.5146114Z ... "order": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-07-17T07:36:44.5146605Z ... "credit card": "5555-1234-1234-1234", 2025-07-17T07:36:44.5146920Z ... } 2025-07-17T07:36:44.5147287Z >>> assoc_in(purchase, ["order", "costs"], [0.25, 1.00]) # doctest: +SKIP 2025-07-17T07:36:44.5147788Z {'credit card': '5555-1234-1234-1234', 2025-07-17T07:36:44.5148389Z 'name': 'Alice', 2025-07-17T07:36:44.5148792Z 'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}} 2025-07-17T07:36:44.5149155Z 2025-07-17T07:36:44.5149520Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.5150091Z 2025-07-17T07:36:44.5151034Z msg = Cannot scrape callname=update_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=261. 2025-07-17T07:36:44.5152375Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.5152886Z Update value in a (potentially) nested dictionary 2025-07-17T07:36:44.5153416Z 2025-07-17T07:36:44.5153499Z inputs: 2025-07-17T07:36:44.5153743Z d - dictionary on which to operate 2025-07-17T07:36:44.5154165Z keys - list or tuple giving the location of the value to be changed in d 2025-07-17T07:36:44.5154623Z func - function to operate on that value 2025-07-17T07:36:44.5154851Z 2025-07-17T07:36:44.5155047Z If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the 2025-07-17T07:36:44.5155585Z original dictionary with v replaced by func(v), but does not mutate the 2025-07-17T07:36:44.5156020Z original dictionary. 2025-07-17T07:36:44.5156198Z 2025-07-17T07:36:44.5156501Z If k0 is not a key in d, update_in creates nested dictionaries to the depth 2025-07-17T07:36:44.5157045Z specified by the keys, with the innermost value set to func(default). 2025-07-17T07:36:44.5157373Z 2025-07-17T07:36:44.5157471Z >>> inc = lambda x: x + 1 2025-07-17T07:36:44.5157764Z >>> update_in({"a": 0}, ["a"], inc) 2025-07-17T07:36:44.5158067Z {'a': 1} 2025-07-17T07:36:44.5158189Z 2025-07-17T07:36:44.5158294Z >>> transaction = { 2025-07-17T07:36:44.5158536Z ... "name": "Alice", 2025-07-17T07:36:44.5158899Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-07-17T07:36:44.5159319Z ... "credit card": "5555-1234-1234-1234", 2025-07-17T07:36:44.5159615Z ... } 2025-07-17T07:36:44.5159947Z >>> update_in(transaction, ["purchase", "costs"], sum) # doctest: +SKIP 2025-07-17T07:36:44.5160384Z {'credit card': '5555-1234-1234-1234', 2025-07-17T07:36:44.5160675Z 'name': 'Alice', 2025-07-17T07:36:44.5161001Z 'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}} 2025-07-17T07:36:44.5161288Z 2025-07-17T07:36:44.5161406Z >>> # updating a value when k0 is not in d 2025-07-17T07:36:44.5161763Z >>> update_in({}, [1, 2, 3], str, default="bar") 2025-07-17T07:36:44.5162080Z {1: {2: {3: 'bar'}}} 2025-07-17T07:36:44.5162357Z >>> update_in({1: "foo"}, [2, 3, 4], inc, 0) 2025-07-17T07:36:44.5162674Z {1: 'foo', 2: {3: {4: 1}}} 2025-07-17T07:36:44.5162919Z 2025-07-17T07:36:44.5163284Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.5163649Z 2025-07-17T07:36:44.5164303Z msg = Cannot scrape callname=get_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=320. 2025-07-17T07:36:44.5165422Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.5165961Z Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys. 2025-07-17T07:36:44.5166247Z 2025-07-17T07:36:44.5166430Z If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless 2025-07-17T07:36:44.5166934Z ``no_default`` is specified, then it raises KeyError or IndexError. 2025-07-17T07:36:44.5167245Z 2025-07-17T07:36:44.5167446Z ``get_in`` is a generalization of ``operator.getitem`` for nested data 2025-07-17T07:36:44.5167912Z structures such as dictionaries and lists. 2025-07-17T07:36:44.5168232Z 2025-07-17T07:36:44.5168323Z >>> transaction = { 2025-07-17T07:36:44.5168573Z ... "name": "Alice", 2025-07-17T07:36:44.5168921Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-07-17T07:36:44.5169343Z ... "credit card": "5555-1234-1234-1234", 2025-07-17T07:36:44.5169650Z ... } 2025-07-17T07:36:44.5169890Z >>> get_in(["purchase", "items", 0], transaction) 2025-07-17T07:36:44.5170449Z 'Apple' 2025-07-17T07:36:44.5170683Z >>> get_in(["name"], transaction) 2025-07-17T07:36:44.5170960Z 'Alice' 2025-07-17T07:36:44.5171214Z >>> get_in(["purchase", "total"], transaction) 2025-07-17T07:36:44.5171602Z >>> get_in(["purchase", "items", "apple"], transaction) 2025-07-17T07:36:44.5171997Z >>> get_in(["purchase", "items", 10], transaction) 2025-07-17T07:36:44.5172366Z >>> get_in(["purchase", "total"], transaction, 0) 2025-07-17T07:36:44.5172830Z 0 2025-07-17T07:36:44.5173052Z >>> get_in(["y"], {}, no_default=True) 2025-07-17T07:36:44.5173370Z Traceback (most recent call last): 2025-07-17T07:36:44.5173670Z ... 2025-07-17T07:36:44.5173881Z KeyError: 'y' 2025-07-17T07:36:44.5174019Z 2025-07-17T07:36:44.5174104Z See Also: 2025-07-17T07:36:44.5174324Z itertoolz.get 2025-07-17T07:36:44.5174600Z operator.getitem 2025-07-17T07:36:44.5174834Z 2025-07-17T07:36:44.5175195Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.5175566Z 2025-07-17T07:36:44.5176353Z msg = Cannot scrape callname=groupby in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=373. 2025-07-17T07:36:44.5177390Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.5177887Z Group a collection by a key function 2025-07-17T07:36:44.5178096Z 2025-07-17T07:36:44.5178261Z >>> names = ["Alice", "Bob", "Charlie", "Dan", "Edith", "Frank"] 2025-07-17T07:36:44.5178667Z >>> groupby(len, names) # doctest: +SKIP 2025-07-17T07:36:44.5179058Z {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']} 2025-07-17T07:36:44.5179329Z 2025-07-17T07:36:44.5179431Z >>> iseven = lambda x: x % 2 == 0 2025-07-17T07:36:44.5179803Z >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8]) # doctest: +SKIP 2025-07-17T07:36:44.5180197Z {False: [1, 3, 5, 7], True: [2, 4, 6, 8]} 2025-07-17T07:36:44.5180410Z 2025-07-17T07:36:44.5180560Z Non-callable keys imply grouping on a member. 2025-07-17T07:36:44.5180803Z 2025-07-17T07:36:44.5180889Z >>> groupby( 2025-07-17T07:36:44.5181120Z ... "gender", 2025-07-17T07:36:44.5181358Z ... [ 2025-07-17T07:36:44.5181588Z ... {"name": "Alice", "gender": "F"}, 2025-07-17T07:36:44.5181932Z ... {"name": "Bob", "gender": "M"}, 2025-07-17T07:36:44.5182278Z ... {"name": "Charlie", "gender": "M"}, 2025-07-17T07:36:44.5182585Z ... ], 2025-07-17T07:36:44.5182814Z ... ) # doctest:+SKIP 2025-07-17T07:36:44.5183100Z {'F': [{'gender': 'F', 'name': 'Alice'}], 2025-07-17T07:36:44.5183419Z 'M': [{'gender': 'M', 'name': 'Bob'}, 2025-07-17T07:36:44.5183748Z {'gender': 'M', 'name': 'Charlie'}]} 2025-07-17T07:36:44.5183979Z 2025-07-17T07:36:44.5184113Z Not to be confused with ``itertools.groupby`` 2025-07-17T07:36:44.5184359Z 2025-07-17T07:36:44.5184455Z See Also: 2025-07-17T07:36:44.5184656Z countby 2025-07-17T07:36:44.5184868Z 2025-07-17T07:36:44.5185242Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.5185610Z 2025-07-17T07:36:44.8194446Z msg = Cannot scrape callname=calculate_gain in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py line=142. 2025-07-17T07:36:44.8195343Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.8195985Z Return the recommended gain value for the given nonlinearity function. 2025-07-17T07:36:44.8196330Z 2025-07-17T07:36:44.8196451Z The values are as follows: 2025-07-17T07:36:44.8196636Z 2025-07-17T07:36:44.8196747Z ================= ==================================================== 2025-07-17T07:36:44.8197089Z nonlinearity gain 2025-07-17T07:36:44.8197382Z ================= ==================================================== 2025-07-17T07:36:44.8197727Z Linear / Identity :math:`1` 2025-07-17T07:36:44.8197996Z Conv{1,2,3}D :math:`1` 2025-07-17T07:36:44.8198275Z Sigmoid :math:`1` 2025-07-17T07:36:44.8198568Z Tanh :math:`\frac{5}{3}` 2025-07-17T07:36:44.8198870Z ReLU :math:`\sqrt{2}` 2025-07-17T07:36:44.8199262Z Leaky Relu :math:`\sqrt{\frac{2}{1 + \text{negative\_slope}^2}}` 2025-07-17T07:36:44.8199674Z SELU :math:`\frac{3}{4}` 2025-07-17T07:36:44.8199986Z ================= ==================================================== 2025-07-17T07:36:44.8200493Z 2025-07-17T07:36:44.8200608Z .. warning:: 2025-07-17T07:36:44.8200941Z In order to implement `Self-Normalizing Neural Networks`_ , 2025-07-17T07:36:44.8201483Z you should use ``nonlinearity='linear'`` instead of ``nonlinearity='selu'``. 2025-07-17T07:36:44.8202005Z This gives the initial weights a variance of ``1 / N``, 2025-07-17T07:36:44.8202510Z which is necessary to induce a stable fixed point in the forward pass. 2025-07-17T07:36:44.8203079Z In contrast, the default gain for ``SELU`` sacrifices the normalization 2025-07-17T07:36:44.8203763Z effect for more stable gradient flow in rectangular layers. 2025-07-17T07:36:44.8204074Z 2025-07-17T07:36:44.8204156Z Args: 2025-07-17T07:36:44.8204476Z nonlinearity: the non-linear function (`nn.functional` name) 2025-07-17T07:36:44.8204968Z param: optional parameter for the non-linear function 2025-07-17T07:36:44.8205248Z 2025-07-17T07:36:44.8205410Z Examples: 2025-07-17T07:36:44.8205666Z >>> gain = nn.init.calculate_gain( 2025-07-17T07:36:44.8205992Z ... "leaky_relu", 0.2 2025-07-17T07:36:44.8206295Z ... ) # leaky_relu with negative_slope=0.2 2025-07-17T07:36:44.8206545Z 2025-07-17T07:36:44.8207035Z .. _Self-Normalizing Neural Networks: https://papers.nips.cc/paper/2017/hash/5d44ee6f2c3f71b73125876103c8f6c4-Abstract.html 2025-07-17T07:36:44.8207710Z 2025-07-17T07:36:44.8208080Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.8208448Z 2025-07-17T07:36:44.8784715Z msg = Cannot scrape callname=SyncBatchNorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=601. 2025-07-17T07:36:44.8786034Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.8786589Z Applies Batch Normalization over a N-Dimensional input. 2025-07-17T07:36:44.8786887Z 2025-07-17T07:36:44.8787339Z The N-D input is a mini-batch of [N-2]D inputs with additional channel dimension) as described in the paper 2025-07-17T07:36:44.8788033Z `Batch Normalization: Accelerating Deep Network Training by Reducing 2025-07-17T07:36:44.8788693Z Internal Covariate Shift `__ . 2025-07-17T07:36:44.8789084Z 2025-07-17T07:36:44.8789194Z .. math:: 2025-07-17T07:36:44.8789363Z 2025-07-17T07:36:44.8789593Z y = \frac{x - \mathrm{E}[x]}{ \sqrt{\mathrm{Var}[x] + \epsilon}} * \gamma + \beta 2025-07-17T07:36:44.8789974Z 2025-07-17T07:36:44.8790207Z The mean and standard-deviation are calculated per-dimension over all 2025-07-17T07:36:44.8790776Z mini-batches of the same process groups. :math:`\gamma` and :math:`\beta` 2025-07-17T07:36:44.8791366Z are learnable parameter vectors of size `C` (where `C` is the input size). 2025-07-17T07:36:44.8791903Z By default, the elements of :math:`\gamma` are sampled from 2025-07-17T07:36:44.8792382Z :math:`\mathcal{U}(0, 1)` and the elements of :math:`\beta` are set to 0. 2025-07-17T07:36:44.8792959Z The standard-deviation is calculated via the biased estimator, equivalent to 2025-07-17T07:36:44.8793452Z `torch.var(input, unbiased=False)`. 2025-07-17T07:36:44.8793667Z 2025-07-17T07:36:44.8794010Z Also by default, during training this layer keeps running estimates of its 2025-07-17T07:36:44.8794635Z computed mean and variance, which are then used for normalization during 2025-07-17T07:36:44.8795233Z evaluation. The running estimates are kept with a default :attr:`momentum` 2025-07-17T07:36:44.8795682Z of 0.1. 2025-07-17T07:36:44.8795799Z 2025-07-17T07:36:44.8796039Z If :attr:`track_running_stats` is set to ``False``, this layer then does not 2025-07-17T07:36:44.8796589Z keep running estimates, and batch statistics are instead used during 2025-07-17T07:36:44.8797032Z evaluation time as well. 2025-07-17T07:36:44.8797211Z 2025-07-17T07:36:44.8797523Z .. note:: 2025-07-17T07:36:44.8797862Z This :attr:`momentum` argument is different from one used in optimizer 2025-07-17T07:36:44.8798427Z classes and the conventional notion of momentum. Mathematically, the 2025-07-17T07:36:44.8798905Z update rule for running statistics here is 2025-07-17T07:36:44.8799403Z :math:`\hat{x}_\text{new} = (1 - \text{momentum}) \times \hat{x} + \text{momentum} \times x_t`, 2025-07-17T07:36:44.8799989Z where :math:`\hat{x}` is the estimated statistic and :math:`x_t` is the 2025-07-17T07:36:44.8800413Z new observed value. 2025-07-17T07:36:44.8800586Z 2025-07-17T07:36:44.8800994Z Because the Batch Normalization is done for each channel in the ``C`` dimension, computing 2025-07-17T07:36:44.8801651Z statistics on ``(N, +)`` slices, it's common terminology to call this Volumetric Batch 2025-07-17T07:36:44.8802194Z Normalization or Spatio-temporal Batch Normalization. 2025-07-17T07:36:44.8802489Z 2025-07-17T07:36:44.8802634Z Currently :class:`SyncBatchNorm` only supports 2025-07-17T07:36:44.8803187Z :class:`~torch.nn.DistributedDataParallel` (DDP) with single GPU per process. Use 2025-07-17T07:36:44.8803793Z :meth:`torch.nn.SyncBatchNorm.convert_sync_batchnorm()` to convert 2025-07-17T07:36:44.8804330Z :attr:`BatchNorm*D` layer to :class:`SyncBatchNorm` before wrapping 2025-07-17T07:36:44.8804752Z Network with DDP. 2025-07-17T07:36:44.8804909Z 2025-07-17T07:36:44.8805007Z Args: 2025-07-17T07:36:44.8805284Z num_features: :math:`C` from an expected input of size 2025-07-17T07:36:44.8805745Z :math:`(N, C, +)` 2025-07-17T07:36:44.8806121Z eps: a value added to the denominator for numerical stability. 2025-07-17T07:36:44.8806512Z Default: ``1e-5`` 2025-07-17T07:36:44.8806889Z momentum: the value used for the running_mean and running_var 2025-07-17T07:36:44.8807413Z computation. Can be set to ``None`` for cumulative moving average 2025-07-17T07:36:44.8807868Z (i.e. simple average). Default: 0.1 2025-07-17T07:36:44.8808292Z affine: a boolean value that when set to ``True``, this module has 2025-07-17T07:36:44.8808771Z learnable affine parameters. Default: ``True`` 2025-07-17T07:36:44.8809250Z track_running_stats: a boolean value that when set to ``True``, this 2025-07-17T07:36:44.8809798Z module tracks the running mean and variance, and when set to ``False``, 2025-07-17T07:36:44.8810374Z this module does not track such statistics, and initializes statistics 2025-07-17T07:36:44.8810925Z buffers :attr:`running_mean` and :attr:`running_var` as ``None``. 2025-07-17T07:36:44.8811475Z When these buffers are ``None``, this module always uses batch statistics. 2025-07-17T07:36:44.8811962Z in both training and eval modes. Default: ``True`` 2025-07-17T07:36:44.8812516Z process_group: synchronization of stats happen within each process group 2025-07-17T07:36:44.8813108Z individually. Default behavior is synchronization across the whole 2025-07-17T07:36:44.8813523Z world 2025-07-17T07:36:44.8813664Z 2025-07-17T07:36:44.8813745Z Shape: 2025-07-17T07:36:44.8813968Z - Input: :math:`(N, C, +)` 2025-07-17T07:36:44.8814309Z - Output: :math:`(N, C, +)` (same shape as input) 2025-07-17T07:36:44.8814558Z 2025-07-17T07:36:44.8814642Z .. note:: 2025-07-17T07:36:44.8815013Z Synchronization of batchnorm statistics occurs only while training, i.e. 2025-07-17T07:36:44.8815573Z synchronization is disabled when ``model.eval()`` is set or if 2025-07-17T07:36:44.8816002Z ``self.training`` is otherwise ``False``. 2025-07-17T07:36:44.8816249Z 2025-07-17T07:36:44.8816335Z Examples:: 2025-07-17T07:36:44.8816465Z 2025-07-17T07:36:44.8816574Z >>> # xdoctest: +SKIP 2025-07-17T07:36:44.8816864Z >>> # With Learnable Parameters 2025-07-17T07:36:44.8817178Z >>> m = nn.SyncBatchNorm(100) 2025-07-17T07:36:44.8817615Z >>> # creating process group (optional) 2025-07-17T07:36:44.8817989Z >>> # ranks is a list of int identifying rank ids. 2025-07-17T07:36:44.8818333Z >>> ranks = list(range(8)) 2025-07-17T07:36:44.8818636Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-07-17T07:36:44.8819041Z >>> # Note: every rank calls into new_group for every 2025-07-17T07:36:44.8819439Z >>> # process group created, even if that rank is not 2025-07-17T07:36:44.8819804Z >>> # part of the group. 2025-07-17T07:36:44.8820238Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-07-17T07:36:44.8820865Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-07-17T07:36:44.8821289Z >>> # Without Learnable Parameters 2025-07-17T07:36:44.8821709Z >>> m = nn.BatchNorm3d(100, affine=False, process_group=process_group) 2025-07-17T07:36:44.8822154Z >>> input = torch.randn(20, 100, 35, 45, 10) 2025-07-17T07:36:44.8822478Z >>> output = m(input) 2025-07-17T07:36:44.8822670Z 2025-07-17T07:36:44.8822782Z >>> # network is nn.BatchNorm layer 2025-07-17T07:36:44.8823280Z >>> sync_bn_network = nn.SyncBatchNorm.convert_sync_batchnorm(network, process_group) 2025-07-17T07:36:44.8823838Z >>> # only single gpu per process is currently supported 2025-07-17T07:36:44.8824316Z >>> ddp_sync_bn_network = torch.nn.parallel.DistributedDataParallel( 2025-07-17T07:36:44.8824764Z >>> sync_bn_network, 2025-07-17T07:36:44.8825118Z >>> device_ids=[args.local_rank], 2025-07-17T07:36:44.8825480Z >>> output_device=args.local_rank) 2025-07-17T07:36:44.8825806Z 2025-07-17T07:36:44.8826168Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.8826533Z 2025-07-17T07:36:44.8827221Z msg = Cannot scrape callname=SyncBatchNorm.convert_sync_batchnorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=825. 2025-07-17T07:36:44.8828241Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.8828929Z Converts all :attr:`BatchNorm*D` layers in the model to :class:`torch.nn.SyncBatchNorm` layers. 2025-07-17T07:36:44.8829365Z 2025-07-17T07:36:44.8829447Z Args: 2025-07-17T07:36:44.8829817Z module (nn.Module): module containing one or more :attr:`BatchNorm*D` layers 2025-07-17T07:36:44.8830387Z process_group (optional): process group to scope synchronization, 2025-07-17T07:36:44.8830834Z default is the whole world 2025-07-17T07:36:44.8831050Z 2025-07-17T07:36:44.8831143Z Returns: 2025-07-17T07:36:44.8831518Z The original :attr:`module` with the converted :class:`torch.nn.SyncBatchNorm` 2025-07-17T07:36:44.8832104Z layers. If the original :attr:`module` is a :attr:`BatchNorm*D` layer, 2025-07-17T07:36:44.8832648Z a new :class:`torch.nn.SyncBatchNorm` layer object will be returned 2025-07-17T07:36:44.8833058Z instead. 2025-07-17T07:36:44.8833202Z 2025-07-17T07:36:44.8833289Z Example:: 2025-07-17T07:36:44.8833433Z 2025-07-17T07:36:44.8833547Z >>> # Network with nn.BatchNorm layer 2025-07-17T07:36:44.8833914Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:44.8834272Z >>> module = torch.nn.Sequential( 2025-07-17T07:36:44.8834614Z >>> torch.nn.Linear(20, 100), 2025-07-17T07:36:44.8834964Z >>> torch.nn.BatchNorm1d(100), 2025-07-17T07:36:44.8835286Z >>> ).cuda() 2025-07-17T07:36:44.8835623Z >>> # creating process group (optional) 2025-07-17T07:36:44.8836000Z >>> # ranks is a list of int identifying rank ids. 2025-07-17T07:36:44.8836360Z >>> ranks = list(range(8)) 2025-07-17T07:36:44.8836663Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-07-17T07:36:44.8837096Z >>> # Note: every rank calls into new_group for every 2025-07-17T07:36:44.8837507Z >>> # process group created, even if that rank is not 2025-07-17T07:36:44.8837862Z >>> # part of the group. 2025-07-17T07:36:44.8838187Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:44.8838665Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-07-17T07:36:44.8839239Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-07-17T07:36:44.8839841Z >>> sync_bn_module = torch.nn.SyncBatchNorm.convert_sync_batchnorm(module, process_group) 2025-07-17T07:36:44.8840322Z 2025-07-17T07:36:44.8840405Z 2025-07-17T07:36:44.8840772Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.8841135Z 2025-07-17T07:36:44.9040345Z msg = Cannot scrape callname=Unflatten in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py line=60. 2025-07-17T07:36:44.9041244Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.9041634Z 2025-07-17T07:36:44.9041938Z Unflattens a tensor dim expanding it to a desired shape. For use with :class:`~nn.Sequential`. 2025-07-17T07:36:44.9042377Z 2025-07-17T07:36:44.9042643Z * :attr:`dim` specifies the dimension of the input tensor to be unflattened, and it can 2025-07-17T07:36:44.9043258Z be either `int` or `str` when `Tensor` or `NamedTensor` is used, respectively. 2025-07-17T07:36:44.9043613Z 2025-07-17T07:36:44.9043944Z * :attr:`unflattened_size` is the new shape of the unflattened dimension of the tensor and it can be 2025-07-17T07:36:44.9044618Z a `tuple` of ints or a `list` of ints or `torch.Size` for `Tensor` input; a `NamedShape` 2025-07-17T07:36:44.9045157Z (tuple of `(name, size)` tuples) for `NamedTensor` input. 2025-07-17T07:36:44.9045496Z 2025-07-17T07:36:44.9045593Z Shape: 2025-07-17T07:36:44.9045921Z - Input: :math:`(*, S_{\text{dim}}, *)`, where :math:`S_{\text{dim}}` is the size at 2025-07-17T07:36:44.9046510Z dimension :attr:`dim` and :math:`*` means any number of dimensions including none. 2025-07-17T07:36:44.9047101Z - Output: :math:`(*, U_1, ..., U_n, *)`, where :math:`U` = :attr:`unflattened_size` and 2025-07-17T07:36:44.9056670Z :math:`\prod_{i=1}^n U_i = S_{\text{dim}}`. 2025-07-17T07:36:44.9056936Z 2025-07-17T07:36:44.9057019Z Args: 2025-07-17T07:36:44.9057298Z dim (Union[int, str]): Dimension to be unflattened 2025-07-17T07:36:44.9057898Z unflattened_size (Union[torch.Size, Tuple, List, NamedShape]): New shape of the unflattened dimension 2025-07-17T07:36:44.9058390Z 2025-07-17T07:36:44.9058478Z Examples: 2025-07-17T07:36:44.9058714Z >>> input = torch.randn(2, 50) 2025-07-17T07:36:44.9059020Z >>> # With tuple of ints 2025-07-17T07:36:44.9059287Z >>> m = nn.Sequential( 2025-07-17T07:36:44.9059559Z >>> nn.Linear(50, 50), 2025-07-17T07:36:44.9059855Z >>> nn.Unflatten(1, (2, 5, 5)) 2025-07-17T07:36:44.9060136Z >>> ) 2025-07-17T07:36:44.9060353Z >>> output = m(input) 2025-07-17T07:36:44.9060615Z >>> output.size() 2025-07-17T07:36:44.9060857Z torch.Size([2, 2, 5, 5]) 2025-07-17T07:36:44.9061133Z >>> # With torch.Size 2025-07-17T07:36:44.9061396Z >>> m = nn.Sequential( 2025-07-17T07:36:44.9061651Z >>> nn.Linear(50, 50), 2025-07-17T07:36:44.9061955Z >>> nn.Unflatten(1, torch.Size([2, 5, 5])) 2025-07-17T07:36:44.9062276Z >>> ) 2025-07-17T07:36:44.9062485Z >>> output = m(input) 2025-07-17T07:36:44.9062748Z >>> output.size() 2025-07-17T07:36:44.9063002Z torch.Size([2, 2, 5, 5]) 2025-07-17T07:36:44.9063292Z >>> # With namedshape (tuple of tuples) 2025-07-17T07:36:44.9063667Z >>> input = torch.randn(2, 50, names=("N", "features")) 2025-07-17T07:36:44.9064135Z >>> unflatten = nn.Unflatten("features", (("C", 2), ("H", 5), ("W", 5))) 2025-07-17T07:36:44.9064566Z >>> output = unflatten(input) 2025-07-17T07:36:44.9065034Z >>> output.size() 2025-07-17T07:36:44.9065286Z torch.Size([2, 2, 5, 5]) 2025-07-17T07:36:44.9065458Z 2025-07-17T07:36:44.9065723Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.9066090Z 2025-07-17T07:36:44.9369046Z msg = Cannot scrape callname=TripletMarginWithDistanceLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1718. 2025-07-17T07:36:44.9370218Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.9370803Z Creates a criterion that measures the triplet loss given input 2025-07-17T07:36:44.9371469Z tensors :math:`a`, :math:`p`, and :math:`n` (representing anchor, 2025-07-17T07:36:44.9371999Z positive, and negative examples, respectively), and a nonnegative, 2025-07-17T07:36:44.9372568Z real-valued function ("distance function") used to compute the relationship 2025-07-17T07:36:44.9373168Z between the anchor and positive example ("positive distance") and the 2025-07-17T07:36:44.9373660Z anchor and negative example ("negative distance"). 2025-07-17T07:36:44.9373922Z 2025-07-17T07:36:44.9374131Z The unreduced loss (i.e., with :attr:`reduction` set to ``'none'``) 2025-07-17T07:36:44.9374554Z can be described as: 2025-07-17T07:36:44.9374731Z 2025-07-17T07:36:44.9374828Z .. math:: 2025-07-17T07:36:44.9375103Z \ell(a, p, n) = L = \{l_1,\dots,l_N\}^\top, \quad 2025-07-17T07:36:44.9375494Z l_i = \max \{d(a_i, p_i) - d(a_i, n_i) + {\rm margin}, 0\} 2025-07-17T07:36:44.9375770Z 2025-07-17T07:36:44.9376018Z where :math:`N` is the batch size; :math:`d` is a nonnegative, real-valued function 2025-07-17T07:36:44.9376676Z quantifying the closeness of two tensors, referred to as the :attr:`distance_function`; 2025-07-17T07:36:44.9377333Z and :math:`margin` is a nonnegative margin representing the minimum difference 2025-07-17T07:36:44.9377928Z between the positive and negative distances that is required for the loss to 2025-07-17T07:36:44.9378527Z be 0. The input tensors have :math:`N` elements each and can be of any shape 2025-07-17T07:36:44.9378996Z that the distance function can handle. 2025-07-17T07:36:44.9379221Z 2025-07-17T07:36:44.9379333Z If :attr:`reduction` is not ``'none'`` 2025-07-17T07:36:44.9379655Z (default ``'mean'``), then: 2025-07-17T07:36:44.9379836Z 2025-07-17T07:36:44.9379931Z .. math:: 2025-07-17T07:36:44.9380137Z \ell(x, y) = 2025-07-17T07:36:44.9380375Z \begin{cases} 2025-07-17T07:36:44.9380730Z \operatorname{mean}(L), & \text{if reduction} = \text{`mean';}\\ 2025-07-17T07:36:44.9381283Z \operatorname{sum}(L), & \text{if reduction} = \text{`sum'.} 2025-07-17T07:36:44.9381667Z \end{cases} 2025-07-17T07:36:44.9381818Z 2025-07-17T07:36:44.9382050Z See also :class:`~torch.nn.TripletMarginLoss`, which computes the triplet 2025-07-17T07:36:44.9382764Z loss for input tensors using the :math:`l_p` distance as the distance function. 2025-07-17T07:36:44.9383381Z 2025-07-17T07:36:44.9383506Z Args: 2025-07-17T07:36:44.9384105Z distance_function (Callable, optional): A nonnegative, real-valued function that 2025-07-17T07:36:44.9384852Z quantifies the closeness of two tensors. If not specified, 2025-07-17T07:36:44.9385333Z `nn.PairwiseDistance` will be used. Default: ``None`` 2025-07-17T07:36:44.9385944Z margin (float, optional): A nonnegative margin representing the minimum difference 2025-07-17T07:36:44.9386666Z between the positive and negative distances required for the loss to be 0. Larger 2025-07-17T07:36:44.9387409Z margins penalize cases where the negative examples are not distant enough from the 2025-07-17T07:36:44.9388045Z anchors, relative to the positives. Default: :math:`1`. 2025-07-17T07:36:44.9388633Z swap (bool, optional): Whether to use the distance swap described in the paper 2025-07-17T07:36:44.9389474Z `Learning shallow convolutional feature descriptors with triplet losses` by 2025-07-17T07:36:44.9390143Z V. Balntas, E. Riba et al. If True, and if the positive example is closer to the 2025-07-17T07:36:44.9390777Z negative example than the anchor is, swaps the positive example and the anchor in 2025-07-17T07:36:44.9391333Z the loss computation. Default: ``False``. 2025-07-17T07:36:44.9391911Z reduction (str, optional): Specifies the (optional) reduction to apply to the output: 2025-07-17T07:36:44.9392547Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-07-17T07:36:44.9393127Z ``'mean'``: the sum of the output will be divided by the number of 2025-07-17T07:36:44.9393682Z elements in the output, ``'sum'``: the output will be summed. Default: ``'mean'`` 2025-07-17T07:36:44.9394096Z 2025-07-17T07:36:44.9394100Z 2025-07-17T07:36:44.9394202Z Shape: 2025-07-17T07:36:44.9394575Z - Input: :math:`(N, *)` where :math:`*` represents any number of additional dimensions 2025-07-17T07:36:44.9395103Z as supported by the distance function. 2025-07-17T07:36:44.9395646Z - Output: A Tensor of shape :math:`(N)` if :attr:`reduction` is ``'none'``, or a scalar 2025-07-17T07:36:44.9396123Z otherwise. 2025-07-17T07:36:44.9396316Z 2025-07-17T07:36:44.9396402Z Examples: 2025-07-17T07:36:44.9396595Z 2025-07-17T07:36:44.9396709Z >>> # Initialize embeddings 2025-07-17T07:36:44.9397057Z >>> embedding = nn.Embedding(1000, 128) 2025-07-17T07:36:44.9397409Z >>> anchor_ids = torch.randint(0, 1000, (1,)) 2025-07-17T07:36:44.9397831Z >>> positive_ids = torch.randint(0, 1000, (1,)) 2025-07-17T07:36:44.9398189Z >>> negative_ids = torch.randint(0, 1000, (1,)) 2025-07-17T07:36:44.9398594Z >>> anchor = embedding(anchor_ids) 2025-07-17T07:36:44.9398931Z >>> positive = embedding(positive_ids) 2025-07-17T07:36:44.9399330Z >>> negative = embedding(negative_ids) 2025-07-17T07:36:44.9399671Z >>> 2025-07-17T07:36:44.9399892Z >>> # Built-in Distance Function 2025-07-17T07:36:44.9400256Z >>> triplet_loss = \ 2025-07-17T07:36:44.9400692Z >>> nn.TripletMarginWithDistanceLoss(distance_function=nn.PairwiseDistance()) 2025-07-17T07:36:44.9401304Z >>> output = triplet_loss(anchor, positive, negative) 2025-07-17T07:36:44.9401729Z >>> output.backward() 2025-07-17T07:36:44.9401971Z >>> 2025-07-17T07:36:44.9402193Z >>> # Custom Distance Function 2025-07-17T07:36:44.9402557Z >>> def l_infinity(x1, x2): 2025-07-17T07:36:44.9402882Z >>> return torch.max(torch.abs(x1 - x2), dim=1).values 2025-07-17T07:36:44.9403301Z >>> 2025-07-17T07:36:44.9403606Z >>> # xdoctest: +SKIP("FIXME: Would call backwards a second time") 2025-07-17T07:36:44.9404069Z >>> triplet_loss = ( 2025-07-17T07:36:44.9404503Z >>> nn.TripletMarginWithDistanceLoss(distance_function=l_infinity, margin=1.5)) 2025-07-17T07:36:44.9405123Z >>> output = triplet_loss(anchor, positive, negative) 2025-07-17T07:36:44.9405609Z >>> output.backward() 2025-07-17T07:36:44.9405851Z >>> 2025-07-17T07:36:44.9406082Z >>> # Custom Distance Function (Lambda) 2025-07-17T07:36:44.9406471Z >>> triplet_loss = ( 2025-07-17T07:36:44.9406779Z >>> nn.TripletMarginWithDistanceLoss( 2025-07-17T07:36:44.9407296Z >>> distance_function=lambda x, y: 1.0 - F.cosine_similarity(x, y))) 2025-07-17T07:36:44.9407785Z >>> output = triplet_loss(anchor, positive, negative) 2025-07-17T07:36:44.9408136Z >>> output.backward() 2025-07-17T07:36:44.9408320Z 2025-07-17T07:36:44.9408406Z Reference: 2025-07-17T07:36:44.9408906Z V. Balntas, et al.: Learning shallow convolutional feature descriptors with triplet losses: 2025-07-17T07:36:44.9409558Z https://bmva-archive.org.uk/bmvc/2016/papers/paper119/index.html 2025-07-17T07:36:44.9409959Z 2025-07-17T07:36:44.9410328Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 17)) 2025-07-17T07:36:44.9410852Z 2025-07-17T07:36:44.9411357Z msg = Cannot scrape callname=CTCLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1852. 2025-07-17T07:36:44.9412227Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.9412738Z The Connectionist Temporal Classification loss. 2025-07-17T07:36:44.9413005Z 2025-07-17T07:36:44.9413381Z Calculates loss between a continuous (unsegmented) time series and a target sequence. CTCLoss sums over the 2025-07-17T07:36:44.9414304Z probability of possible alignments of input to target, producing a loss value which is differentiable 2025-07-17T07:36:44.9415172Z with respect to each input node. The alignment of input to target is assumed to be "many-to-one", which 2025-07-17T07:36:44.9415924Z limits the length of the target sequence such that it must be :math:`\leq` the input length. 2025-07-17T07:36:44.9416358Z 2025-07-17T07:36:44.9416440Z Args: 2025-07-17T07:36:44.9416730Z blank (int, optional): blank label. Default :math:`0`. 2025-07-17T07:36:44.9417238Z reduction (str, optional): Specifies the reduction to apply to the output: 2025-07-17T07:36:44.9417784Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-07-17T07:36:44.9418300Z ``'mean'``: the output losses will be divided by the target lengths and 2025-07-17T07:36:44.9418874Z then the mean over the batch is taken, ``'sum'``: the output losses will be summed. 2025-07-17T07:36:44.9419329Z Default: ``'mean'`` 2025-07-17T07:36:44.9419634Z zero_infinity (bool, optional): 2025-07-17T07:36:44.9420047Z Whether to zero infinite losses and the associated gradients. 2025-07-17T07:36:44.9420447Z Default: ``False`` 2025-07-17T07:36:44.9420819Z Infinite losses mainly occur when the inputs are too short 2025-07-17T07:36:44.9421236Z to be aligned to the targets. 2025-07-17T07:36:44.9421505Z 2025-07-17T07:36:44.9421596Z Shape: 2025-07-17T07:36:44.9421911Z - Log_probs: Tensor of size :math:`(T, N, C)` or :math:`(T, C)`, 2025-07-17T07:36:44.9422340Z where :math:`T = \text{input length}`, 2025-07-17T07:36:44.9422672Z :math:`N = \text{batch size}`, and 2025-07-17T07:36:44.9423059Z :math:`C = \text{number of classes (including blank)}`. 2025-07-17T07:36:44.9423559Z The logarithmized probabilities of the outputs (e.g. obtained with 2025-07-17T07:36:44.9424041Z :func:`torch.nn.functional.log_softmax`). 2025-07-17T07:36:44.9424409Z - Targets: Tensor of size :math:`(N, S)` or 2025-07-17T07:36:44.9424810Z :math:`(\operatorname{sum}(\text{target\_lengths}))`, 2025-07-17T07:36:44.9425241Z where :math:`N = \text{batch size}` and 2025-07-17T07:36:44.9425626Z :math:`S = \text{max target length, if shape is } (N, S)`. 2025-07-17T07:36:44.9426111Z It represents the target sequences. Each element in the target 2025-07-17T07:36:44.9426664Z sequence is a class index. And the target index cannot be blank (default=0). 2025-07-17T07:36:44.9427183Z In the :math:`(N, S)` form, targets are padded to the 2025-07-17T07:36:44.9427577Z length of the longest sequence, and stacked. 2025-07-17T07:36:44.9428012Z In the :math:`(\operatorname{sum}(\text{target\_lengths}))` form, 2025-07-17T07:36:44.9428456Z the targets are assumed to be un-padded and 2025-07-17T07:36:44.9428805Z concatenated within 1 dimension. 2025-07-17T07:36:44.9429236Z - Input_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-07-17T07:36:44.9429757Z where :math:`N = \text{batch size}`. It represents the lengths of the 2025-07-17T07:36:44.9430275Z inputs (must each be :math:`\leq T`). And the lengths are specified 2025-07-17T07:36:44.9430810Z for each sequence to achieve masking under the assumption that sequences 2025-07-17T07:36:44.9431409Z are padded to equal lengths. 2025-07-17T07:36:44.9431826Z - Target_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-07-17T07:36:44.9432354Z where :math:`N = \text{batch size}`. It represents lengths of the targets. 2025-07-17T07:36:44.9432907Z Lengths are specified for each sequence to achieve masking under the 2025-07-17T07:36:44.9433499Z assumption that sequences are padded to equal lengths. If target shape is 2025-07-17T07:36:44.9434032Z :math:`(N,S)`, target_lengths are effectively the stop index 2025-07-17T07:36:44.9434617Z :math:`s_n` for each target sequence, such that ``target_n = targets[n,0:s_n]`` for 2025-07-17T07:36:44.9435246Z each target in a batch. Lengths must each be :math:`\leq S` 2025-07-17T07:36:44.9435778Z If the targets are given as a 1d tensor that is the concatenation of individual 2025-07-17T07:36:44.9436368Z targets, the target_lengths must add up to the total length of the tensor. 2025-07-17T07:36:44.9436915Z - Output: scalar if :attr:`reduction` is ``'mean'`` (default) or 2025-07-17T07:36:44.9437450Z ``'sum'``. If :attr:`reduction` is ``'none'``, then :math:`(N)` if input is batched or 2025-07-17T07:36:44.9438039Z :math:`()` if input is unbatched, where :math:`N = \text{batch size}`. 2025-07-17T07:36:44.9438349Z 2025-07-17T07:36:44.9438434Z Examples: 2025-07-17T07:36:44.9438577Z 2025-07-17T07:36:44.9438711Z >>> # Target are to be padded 2025-07-17T07:36:44.9439034Z >>> T = 50 # Input sequence length 2025-07-17T07:36:44.9439375Z >>> C = 20 # Number of classes (including blank) 2025-07-17T07:36:44.9439733Z >>> N = 16 # Batch size 2025-07-17T07:36:44.9440144Z >>> S = 30 # Target sequence length of longest target in batch (padding length) 2025-07-17T07:36:44.9440674Z >>> S_min = 10 # Minimum target length, for demonstration purposes 2025-07-17T07:36:44.9441055Z >>> 2025-07-17T07:36:44.9441376Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-07-17T07:36:44.9441901Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-07-17T07:36:44.9442297Z >>> 2025-07-17T07:36:44.9442611Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-07-17T07:36:44.9443133Z >>> target = torch.randint(low=1, high=C, size=(N, S), dtype=torch.long) 2025-07-17T07:36:44.9443606Z >>> 2025-07-17T07:36:44.9443932Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-07-17T07:36:44.9444385Z >>> target_lengths = torch.randint( 2025-07-17T07:36:44.9444699Z ... low=S_min, 2025-07-17T07:36:44.9444960Z ... high=S, 2025-07-17T07:36:44.9445203Z ... size=(N,), 2025-07-17T07:36:44.9445568Z ... dtype=torch.long, 2025-07-17T07:36:44.9445837Z ... ) 2025-07-17T07:36:44.9446076Z >>> ctc_loss = nn.CTCLoss() 2025-07-17T07:36:44.9446459Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-07-17T07:36:44.9446847Z >>> loss.backward() 2025-07-17T07:36:44.9447108Z >>> 2025-07-17T07:36:44.9447314Z >>> 2025-07-17T07:36:44.9447532Z >>> # Target are to be un-padded 2025-07-17T07:36:44.9447857Z >>> T = 50 # Input sequence length 2025-07-17T07:36:44.9448206Z >>> C = 20 # Number of classes (including blank) 2025-07-17T07:36:44.9448544Z >>> N = 16 # Batch size 2025-07-17T07:36:44.9448796Z >>> 2025-07-17T07:36:44.9449114Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-07-17T07:36:44.9449633Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-07-17T07:36:44.9450163Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-07-17T07:36:44.9450585Z >>> 2025-07-17T07:36:44.9450989Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-07-17T07:36:44.9451525Z >>> target_lengths = torch.randint(low=1, high=T, size=(N,), dtype=torch.long) 2025-07-17T07:36:44.9451989Z >>> target = torch.randint( 2025-07-17T07:36:44.9452282Z ... low=1, 2025-07-17T07:36:44.9452523Z ... high=C, 2025-07-17T07:36:44.9452782Z ... size=(sum(target_lengths),), 2025-07-17T07:36:44.9453109Z ... dtype=torch.long, 2025-07-17T07:36:44.9453389Z ... ) 2025-07-17T07:36:44.9453605Z >>> ctc_loss = nn.CTCLoss() 2025-07-17T07:36:44.9454037Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-07-17T07:36:44.9454441Z >>> loss.backward() 2025-07-17T07:36:44.9454686Z >>> 2025-07-17T07:36:44.9454890Z >>> 2025-07-17T07:36:44.9455196Z >>> # Target are to be un-padded and unbatched (effectively N=1) 2025-07-17T07:36:44.9455657Z >>> T = 50 # Input sequence length 2025-07-17T07:36:44.9456013Z >>> C = 20 # Number of classes (including blank) 2025-07-17T07:36:44.9456341Z >>> 2025-07-17T07:36:44.9456654Z >>> # Initialize random batch of input vectors, for *size = (T,C) 2025-07-17T07:36:44.9457089Z >>> # xdoctest: +SKIP("FIXME: error in doctest") 2025-07-17T07:36:44.9457535Z >>> input = torch.randn(T, C).log_softmax(1).detach().requires_grad_() 2025-07-17T07:36:44.9458012Z >>> input_lengths = torch.tensor(T, dtype=torch.long) 2025-07-17T07:36:44.9458355Z >>> 2025-07-17T07:36:44.9458677Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-07-17T07:36:44.9459227Z >>> target_lengths = torch.randint(low=1, high=T, size=(), dtype=torch.long) 2025-07-17T07:36:44.9459680Z >>> target = torch.randint( 2025-07-17T07:36:44.9459973Z ... low=1, 2025-07-17T07:36:44.9460215Z ... high=C, 2025-07-17T07:36:44.9460477Z ... size=(target_lengths,), 2025-07-17T07:36:44.9460781Z ... dtype=torch.long, 2025-07-17T07:36:44.9461136Z ... ) 2025-07-17T07:36:44.9461377Z >>> ctc_loss = nn.CTCLoss() 2025-07-17T07:36:44.9461752Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-07-17T07:36:44.9462154Z >>> loss.backward() 2025-07-17T07:36:44.9462327Z 2025-07-17T07:36:44.9462426Z Reference: 2025-07-17T07:36:44.9462721Z A. Graves et al.: Connectionist Temporal Classification: 2025-07-17T07:36:44.9463234Z Labelling Unsegmented Sequence Data with Recurrent Neural Networks: 2025-07-17T07:36:44.9463743Z https://www.cs.toronto.edu/~graves/icml_2006.pdf 2025-07-17T07:36:44.9464009Z 2025-07-17T07:36:44.9464104Z Note: 2025-07-17T07:36:44.9464450Z In order to use CuDNN, the following must be satisfied: :attr:`targets` must be 2025-07-17T07:36:44.9465065Z in concatenated format, all :attr:`input_lengths` must be `T`. :math:`blank=0`, 2025-07-17T07:36:44.9465662Z :attr:`target_lengths` :math:`\leq 256`, the integer arguments must be of 2025-07-17T07:36:44.9466093Z dtype :attr:`torch.int32`. 2025-07-17T07:36:44.9466300Z 2025-07-17T07:36:44.9466569Z The regular implementation uses the (more common in PyTorch) `torch.long` dtype. 2025-07-17T07:36:44.9466966Z 2025-07-17T07:36:44.9466971Z 2025-07-17T07:36:44.9467050Z Note: 2025-07-17T07:36:44.9467411Z In some circumstances when using the CUDA backend with CuDNN, this operator 2025-07-17T07:36:44.9468019Z may select a nondeterministic algorithm to increase performance. If this is 2025-07-17T07:36:44.9468638Z undesirable, you can try to make the operation deterministic (potentially at 2025-07-17T07:36:44.9469233Z a performance cost) by setting ``torch.backends.cudnn.deterministic = 2025-07-17T07:36:44.9469656Z True``. 2025-07-17T07:36:44.9470128Z Please see the notes on :doc:`/notes/randomness` for background. 2025-07-17T07:36:44.9470650Z 2025-07-17T07:36:44.9471017Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.9471382Z 2025-07-17T07:36:44.9914947Z msg = Cannot scrape callname=MaxUnpool2d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py line=406. 2025-07-17T07:36:44.9916113Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:44.9916650Z Computes a partial inverse of :class:`MaxPool2d`. 2025-07-17T07:36:44.9916922Z 2025-07-17T07:36:44.9917179Z :class:`MaxPool2d` is not fully invertible, since the non-maximal values are lost. 2025-07-17T07:36:44.9917556Z 2025-07-17T07:36:44.9917972Z :class:`MaxUnpool2d` takes in as input the output of :class:`MaxPool2d` 2025-07-17T07:36:44.9918547Z including the indices of the maximal values and computes a partial inverse 2025-07-17T07:36:44.9919050Z in which all non-maximal values are set to zero. 2025-07-17T07:36:44.9919312Z 2025-07-17T07:36:44.9919400Z Note: 2025-07-17T07:36:44.9919836Z This operation may behave nondeterministically when the input indices has repeat values. 2025-07-17T07:36:44.9920645Z See https://github.com/pytorch/pytorch/issues/80827 and :doc:`/notes/randomness` for more information. 2025-07-17T07:36:44.9921149Z 2025-07-17T07:36:44.9921384Z .. note:: :class:`MaxPool2d` can map several input sizes to the same output 2025-07-17T07:36:44.9921904Z sizes. Hence, the inversion process can get ambiguous. 2025-07-17T07:36:44.9922383Z To accommodate this, you can provide the needed output size 2025-07-17T07:36:44.9922887Z as an additional argument :attr:`output_size` in the forward call. 2025-07-17T07:36:44.9923333Z See the Inputs and Example below. 2025-07-17T07:36:44.9923558Z 2025-07-17T07:36:44.9923654Z Args: 2025-07-17T07:36:44.9923943Z kernel_size (int or tuple): Size of the max pooling window. 2025-07-17T07:36:44.9924409Z stride (int or tuple): Stride of the max pooling window. 2025-07-17T07:36:44.9924833Z It is set to :attr:`kernel_size` by default. 2025-07-17T07:36:44.9925249Z padding (int or tuple): Padding that was added to the input 2025-07-17T07:36:44.9925636Z 2025-07-17T07:36:44.9925720Z Inputs: 2025-07-17T07:36:44.9925968Z - `input`: the input Tensor to invert 2025-07-17T07:36:44.9926401Z - `indices`: the indices given out by :class:`~torch.nn.MaxPool2d` 2025-07-17T07:36:44.9926867Z - `output_size` (optional): the targeted output size 2025-07-17T07:36:44.9927147Z 2025-07-17T07:36:44.9927229Z Shape: 2025-07-17T07:36:44.9927540Z - Input: :math:`(N, C, H_{in}, W_{in})` or :math:`(C, H_{in}, W_{in})`. 2025-07-17T07:36:44.9928041Z - Output: :math:`(N, C, H_{out}, W_{out})` or :math:`(C, H_{out}, W_{out})`, where 2025-07-17T07:36:44.9928378Z 2025-07-17T07:36:44.9928466Z .. math:: 2025-07-17T07:36:44.9928875Z H_{out} = (H_{in} - 1) \times \text{stride[0]} - 2 \times \text{padding[0]} + \text{kernel\_size[0]} 2025-07-17T07:36:44.9929255Z 2025-07-17T07:36:44.9929352Z .. math:: 2025-07-17T07:36:44.9929728Z W_{out} = (W_{in} - 1) \times \text{stride[1]} - 2 \times \text{padding[1]} + \text{kernel\_size[1]} 2025-07-17T07:36:44.9930112Z 2025-07-17T07:36:44.9930270Z or as given by :attr:`output_size` in the call operator 2025-07-17T07:36:44.9930552Z 2025-07-17T07:36:44.9930637Z Example:: 2025-07-17T07:36:44.9930767Z 2025-07-17T07:36:44.9930936Z >>> pool = nn.MaxPool2d(2, stride=2, return_indices=True) 2025-07-17T07:36:44.9931323Z >>> unpool = nn.MaxUnpool2d(2, stride=2) 2025-07-17T07:36:44.9931689Z >>> input = torch.tensor([[[[ 1., 2., 3., 4.], 2025-07-17T07:36:44.9932037Z [ 5., 6., 7., 8.], 2025-07-17T07:36:44.9932351Z [ 9., 10., 11., 12.], 2025-07-17T07:36:44.9932688Z [13., 14., 15., 16.]]]]) 2025-07-17T07:36:44.9933123Z >>> output, indices = pool(input) 2025-07-17T07:36:44.9933450Z >>> unpool(output, indices) 2025-07-17T07:36:44.9933740Z tensor([[[[ 0., 0., 0., 0.], 2025-07-17T07:36:44.9934048Z [ 0., 6., 0., 8.], 2025-07-17T07:36:44.9934347Z [ 0., 0., 0., 0.], 2025-07-17T07:36:44.9934639Z [ 0., 14., 0., 16.]]]]) 2025-07-17T07:36:44.9935057Z >>> # Now using output_size to resolve an ambiguous size for the inverse 2025-07-17T07:36:44.9935530Z >>> input = torch.tensor([[[[ 1., 2., 3., 4., 5.], 2025-07-17T07:36:44.9935942Z [ 6., 7., 8., 9., 10.], 2025-07-17T07:36:44.9936277Z [11., 12., 13., 14., 15.], 2025-07-17T07:36:44.9936616Z [16., 17., 18., 19., 20.]]]]) 2025-07-17T07:36:44.9936960Z >>> output, indices = pool(input) 2025-07-17T07:36:44.9937341Z >>> # This call will not work without specifying output_size 2025-07-17T07:36:44.9937778Z >>> unpool(output, indices, output_size=input.size()) 2025-07-17T07:36:44.9938150Z tensor([[[[ 0., 0., 0., 0., 0.], 2025-07-17T07:36:44.9938447Z [ 0., 7., 0., 9., 0.], 2025-07-17T07:36:44.9938749Z [ 0., 0., 0., 0., 0.], 2025-07-17T07:36:44.9939051Z [ 0., 17., 0., 19., 0.]]]]) 2025-07-17T07:36:44.9939258Z 2025-07-17T07:36:44.9939263Z 2025-07-17T07:36:44.9939352Z 2025-07-17T07:36:44.9939706Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:44.9940080Z 2025-07-17T07:36:45.0190360Z msg = Cannot scrape callname=EmbeddingBag in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py line=272. 2025-07-17T07:36:45.0191389Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.0192156Z Compute sums or means of 'bags' of embeddings, without instantiating the intermediate embeddings. 2025-07-17T07:36:45.0192594Z 2025-07-17T07:36:45.0192992Z For bags of constant length, no :attr:`per_sample_weights`, no indices equal to :attr:`padding_idx`, 2025-07-17T07:36:45.0193589Z and with 2D inputs, this class 2025-07-17T07:36:45.0193799Z 2025-07-17T07:36:45.0194104Z * with ``mode="sum"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.sum(dim=1)``, 2025-07-17T07:36:45.0194899Z * with ``mode="mean"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.mean(dim=1)``, 2025-07-17T07:36:45.0195701Z * with ``mode="max"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.max(dim=1)``. 2025-07-17T07:36:45.0196180Z 2025-07-17T07:36:45.0196549Z However, :class:`~torch.nn.EmbeddingBag` is much more time and memory efficient than using a chain of these 2025-07-17T07:36:45.0197153Z operations. 2025-07-17T07:36:45.0197294Z 2025-07-17T07:36:45.0197622Z EmbeddingBag also supports per-sample weights as an argument to the forward 2025-07-17T07:36:45.0198299Z pass. This scales the output of the Embedding before performing a weighted 2025-07-17T07:36:45.0198922Z reduction as specified by ``mode``. If :attr:`per_sample_weights` is passed, the 2025-07-17T07:36:45.0199559Z only supported ``mode`` is ``"sum"``, which computes a weighted sum according to 2025-07-17T07:36:45.0200088Z :attr:`per_sample_weights`. 2025-07-17T07:36:45.0200276Z 2025-07-17T07:36:45.0200356Z Args: 2025-07-17T07:36:45.0200719Z num_embeddings (int): size of the dictionary of embeddings 2025-07-17T07:36:45.0201185Z embedding_dim (int): the size of each embedding vector 2025-07-17T07:36:45.0201848Z max_norm (float, optional): If given, each embedding vector with norm larger than :attr:`max_norm` 2025-07-17T07:36:45.0202490Z is renormalized to have norm :attr:`max_norm`. 2025-07-17T07:36:45.0203162Z norm_type (float, optional): The p of the p-norm to compute for the :attr:`max_norm` option. Default ``2``. 2025-07-17T07:36:45.0204165Z scale_grad_by_freq (bool, optional): if given, this will scale gradients by the inverse of frequency of 2025-07-17T07:36:45.0204829Z the words in the mini-batch. Default ``False``. 2025-07-17T07:36:45.0205421Z Note: this option is not supported when ``mode="max"``. 2025-07-17T07:36:45.0206035Z mode (str, optional): ``"sum"``, ``"mean"`` or ``"max"``. Specifies the way to reduce the bag. 2025-07-17T07:36:45.0206738Z ``"sum"`` computes the weighted sum, taking :attr:`per_sample_weights` 2025-07-17T07:36:45.0207319Z into consideration. ``"mean"`` computes the average of the values 2025-07-17T07:36:45.0207897Z in the bag, ``"max"`` computes the max value over each bag. 2025-07-17T07:36:45.0208369Z Default: ``"mean"`` 2025-07-17T07:36:45.0208914Z sparse (bool, optional): if ``True``, gradient w.r.t. :attr:`weight` matrix will be a sparse tensor. See 2025-07-17T07:36:45.0209663Z Notes for more details regarding sparse gradients. Note: this option is not 2025-07-17T07:36:45.0210233Z supported when ``mode="max"``. 2025-07-17T07:36:45.0210915Z include_last_offset (bool, optional): if ``True``, :attr:`offsets` has one additional element, where the last element 2025-07-17T07:36:45.0211693Z is equivalent to the size of `indices`. This matches the CSR format. 2025-07-17T07:36:45.0212420Z padding_idx (int, optional): If specified, the entries at :attr:`padding_idx` do not contribute to the 2025-07-17T07:36:45.0213211Z gradient; therefore, the embedding vector at :attr:`padding_idx` is not updated 2025-07-17T07:36:45.0213918Z during training, i.e. it remains as a fixed "pad". For a newly constructed 2025-07-17T07:36:45.0214608Z EmbeddingBag, the embedding vector at :attr:`padding_idx` will default to all 2025-07-17T07:36:45.0215231Z zeros, but can be updated to another value to be used as the padding vector. 2025-07-17T07:36:45.0215915Z Note that the embedding vector at :attr:`padding_idx` is excluded from the 2025-07-17T07:36:45.0216458Z reduction. 2025-07-17T07:36:45.0216672Z 2025-07-17T07:36:45.0216759Z Attributes: 2025-07-17T07:36:45.0217282Z weight (Tensor): the learnable weights of the module of shape `(num_embeddings, embedding_dim)` 2025-07-17T07:36:45.0217922Z initialized from :math:`\mathcal{N}(0, 1)`. 2025-07-17T07:36:45.0218174Z 2025-07-17T07:36:45.0218287Z Examples:: 2025-07-17T07:36:45.0218461Z 2025-07-17T07:36:45.0218644Z >>> # an EmbeddingBag module containing 10 tensors of size 3 2025-07-17T07:36:45.0219082Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum') 2025-07-17T07:36:45.0219560Z >>> # a batch of 2 samples of 4 indices each 2025-07-17T07:36:45.0220028Z >>> input = torch.tensor([1, 2, 4, 5, 4, 3, 2, 9], dtype=torch.long) 2025-07-17T07:36:45.0220487Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-07-17T07:36:45.0220952Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-07-17T07:36:45.0221324Z >>> embedding_sum(input, offsets) 2025-07-17T07:36:45.0221707Z tensor([[-0.8861, -5.4350, -0.0523], 2025-07-17T07:36:45.0222027Z [ 1.1306, -2.5798, -1.0044]]) 2025-07-17T07:36:45.0222247Z 2025-07-17T07:36:45.0222415Z >>> # Example with padding_idx 2025-07-17T07:36:45.0222844Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum', padding_idx=2) 2025-07-17T07:36:45.0223486Z >>> input = torch.tensor([2, 2, 2, 2, 4, 3, 2, 9], dtype=torch.long) 2025-07-17T07:36:45.0224010Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-07-17T07:36:45.0224389Z >>> embedding_sum(input, offsets) 2025-07-17T07:36:45.0224759Z tensor([[ 0.0000, 0.0000, 0.0000], 2025-07-17T07:36:45.0225078Z [-0.7082, 3.2145, -2.6251]]) 2025-07-17T07:36:45.0225284Z 2025-07-17T07:36:45.0225528Z >>> # An EmbeddingBag can be loaded from an Embedding like so 2025-07-17T07:36:45.0225968Z >>> embedding = nn.Embedding(10, 3, padding_idx=2) 2025-07-17T07:36:45.0226433Z >>> embedding_sum = nn.EmbeddingBag.from_pretrained( 2025-07-17T07:36:45.0226879Z embedding.weight, 2025-07-17T07:36:45.0227265Z padding_idx=embedding.padding_idx, 2025-07-17T07:36:45.0227586Z mode='sum') 2025-07-17T07:36:45.0227840Z 2025-07-17T07:36:45.0228267Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.0228636Z 2025-07-17T07:36:45.0261808Z msg = Cannot scrape callname=Transformer.forward in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py line=186. 2025-07-17T07:36:45.0262780Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.0263308Z Take in and process masked source/target sequences. 2025-07-17T07:36:45.0263577Z 2025-07-17T07:36:45.0263668Z .. note:: 2025-07-17T07:36:45.0263799Z 2025-07-17T07:36:45.0264194Z If a boolean tensor is provided for any of the [src/tgt/memory]_mask arguments, positions with a ``True`` value are 2025-07-17T07:36:45.0264835Z not allowed to participate in the attention, 2025-07-17T07:36:45.0265278Z which is the opposite of the definition for :attr:`attn_mask` 2025-07-17T07:36:45.0265771Z in :func:`torch.nn.functional.scaled_dot_product_attention`. 2025-07-17T07:36:45.0266073Z 2025-07-17T07:36:45.0266173Z Args: 2025-07-17T07:36:45.0266428Z src: the sequence to the encoder (required). 2025-07-17T07:36:45.0266817Z tgt: the sequence to the decoder (required). 2025-07-17T07:36:45.0267249Z src_mask: the additive mask for the src sequence (optional). 2025-07-17T07:36:45.0267718Z tgt_mask: the additive mask for the tgt sequence (optional). 2025-07-17T07:36:45.0268223Z memory_mask: the additive mask for the encoder output (optional). 2025-07-17T07:36:45.0268773Z src_key_padding_mask: the Tensor mask for src keys per batch (optional). 2025-07-17T07:36:45.0269337Z tgt_key_padding_mask: the Tensor mask for tgt keys per batch (optional). 2025-07-17T07:36:45.0269932Z memory_key_padding_mask: the Tensor mask for memory keys per batch (optional). 2025-07-17T07:36:45.0270661Z src_is_causal: If specified, applies a causal mask as ``src_mask``. 2025-07-17T07:36:45.0271132Z Default: ``None``; try to detect a causal mask. 2025-07-17T07:36:45.0271477Z Warning: 2025-07-17T07:36:45.0271795Z ``src_is_causal`` provides a hint that ``src_mask`` is 2025-07-17T07:36:45.0272245Z the causal mask. Providing incorrect hints can result in 2025-07-17T07:36:45.0272689Z incorrect execution, including forward and backward 2025-07-17T07:36:45.0273065Z compatibility. 2025-07-17T07:36:45.0273458Z tgt_is_causal: If specified, applies a causal mask as ``tgt_mask``. 2025-07-17T07:36:45.0273927Z Default: ``None``; try to detect a causal mask. 2025-07-17T07:36:45.0274263Z Warning: 2025-07-17T07:36:45.0274585Z ``tgt_is_causal`` provides a hint that ``tgt_mask`` is 2025-07-17T07:36:45.0275033Z the causal mask. Providing incorrect hints can result in 2025-07-17T07:36:45.0275476Z incorrect execution, including forward and backward 2025-07-17T07:36:45.0276030Z compatibility. 2025-07-17T07:36:45.0276395Z memory_is_causal: If specified, applies a causal mask as 2025-07-17T07:36:45.0276786Z ``memory_mask``. 2025-07-17T07:36:45.0277059Z Default: ``False``. 2025-07-17T07:36:45.0277353Z Warning: 2025-07-17T07:36:45.0277647Z ``memory_is_causal`` provides a hint that 2025-07-17T07:36:45.0278041Z ``memory_mask`` is the causal mask. Providing incorrect 2025-07-17T07:36:45.0278477Z hints can result in incorrect execution, including 2025-07-17T07:36:45.0278873Z forward and backward compatibility. 2025-07-17T07:36:45.0279107Z 2025-07-17T07:36:45.0279294Z Shape: 2025-07-17T07:36:45.0279677Z - src: :math:`(S, E)` for unbatched input, :math:`(S, N, E)` if `batch_first=False` or 2025-07-17T07:36:45.0280152Z `(N, S, E)` if `batch_first=True`. 2025-07-17T07:36:45.0280622Z - tgt: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-07-17T07:36:45.0281107Z `(N, T, E)` if `batch_first=True`. 2025-07-17T07:36:45.0281520Z - src_mask: :math:`(S, S)` or :math:`(N\cdot\text{num\_heads}, S, S)`. 2025-07-17T07:36:45.0282090Z - tgt_mask: :math:`(T, T)` or :math:`(N\cdot\text{num\_heads}, T, T)`. 2025-07-17T07:36:45.0282510Z - memory_mask: :math:`(T, S)`. 2025-07-17T07:36:45.0282960Z - src_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-07-17T07:36:45.0283596Z - tgt_key_padding_mask: :math:`(T)` for unbatched input otherwise :math:`(N, T)`. 2025-07-17T07:36:45.0284233Z - memory_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-07-17T07:36:45.0284603Z 2025-07-17T07:36:45.0284923Z Note: [src/tgt/memory]_mask ensures that position :math:`i` is allowed to attend the unmasked 2025-07-17T07:36:45.0285623Z positions. If a BoolTensor is provided, positions with ``True`` 2025-07-17T07:36:45.0286213Z are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor 2025-07-17T07:36:45.0286757Z is provided, it will be added to the attention weight. 2025-07-17T07:36:45.0287329Z [src/tgt/memory]_key_padding_mask provides specified elements in the key to be ignored by 2025-07-17T07:36:45.0287968Z the attention. If a BoolTensor is provided, the positions with the 2025-07-17T07:36:45.0288608Z value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged. 2025-07-17T07:36:45.0289033Z 2025-07-17T07:36:45.0289305Z - output: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-07-17T07:36:45.0289786Z `(N, T, E)` if `batch_first=True`. 2025-07-17T07:36:45.0290022Z 2025-07-17T07:36:45.0290261Z Note: Due to the multi-head attention architecture in the transformer model, 2025-07-17T07:36:45.0290935Z the output sequence length of a transformer is same as the input sequence 2025-07-17T07:36:45.0291422Z (i.e. target) length of the decoder. 2025-07-17T07:36:45.0291731Z 2025-07-17T07:36:45.0292052Z where :math:`S` is the source sequence length, :math:`T` is the target sequence length, :math:`N` is the 2025-07-17T07:36:45.0292621Z batch size, :math:`E` is the feature number 2025-07-17T07:36:45.0292859Z 2025-07-17T07:36:45.0292954Z Examples: 2025-07-17T07:36:45.0293192Z >>> # xdoctest: +SKIP 2025-07-17T07:36:45.0293487Z >>> output = transformer_model( 2025-07-17T07:36:45.0293858Z ... src, tgt, src_mask=src_mask, tgt_mask=tgt_mask 2025-07-17T07:36:45.0294201Z ... ) 2025-07-17T07:36:45.0294408Z 2025-07-17T07:36:45.0294776Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.0295142Z 2025-07-17T07:36:45.0529578Z msg = Cannot scrape callname=DistributedDataParallel.join in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=1766. 2025-07-17T07:36:45.0530741Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.0531123Z 2025-07-17T07:36:45.0531361Z Context manager for training with uneven inputs across processes in DDP. 2025-07-17T07:36:45.0531734Z 2025-07-17T07:36:45.0531959Z This context manager will keep track of already-joined DDP processes, 2025-07-17T07:36:45.0532509Z and "shadow" the forward and backward passes by inserting collective 2025-07-17T07:36:45.0533267Z communication operations to match with the ones created by non-joined 2025-07-17T07:36:45.0533842Z DDP processes. This will ensure each collective call has a corresponding 2025-07-17T07:36:45.0534421Z call by already-joined DDP processes, preventing hangs or errors that 2025-07-17T07:36:45.0534964Z would otherwise happen when training with uneven inputs across 2025-07-17T07:36:45.0535531Z processes. Alternatively, if the flag ``throw_on_early_termination`` is 2025-07-17T07:36:45.0536085Z specified to be ``True``, all trainers will throw an error once one rank 2025-07-17T07:36:45.0536614Z runs out of inputs, allowing these errors to be caught and handled 2025-07-17T07:36:45.0537043Z according to application logic. 2025-07-17T07:36:45.0537236Z 2025-07-17T07:36:45.0537449Z Once all DDP processes have joined, the context manager will broadcast 2025-07-17T07:36:45.0538013Z the model corresponding to the last joined process to all processes to 2025-07-17T07:36:45.0538507Z ensure the model is the same across all processes 2025-07-17T07:36:45.0538864Z (which is guaranteed by DDP). 2025-07-17T07:36:45.0539064Z 2025-07-17T07:36:45.0539265Z To use this to enable training with uneven inputs across processes, 2025-07-17T07:36:45.0539804Z simply wrap this context manager around your training loop. No further 2025-07-17T07:36:45.0540313Z modifications to the model or data loading is required. 2025-07-17T07:36:45.0540596Z 2025-07-17T07:36:45.0540693Z .. warning:: 2025-07-17T07:36:45.0541030Z If the model or training loop this context manager is wrapped around 2025-07-17T07:36:45.0541536Z has additional distributed collective operations, such as 2025-07-17T07:36:45.0542006Z ``SyncBatchNorm`` in the model's forward pass, then the flag 2025-07-17T07:36:45.0542507Z ``throw_on_early_termination`` must be enabled. This is because this 2025-07-17T07:36:45.0543040Z context manager is not aware of non-DDP collective communication. 2025-07-17T07:36:45.0543533Z This flag will cause all ranks to throw when any one rank 2025-07-17T07:36:45.0544022Z exhausts inputs, allowing these errors to be caught and recovered 2025-07-17T07:36:45.0544448Z from across all ranks. 2025-07-17T07:36:45.0544619Z 2025-07-17T07:36:45.0544712Z Args: 2025-07-17T07:36:45.0544997Z divide_by_initial_world_size (bool): If ``True``, will divide 2025-07-17T07:36:45.0545524Z gradients by the initial ``world_size`` DDP training was launched 2025-07-17T07:36:45.0546081Z with. If ``False``, will compute the effective world size 2025-07-17T07:36:45.0546551Z (number of ranks that have not depleted their inputs yet) and 2025-07-17T07:36:45.0546991Z divide gradients by that during allreduce. Set 2025-07-17T07:36:45.0547423Z ``divide_by_initial_world_size=True`` to ensure every input 2025-07-17T07:36:45.0547926Z sample including the uneven inputs have equal weight in terms of 2025-07-17T07:36:45.0548410Z how much they contribute to the global gradient. This is 2025-07-17T07:36:45.0548871Z achieved by always dividing the gradient by the initial 2025-07-17T07:36:45.0549337Z ``world_size`` even when we encounter uneven inputs. If you set 2025-07-17T07:36:45.0549808Z this to ``False``, we divide the gradient by the remaining 2025-07-17T07:36:45.0550272Z number of nodes. This ensures parity with training on a smaller 2025-07-17T07:36:45.0550869Z ``world_size`` although it also means the uneven inputs would 2025-07-17T07:36:45.0551387Z contribute more towards the global gradient. Typically, you 2025-07-17T07:36:45.0551879Z would want to set this to ``True`` for cases where the last few 2025-07-17T07:36:45.0552364Z inputs of your training job are uneven. In extreme cases, where 2025-07-17T07:36:45.0552861Z there is a large discrepancy in the number of inputs, setting 2025-07-17T07:36:45.0553302Z this to ``False`` might provide better results. 2025-07-17T07:36:45.0553756Z enable (bool): Whether to enable uneven input detection or not. Pass 2025-07-17T07:36:45.0554322Z in ``enable=False`` to disable in cases where you know that 2025-07-17T07:36:45.0554802Z inputs are even across participating processes. Default is 2025-07-17T07:36:45.0555218Z ``True``. 2025-07-17T07:36:45.0555526Z throw_on_early_termination (bool): Whether to throw an error 2025-07-17T07:36:45.0556003Z or continue training when at least one rank has exhausted 2025-07-17T07:36:45.0556589Z inputs. If ``True``, will throw upon the first rank reaching end 2025-07-17T07:36:45.0557100Z of data. If ``False``, will continue training with a smaller 2025-07-17T07:36:45.0557714Z effective world size until all ranks are joined. Note that if 2025-07-17T07:36:45.0558463Z this flag is specified, then the flag 2025-07-17T07:36:45.0559067Z ``divide_by_initial_world_size`` would be ignored. Default 2025-07-17T07:36:45.0559433Z is ``False``. 2025-07-17T07:36:45.0559593Z 2025-07-17T07:36:45.0559597Z 2025-07-17T07:36:45.0559697Z Example:: 2025-07-17T07:36:45.0559817Z 2025-07-17T07:36:45.0559939Z >>> # xdoctest: +SKIP("Distributed") 2025-07-17T07:36:45.0560237Z >>> import torch 2025-07-17T07:36:45.0560504Z >>> import torch.distributed as dist 2025-07-17T07:36:45.0560811Z >>> import os 2025-07-17T07:36:45.0561065Z >>> import torch.multiprocessing as mp 2025-07-17T07:36:45.0561396Z >>> import torch.nn as nn 2025-07-17T07:36:45.0561729Z >>> # On each spawned worker 2025-07-17T07:36:45.0562003Z >>> def worker(rank): 2025-07-17T07:36:45.0562342Z >>> dist.init_process_group("nccl", rank=rank, world_size=2) 2025-07-17T07:36:45.0562739Z >>> torch.cuda.set_device(rank) 2025-07-17T07:36:45.0563083Z >>> model = nn.Linear(1, 1, bias=False).to(rank) 2025-07-17T07:36:45.0563486Z >>> model = torch.nn.parallel.DistributedDataParallel( 2025-07-17T07:36:45.0563910Z >>> model, device_ids=[rank], output_device=rank 2025-07-17T07:36:45.0564242Z >>> ) 2025-07-17T07:36:45.0564493Z >>> # Rank 1 gets one more input than rank 0. 2025-07-17T07:36:45.0564914Z >>> inputs = [torch.tensor([1]).float() for _ in range(10 + rank)] 2025-07-17T07:36:45.0565390Z >>> with model.join(): 2025-07-17T07:36:45.0565665Z >>> for _ in range(5): 2025-07-17T07:36:45.0565969Z >>> for inp in inputs: 2025-07-17T07:36:45.0566332Z >>> loss = model(inp).sum() 2025-07-17T07:36:45.0566665Z >>> loss.backward() 2025-07-17T07:36:45.0567050Z >>> # Without the join() API, the below synchronization will hang 2025-07-17T07:36:45.0567519Z >>> # blocking for rank 1's allreduce to complete. 2025-07-17T07:36:45.0567900Z >>> torch.cuda.synchronize(device=rank) 2025-07-17T07:36:45.0568133Z 2025-07-17T07:36:45.0568382Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.0568762Z 2025-07-17T07:36:45.0569516Z msg = Cannot scrape callname=DistributedDataParallel._register_fused_optim in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=2057. 2025-07-17T07:36:45.0570830Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.0571219Z 2025-07-17T07:36:45.0571522Z Register an optimizer in DDP to optimize parameter immediately after its gradient reduction. 2025-07-17T07:36:45.0572094Z 2025-07-17T07:36:45.0572310Z Registers an optimizer with DDP such that the optimization for a 2025-07-17T07:36:45.0572836Z parameter will run immediately when that parameter's gradient is 2025-07-17T07:36:45.0573363Z finished with reduction, instead of waiting for all parameters' 2025-07-17T07:36:45.0573919Z gradients to finish reduction. This can result in a training speedup 2025-07-17T07:36:45.0574473Z depending on your workload since the optimizer can run while gradient 2025-07-17T07:36:45.0575024Z reduction for other parameters are still ongoing. In addition, this has 2025-07-17T07:36:45.0575694Z the potential to reduce peak memory consumption during training, as it 2025-07-17T07:36:45.0576241Z only needs to load the per-parameter optimizer states of a single 2025-07-17T07:36:45.0576761Z parameter at a time, instead of loading all per-parameter optimizer 2025-07-17T07:36:45.0577210Z states at once. 2025-07-17T07:36:45.0577351Z 2025-07-17T07:36:45.0577450Z Args: 2025-07-17T07:36:45.0577752Z optim (Type): a ``torch.optim.Optimizer`` class to be registered 2025-07-17T07:36:45.0578175Z as a fused optimizer. 2025-07-17T07:36:45.0578518Z *args (Sequence[Any]): Arguments to forward to `optim`. 2025-07-17T07:36:45.0579015Z optim_params (Optional[Iterable[torch.Tensor]]): Set of parameters 2025-07-17T07:36:45.0579556Z to optimize, similar to `params` argument of traditional `torch.optim` 2025-07-17T07:36:45.0580107Z Optimizers. If this is omitted, all DDP model parameters will be 2025-07-17T07:36:45.0580522Z optimized. 2025-07-17T07:36:45.0580850Z **kwargs: (Dict[str, Any]): Keyword arguments to forward to `optim`. 2025-07-17T07:36:45.0581175Z 2025-07-17T07:36:45.0581267Z .. warning :: 2025-07-17T07:36:45.0581613Z _register_fused_optim should only be called once on a DDP instance, 2025-07-17T07:36:45.0582154Z and registering multiple fused optimizers for the same DDP model 2025-07-17T07:36:45.0582603Z is not currently supported. Please ping 2025-07-17T07:36:45.0583084Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-07-17T07:36:45.0583528Z for your use case. 2025-07-17T07:36:45.0583681Z 2025-07-17T07:36:45.0583766Z .. warning :: 2025-07-17T07:36:45.0584088Z _register_fused_optim and register_comm_hook currently do not 2025-07-17T07:36:45.0584609Z compose together, meaning that custom DDP communication hooks are 2025-07-17T07:36:45.0585098Z not supported with overlapped optimizers. Please ping 2025-07-17T07:36:45.0585609Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-07-17T07:36:45.0586048Z for your use case. 2025-07-17T07:36:45.0586200Z 2025-07-17T07:36:45.0586296Z .. warning :: 2025-07-17T07:36:45.0586639Z Gradient accumulation and DDP `no_sync` are currently not supported 2025-07-17T07:36:45.0587103Z with overlapped optimizer. Please ping 2025-07-17T07:36:45.0587570Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-07-17T07:36:45.0587997Z for your use case. 2025-07-17T07:36:45.0588163Z 2025-07-17T07:36:45.0588251Z Example:: 2025-07-17T07:36:45.0588368Z 2025-07-17T07:36:45.0588504Z >>> # xdoctest: +SKIP("No rendezvous handler") 2025-07-17T07:36:45.0589044Z >>> torch.distributed.init_process_group(backend='nccl', world_size=4, init_method='...') 2025-07-17T07:36:45.0589651Z >>> net = torch.nn.parallel.DistributedDataParallel(model, pg) 2025-07-17T07:36:45.0590049Z >>> lr = 1e-2 2025-07-17T07:36:45.0590292Z >>> betas = (0.9, 0.99) 2025-07-17T07:36:45.0590540Z >>> eps = 1e-6 2025-07-17T07:36:45.0590970Z >>> net._register_fused_optim(torch.optim.Adam, lr, betas=betas, eps=eps) 2025-07-17T07:36:45.0591428Z >>> # Example with subset of parameters 2025-07-17T07:36:45.0591774Z >>> params_to_opt = [list(net.parameters())[0]] 2025-07-17T07:36:45.0592171Z >>> net._register_fused_optim( 2025-07-17T07:36:45.0592667Z ... torch.optim.Adam, lr, optim_params=params_to_opt, betas=betas, eps=eps 2025-07-17T07:36:45.0593108Z ... ) 2025-07-17T07:36:45.0593224Z 2025-07-17T07:36:45.0593475Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.0593859Z 2025-07-17T07:36:45.0810426Z msg = Cannot scrape callname=convert_conv2d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=14. 2025-07-17T07:36:45.0811464Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.0812090Z Convert ``memory_format`` of ``nn.Conv2d.weight`` to ``memory_format``. 2025-07-17T07:36:45.0812425Z 2025-07-17T07:36:45.0812871Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-07-17T07:36:45.0813534Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-07-17T07:36:45.0814188Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-07-17T07:36:45.0814947Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-07-17T07:36:45.0815370Z 2025-07-17T07:36:45.0815473Z .. note:: 2025-07-17T07:36:45.0816034Z Calling ``model.to(memory_format=torch.channels_last)`` is more aggressive 2025-07-17T07:36:45.0816940Z than the utility function ``convert_conv2d_weight_memory_format``. Any 2025-07-17T07:36:45.0817493Z layer with 4d weight will be affected by ``model.to``, which does not 2025-07-17T07:36:45.0818034Z necessarily benefit from conversion to specified ``memory_format``. 2025-07-17T07:36:45.0818604Z One place we are confident in is that NHWC(channels_last) conversion for 2025-07-17T07:36:45.0819163Z convolution in cuDNN, as it is beneficial to run convolution in NHWC, 2025-07-17T07:36:45.0819701Z even in cases where we have to apply permutation to input tensors. 2025-07-17T07:36:45.0820022Z 2025-07-17T07:36:45.0820242Z Hence our strategy here is to convert only the weight of convolution to 2025-07-17T07:36:45.0820702Z channels_last. This ensures that; 2025-07-17T07:36:45.0821141Z 1. Fast convolution kernels will be used, the benefit of which could 2025-07-17T07:36:45.0821697Z outweigh overhead of permutation (if input is not in the same format). 2025-07-17T07:36:45.0822281Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-07-17T07:36:45.0822745Z from memory_format conversion. 2025-07-17T07:36:45.0822953Z 2025-07-17T07:36:45.0823187Z The optimal case is that, layers between convolution layers are channels 2025-07-17T07:36:45.0823754Z last compatible. Input tensor would be permuted to channels last when it 2025-07-17T07:36:45.0824334Z encounters the first convolution layer and stay in that memory format. 2025-07-17T07:36:45.0824917Z Hence following convolutions will not need to permute its input tensor. 2025-07-17T07:36:45.0825274Z 2025-07-17T07:36:45.0825512Z In case where a channels last incompatible layer is between convolution 2025-07-17T07:36:45.0826050Z layers, we need to permute the input tensor back to contiguous format 2025-07-17T07:36:45.0826601Z for that layer. The input tensor will go through the remaining layers in 2025-07-17T07:36:45.0827166Z contiguous format and be permuted to channels last when it encounters 2025-07-17T07:36:45.0827708Z another convolution layer. There's no point in propagating that 2025-07-17T07:36:45.0828249Z permutation to an earlier layer, as most layers are quite agnostic to 2025-07-17T07:36:45.0828689Z ``memory_format``. 2025-07-17T07:36:45.0828857Z 2025-07-17T07:36:45.0829100Z This claim might change when PyTorch supports fusion of permutation, as 2025-07-17T07:36:45.0829657Z there might have been a better spot to fuse the permutation other than 2025-07-17T07:36:45.0830246Z immediately before a convolution. 2025-07-17T07:36:45.0830467Z 2025-07-17T07:36:45.0830563Z Args: 2025-07-17T07:36:45.0830884Z module (nn.Module): ``nn.Conv2d`` & ``nn.ConvTranspose2d`` or container 2025-07-17T07:36:45.0831353Z ``nn.Module`` 2025-07-17T07:36:45.0831713Z memory_format: user specified ``memory_format``, 2025-07-17T07:36:45.0832153Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-07-17T07:36:45.0832439Z 2025-07-17T07:36:45.0832522Z Returns: 2025-07-17T07:36:45.0832789Z The original module with updated ``nn.Conv2d`` 2025-07-17T07:36:45.0833037Z 2025-07-17T07:36:45.0833131Z Example: 2025-07-17T07:36:45.0833437Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:45.0833842Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-07-17T07:36:45.0834211Z >>> input = torch.randint( 2025-07-17T07:36:45.0834560Z ... 1, 10, (2, 8, 4, 4), dtype=torch.float16, device="cuda" 2025-07-17T07:36:45.0834902Z ... ) 2025-07-17T07:36:45.0835136Z >>> model = nn.Sequential( 2025-07-17T07:36:45.0835454Z >>> nn.Conv2d(8, 4, 3)).cuda().half() 2025-07-17T07:36:45.0835773Z >>> # This is identical to: 2025-07-17T07:36:45.0836219Z >>> # nn.utils.convert_conv2d_weight_memory_format(model, torch.channels_last) 2025-07-17T07:36:45.0836753Z >>> model = nn.utils.convert_conv2d_weight_memory_format( 2025-07-17T07:36:45.0837131Z ... model, torch.channels_last 2025-07-17T07:36:45.0837439Z ... ) 2025-07-17T07:36:45.0837670Z >>> out = model(input) 2025-07-17T07:36:45.0837926Z 2025-07-17T07:36:45.0838295Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.0838678Z 2025-07-17T07:36:45.0839342Z msg = Cannot scrape callname=convert_conv3d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=93. 2025-07-17T07:36:45.0840363Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.0840954Z Convert ``memory_format`` of ``nn.Conv3d.weight`` to ``memory_format`` 2025-07-17T07:36:45.0841546Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-07-17T07:36:45.0842214Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-07-17T07:36:45.0842867Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-07-17T07:36:45.0843559Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-07-17T07:36:45.0843980Z 2025-07-17T07:36:45.0844071Z .. note:: 2025-07-17T07:36:45.0844444Z Calling ``model.to(memory_format=torch.channels_last_3d)`` is more aggressive 2025-07-17T07:36:45.0845034Z than the utility function ``convert_conv3d_weight_memory_format``. Any 2025-07-17T07:36:45.0845672Z layer with 4d weight will be affected by ``model.to``, which does not 2025-07-17T07:36:45.0846216Z necessarily benefit from conversion to specified ``memory_format``. 2025-07-17T07:36:45.0846795Z One place we are confident in is that NDHWC(channels_last_3d) conversion for 2025-07-17T07:36:45.0847373Z convolution in cuDNN, as it is beneficial to run convolution in NDHWC, 2025-07-17T07:36:45.0847900Z even in cases where we have to apply permutation to input tensors. 2025-07-17T07:36:45.0848229Z 2025-07-17T07:36:45.0848449Z Hence our strategy here is to convert only the weight of convolution to 2025-07-17T07:36:45.0848912Z channels_last_3d. This ensures that; 2025-07-17T07:36:45.0849358Z 1. Fast convolution kernels will be used, the benefit of which could 2025-07-17T07:36:45.0849908Z outweigh overhead of permutation (if input is not in the same format). 2025-07-17T07:36:45.0850488Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-07-17T07:36:45.0851020Z from memory_format conversion. 2025-07-17T07:36:45.0851229Z 2025-07-17T07:36:45.0851450Z The optimal case is that, layers between convolution layers are channels 2025-07-17T07:36:45.0852026Z last compatible. Input tensor would be permuted to channels last when it 2025-07-17T07:36:45.0852613Z encounters the first convolution layer and stay in that memory format. 2025-07-17T07:36:45.0853197Z Hence following convolutions will not need to permute its input tensor. 2025-07-17T07:36:45.0853551Z 2025-07-17T07:36:45.0853769Z In case where a channels last incompatible layer is between convolution 2025-07-17T07:36:45.0854372Z layers, we need to permute the input tensor back to contiguous format 2025-07-17T07:36:45.0854925Z for that layer. The input tensor will go through the remaining layers in 2025-07-17T07:36:45.0855489Z contiguous format and be permuted to channels last when it encounters 2025-07-17T07:36:45.0856034Z another convolution layer. There's no point in propagating that 2025-07-17T07:36:45.0856572Z permutation to an earlier layer, as most layers are quite agnostic to 2025-07-17T07:36:45.0857005Z ``memory_format``. 2025-07-17T07:36:45.0857172Z 2025-07-17T07:36:45.0857400Z This claim might change when PyTorch supports fusion of permutation, as 2025-07-17T07:36:45.0857974Z there might have been a better spot to fuse the permutation other than 2025-07-17T07:36:45.0858429Z immediately before a convolution. 2025-07-17T07:36:45.0858649Z 2025-07-17T07:36:45.0858743Z Args: 2025-07-17T07:36:45.0859067Z module (nn.Module): ``nn.Conv3d`` & ``nn.ConvTranspose3d`` or container 2025-07-17T07:36:45.0859499Z ``nn.Module`` 2025-07-17T07:36:45.0859859Z memory_format: user specified ``memory_format``, 2025-07-17T07:36:45.0860287Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-07-17T07:36:45.0860591Z 2025-07-17T07:36:45.0860717Z Returns: 2025-07-17T07:36:45.0860987Z The original module with updated ``nn.Conv3d`` 2025-07-17T07:36:45.0861234Z 2025-07-17T07:36:45.0861329Z Example: 2025-07-17T07:36:45.0861581Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:45.0861981Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-07-17T07:36:45.0862352Z >>> input = torch.randint( 2025-07-17T07:36:45.0862686Z ... 1, 10, (2, 8, 4, 4, 4), dtype=torch.float16, device="cuda" 2025-07-17T07:36:45.0863035Z ... ) 2025-07-17T07:36:45.0863268Z >>> model = nn.Sequential( 2025-07-17T07:36:45.0863568Z >>> nn.Conv3d(8, 4, 3)).cuda().half() 2025-07-17T07:36:45.0863895Z >>> # This is identical to: 2025-07-17T07:36:45.0864347Z >>> # nn.utils.convert_conv3d_weight_memory_format(model, torch.channels_last_3d) 2025-07-17T07:36:45.0864882Z >>> model = nn.utils.convert_conv3d_weight_memory_format( 2025-07-17T07:36:45.0865266Z ... model, torch.channels_last_3d 2025-07-17T07:36:45.0865577Z ... ) 2025-07-17T07:36:45.0865804Z >>> out = model(input) 2025-07-17T07:36:45.0866055Z 2025-07-17T07:36:45.0866421Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.0866786Z 2025-07-17T07:36:45.0919941Z msg = Cannot scrape callname=register_parametrization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrize.py line=424. 2025-07-17T07:36:45.0920952Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.0921473Z Register a parametrization to a tensor in a module. 2025-07-17T07:36:45.0921769Z 2025-07-17T07:36:45.0922042Z Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``, 2025-07-17T07:36:45.0922756Z the module will return the parametrized version ``parametrization(module.weight)``. 2025-07-17T07:36:45.0923567Z If the original tensor requires a gradient, the backward pass will differentiate 2025-07-17T07:36:45.0924231Z through :attr:`parametrization`, and the optimizer will update the tensor accordingly. 2025-07-17T07:36:45.0924650Z 2025-07-17T07:36:45.0924958Z The first time that a module registers a parametrization, this function will add an attribute 2025-07-17T07:36:45.0925707Z ``parametrizations`` to the module of type :class:`~ParametrizationList`. 2025-07-17T07:36:45.0926063Z 2025-07-17T07:36:45.0926328Z The list of parametrizations on the tensor ``weight`` will be accessible under 2025-07-17T07:36:45.0926819Z ``module.parametrizations.weight``. 2025-07-17T07:36:45.0927060Z 2025-07-17T07:36:45.0927279Z The original tensor will be accessible under 2025-07-17T07:36:45.0927679Z ``module.parametrizations.weight.original``. 2025-07-17T07:36:45.0927934Z 2025-07-17T07:36:45.0928211Z Parametrizations may be concatenated by registering several parametrizations 2025-07-17T07:36:45.0928690Z on the same attribute. 2025-07-17T07:36:45.0928873Z 2025-07-17T07:36:45.0929110Z The training mode of a registered parametrization is updated on registration 2025-07-17T07:36:45.0929608Z to match the training mode of the host module 2025-07-17T07:36:45.0929850Z 2025-07-17T07:36:45.0930154Z Parametrized parameters and buffers have an inbuilt caching system that can be activated 2025-07-17T07:36:45.0930706Z using the context manager :func:`cached`. 2025-07-17T07:36:45.0930948Z 2025-07-17T07:36:45.0931190Z A :attr:`parametrization` may optionally implement a method with signature 2025-07-17T07:36:45.0931546Z 2025-07-17T07:36:45.0931667Z .. code-block:: python 2025-07-17T07:36:45.0931841Z 2025-07-17T07:36:45.0932058Z def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]] 2025-07-17T07:36:45.0932402Z 2025-07-17T07:36:45.0932680Z This method is called on the unparametrized tensor when the first parametrization 2025-07-17T07:36:45.0933273Z is registered to compute the initial value of the original tensor. 2025-07-17T07:36:45.0933915Z If this method is not implemented, the original tensor will be just the unparametrized tensor. 2025-07-17T07:36:45.0933920Z 2025-07-17T07:36:45.0934229Z If all the parametrizations registered on a tensor implement `right_inverse` it is possible 2025-07-17T07:36:45.0934514Z to initialize a parametrized tensor by assigning to it, as shown in the example below. 2025-07-17T07:36:45.0934519Z 2025-07-17T07:36:45.0934803Z It is possible for the first parametrization to depend on several inputs. 2025-07-17T07:36:45.0935042Z This may be implemented returning a tuple of tensors from ``right_inverse`` 2025-07-17T07:36:45.0935294Z (see the example implementation of a ``RankOne`` parametrization below). 2025-07-17T07:36:45.0935299Z 2025-07-17T07:36:45.0935630Z In this case, the unconstrained tensors are also located under ``module.parametrizations.weight`` 2025-07-17T07:36:45.0935756Z with names ``original0``, ``original1``,... 2025-07-17T07:36:45.0935765Z 2025-07-17T07:36:45.0935865Z .. note:: 2025-07-17T07:36:45.0935869Z 2025-07-17T07:36:45.0936137Z If unsafe=False (default) both the forward and right_inverse methods will be called 2025-07-17T07:36:45.0936294Z once to perform a number of consistency checks. 2025-07-17T07:36:45.0936558Z If unsafe=True, then right_inverse will be called if the tensor is not parametrized, 2025-07-17T07:36:45.0936675Z and nothing will be called otherwise. 2025-07-17T07:36:45.0936680Z 2025-07-17T07:36:45.0936779Z .. note:: 2025-07-17T07:36:45.0936783Z 2025-07-17T07:36:45.0936988Z In most situations, ``right_inverse`` will be a function such that 2025-07-17T07:36:45.0937118Z ``forward(right_inverse(X)) == X`` (see 2025-07-17T07:36:45.0937404Z `right inverse `_). 2025-07-17T07:36:45.0937654Z Sometimes, when the parametrization is not surjective, it may be reasonable 2025-07-17T07:36:45.0937849Z to relax this. 2025-07-17T07:36:45.0937853Z 2025-07-17T07:36:45.0937940Z .. warning:: 2025-07-17T07:36:45.0937944Z 2025-07-17T07:36:45.0938229Z If a parametrization depends on several inputs, :func:`~register_parametrization` 2025-07-17T07:36:45.0938484Z will register a number of new parameters. If such parametrization is registered 2025-07-17T07:36:45.0938764Z after the optimizer is created, these new parameters will need to be added manually 2025-07-17T07:36:45.0938958Z to the optimizer. See :meth:`torch.Optimizer.add_param_group`. 2025-07-17T07:36:45.0938962Z 2025-07-17T07:36:45.0939044Z Args: 2025-07-17T07:36:45.0939389Z module (nn.Module): module on which to register the parametrization 2025-07-17T07:36:45.0939601Z tensor_name (str): name of the parameter or buffer on which to register 2025-07-17T07:36:45.0939705Z the parametrization 2025-07-17T07:36:45.0939918Z parametrization (nn.Module): the parametrization to register 2025-07-17T07:36:45.0940010Z Keyword args: 2025-07-17T07:36:45.0940237Z unsafe (bool): a boolean flag that denotes whether the parametrization 2025-07-17T07:36:45.0940425Z may change the dtype and shape of the tensor. Default: `False` 2025-07-17T07:36:45.0940687Z Warning: the parametrization is not checked for consistency upon registration. 2025-07-17T07:36:45.0940816Z Enable this flag at your own risk. 2025-07-17T07:36:45.0940820Z 2025-07-17T07:36:45.0940901Z Raises: 2025-07-17T07:36:45.0941184Z ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name` 2025-07-17T07:36:45.0941192Z 2025-07-17T07:36:45.0941289Z Examples: 2025-07-17T07:36:45.0941435Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-07-17T07:36:45.0941539Z >>> import torch 2025-07-17T07:36:45.0941640Z >>> import torch.nn as nn 2025-07-17T07:36:45.0941776Z >>> import torch.nn.utils.parametrize as P 2025-07-17T07:36:45.0941867Z >>> 2025-07-17T07:36:45.0941972Z >>> class Symmetric(nn.Module): 2025-07-17T07:36:45.0942072Z >>> def forward(self, X): 2025-07-17T07:36:45.0942255Z >>> return X.triu() + X.triu(1).T # Return a symmetric matrix 2025-07-17T07:36:45.0942335Z >>> 2025-07-17T07:36:45.0942443Z >>> def right_inverse(self, A): 2025-07-17T07:36:45.0942547Z >>> return A.triu() 2025-07-17T07:36:45.0942627Z >>> 2025-07-17T07:36:45.0942732Z >>> m = nn.Linear(5, 5) 2025-07-17T07:36:45.0942894Z >>> P.register_parametrization(m, "weight", Symmetric()) 2025-07-17T07:36:45.0943137Z >>> print(torch.allclose(m.weight, m.weight.T)) # m.weight is now symmetric 2025-07-17T07:36:45.0943229Z True 2025-07-17T07:36:45.0943325Z >>> A = torch.rand(5, 5) 2025-07-17T07:36:45.0943432Z >>> A = A + A.T # A is now symmetric 2025-07-17T07:36:45.0943639Z >>> m.weight = A # Initialize the weight to be the symmetric matrix A 2025-07-17T07:36:45.0943756Z >>> print(torch.allclose(m.weight, A)) 2025-07-17T07:36:45.0943838Z True 2025-07-17T07:36:45.0943843Z 2025-07-17T07:36:45.0943957Z >>> class RankOne(nn.Module): 2025-07-17T07:36:45.0944061Z >>> def forward(self, x, y): 2025-07-17T07:36:45.0944209Z >>> # Form a rank 1 matrix multiplying two vectors 2025-07-17T07:36:45.0944337Z >>> return x.unsqueeze(-1) @ y.unsqueeze(-2) 2025-07-17T07:36:45.0944418Z >>> 2025-07-17T07:36:45.0944536Z >>> def right_inverse(self, Z): 2025-07-17T07:36:45.0944652Z >>> # Project Z onto the rank 1 matrices 2025-07-17T07:36:45.0944800Z >>> U, S, Vh = torch.linalg.svd(Z, full_matrices=False) 2025-07-17T07:36:45.0944929Z >>> # Return rescaled singular vectors 2025-07-17T07:36:45.0945046Z >>> s0_sqrt = S[0].sqrt().unsqueeze(-1) 2025-07-17T07:36:45.0945244Z >>> return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt 2025-07-17T07:36:45.0945341Z >>> 2025-07-17T07:36:45.0945485Z >>> linear_rank_one = P.register_parametrization( 2025-07-17T07:36:45.0945615Z ... nn.Linear(4, 4), "weight", RankOne() 2025-07-17T07:36:45.0945696Z ... ) 2025-07-17T07:36:45.0945894Z >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item()) 2025-07-17T07:36:45.0945986Z 1 2025-07-17T07:36:45.0945991Z 2025-07-17T07:36:45.0946066Z 2025-07-17T07:36:45.0946317Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.0946321Z 2025-07-17T07:36:45.1024482Z msg = Cannot scrape callname=ln_structured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=979. 2025-07-17T07:36:45.1024752Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.1025073Z Prune tensor by removing channels with the lowest L\ ``n``-norm along the specified dimension. 2025-07-17T07:36:45.1025086Z 2025-07-17T07:36:45.1025314Z Prunes tensor corresponding to parameter called ``name`` in ``module`` 2025-07-17T07:36:45.1025539Z by removing the specified ``amount`` of (currently unpruned) channels 2025-07-17T07:36:45.1025712Z along the specified ``dim`` with the lowest L\ ``n``-norm. 2025-07-17T07:36:45.1025904Z Modifies module in place (and also return the modified module) 2025-07-17T07:36:45.1025998Z by: 2025-07-17T07:36:45.1026003Z 2025-07-17T07:36:45.1026206Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-07-17T07:36:45.1026424Z binary mask applied to the parameter ``name`` by the pruning method. 2025-07-17T07:36:45.1026642Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-07-17T07:36:45.1026844Z original (unpruned) parameter is stored in a new parameter named 2025-07-17T07:36:45.1026948Z ``name+'_orig'``. 2025-07-17T07:36:45.1026956Z 2025-07-17T07:36:45.1027038Z Args: 2025-07-17T07:36:45.1027212Z module (nn.Module): module containing the tensor to prune 2025-07-17T07:36:45.1027403Z name (str): parameter name within ``module`` on which pruning 2025-07-17T07:36:45.1027491Z will act. 2025-07-17T07:36:45.1027656Z amount (int or float): quantity of parameters to prune. 2025-07-17T07:36:45.1027842Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-07-17T07:36:45.1028037Z fraction of parameters to prune. If ``int``, it represents the 2025-07-17T07:36:45.1028175Z absolute number of parameters to prune. 2025-07-17T07:36:45.1028367Z n (int, float, inf, -inf, 'fro', 'nuc'): See documentation of valid 2025-07-17T07:36:45.1028544Z entries for argument ``p`` in :func:`torch.norm`. 2025-07-17T07:36:45.1028870Z dim (int): index of the dim along which we define channels to prune. 2025-07-17T07:36:45.1029136Z importance_scores (torch.Tensor): tensor of importance scores (of same 2025-07-17T07:36:45.1029439Z shape as module parameter) used to compute mask for pruning. 2025-07-17T07:36:45.1029745Z The values in this tensor indicate the importance of the corresponding 2025-07-17T07:36:45.1029961Z elements in the parameter being pruned. 2025-07-17T07:36:45.1030418Z If unspecified or None, the module parameter will be used in its place. 2025-07-17T07:36:45.1030427Z 2025-07-17T07:36:45.1030574Z Returns: 2025-07-17T07:36:45.1030800Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-07-17T07:36:45.1030805Z 2025-07-17T07:36:45.1030906Z Examples: 2025-07-17T07:36:45.1031022Z >>> from torch.nn.utils import prune 2025-07-17T07:36:45.1031137Z >>> m = prune.ln_structured( 2025-07-17T07:36:45.1031311Z ... nn.Conv2d(5, 3, 2), "weight", amount=0.3, dim=1, n=float("-inf") 2025-07-17T07:36:45.1031432Z ... ) 2025-07-17T07:36:45.1031617Z 2025-07-17T07:36:45.1031871Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.1031875Z 2025-07-17T07:36:45.1032434Z msg = Cannot scrape callname=global_unstructured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1026. 2025-07-17T07:36:45.1032692Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.1032696Z 2025-07-17T07:36:45.1033142Z Globally prunes tensors corresponding to all parameters in ``parameters`` by applying the specified ``pruning_method``. 2025-07-17T07:36:45.1033148Z 2025-07-17T07:36:45.1033310Z Modifies modules in place by: 2025-07-17T07:36:45.1033315Z 2025-07-17T07:36:45.1033519Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-07-17T07:36:45.1033802Z binary mask applied to the parameter ``name`` by the pruning method. 2025-07-17T07:36:45.1034112Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-07-17T07:36:45.1034498Z original (unpruned) parameter is stored in a new parameter named 2025-07-17T07:36:45.1034687Z ``name+'_orig'``. 2025-07-17T07:36:45.1034696Z 2025-07-17T07:36:45.1034851Z Args: 2025-07-17T07:36:45.1035125Z parameters (Iterable of (module, name) tuples): parameters of 2025-07-17T07:36:45.1035313Z the model to prune in a global fashion, i.e. by aggregating all 2025-07-17T07:36:45.1035517Z weights prior to deciding which ones to prune. module must be of 2025-07-17T07:36:45.1035674Z type :class:`nn.Module`, and name must be a string. 2025-07-17T07:36:45.1035894Z pruning_method (function): a valid pruning function from this module, 2025-07-17T07:36:45.1036065Z or a custom one implemented by the user that satisfies the 2025-07-17T07:36:45.1036301Z implementation guidelines and has ``PRUNING_TYPE='unstructured'``. 2025-07-17T07:36:45.1036524Z importance_scores (dict): a dictionary mapping (module, name) tuples to 2025-07-17T07:36:45.1036759Z the corresponding parameter's importance scores tensor. The tensor 2025-07-17T07:36:45.1036961Z should be the same shape as the parameter, and is used for computing 2025-07-17T07:36:45.1037056Z mask for pruning. 2025-07-17T07:36:45.1037270Z If unspecified or None, the parameter will be used in place of its 2025-07-17T07:36:45.1037366Z importance scores. 2025-07-17T07:36:45.1037486Z kwargs: other keyword arguments such as: 2025-07-17T07:36:45.1037690Z amount (int or float): quantity of parameters to prune across the 2025-07-17T07:36:45.1037790Z specified parameters. 2025-07-17T07:36:45.1037972Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-07-17T07:36:45.1038167Z fraction of parameters to prune. If ``int``, it represents the 2025-07-17T07:36:45.1038292Z absolute number of parameters to prune. 2025-07-17T07:36:45.1038296Z 2025-07-17T07:36:45.1038392Z Raises: 2025-07-17T07:36:45.1038544Z TypeError: if ``PRUNING_TYPE != 'unstructured'`` 2025-07-17T07:36:45.1038548Z 2025-07-17T07:36:45.1038627Z Note: 2025-07-17T07:36:45.1038848Z Since global structured pruning doesn't make much sense unless the 2025-07-17T07:36:45.1039042Z norm is normalized by the size of the parameter, we now limit the 2025-07-17T07:36:45.1039198Z scope of global pruning to unstructured methods. 2025-07-17T07:36:45.1039202Z 2025-07-17T07:36:45.1039285Z Examples: 2025-07-17T07:36:45.1039398Z >>> from torch.nn.utils import prune 2025-07-17T07:36:45.1039526Z >>> from collections import OrderedDict 2025-07-17T07:36:45.1039622Z >>> net = nn.Sequential( 2025-07-17T07:36:45.1039715Z ... OrderedDict( 2025-07-17T07:36:45.1039810Z ... [ 2025-07-17T07:36:45.1039924Z ... ("first", nn.Linear(10, 4)), 2025-07-17T07:36:45.1040034Z ... ("second", nn.Linear(4, 1)), 2025-07-17T07:36:45.1040127Z ... ] 2025-07-17T07:36:45.1040281Z ... ) 2025-07-17T07:36:45.1040360Z ... ) 2025-07-17T07:36:45.1040476Z >>> parameters_to_prune = ( 2025-07-17T07:36:45.1040573Z ... (net.first, "weight"), 2025-07-17T07:36:45.1040685Z ... (net.second, "weight"), 2025-07-17T07:36:45.1040768Z ... ) 2025-07-17T07:36:45.1040873Z >>> prune.global_unstructured( 2025-07-17T07:36:45.1040986Z ... parameters_to_prune, 2025-07-17T07:36:45.1041112Z ... pruning_method=prune.L1Unstructured, 2025-07-17T07:36:45.1041196Z ... amount=10, 2025-07-17T07:36:45.1041290Z ... ) 2025-07-17T07:36:45.1041504Z >>> print(sum(torch.nn.utils.parameters_to_vector(net.buffers()) == 0)) 2025-07-17T07:36:45.1041642Z tensor(10) 2025-07-17T07:36:45.1041647Z 2025-07-17T07:36:45.1041664Z 2025-07-17T07:36:45.1041915Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.1041920Z 2025-07-17T07:36:45.1042453Z msg = Cannot scrape callname=custom_from_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1149. 2025-07-17T07:36:45.1042820Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.1043214Z Prune tensor corresponding to parameter called ``name`` in ``module`` by applying the pre-computed mask in ``mask``. 2025-07-17T07:36:45.1043219Z 2025-07-17T07:36:45.1043444Z Modifies module in place (and also return the modified module) by: 2025-07-17T07:36:45.1043449Z 2025-07-17T07:36:45.1043655Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-07-17T07:36:45.1043870Z binary mask applied to the parameter ``name`` by the pruning method. 2025-07-17T07:36:45.1044095Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-07-17T07:36:45.1044298Z original (unpruned) parameter is stored in a new parameter named 2025-07-17T07:36:45.1044408Z ``name+'_orig'``. 2025-07-17T07:36:45.1044412Z 2025-07-17T07:36:45.1055898Z Args: 2025-07-17T07:36:45.1056183Z module (nn.Module): module containing the tensor to prune 2025-07-17T07:36:45.1056384Z name (str): parameter name within ``module`` on which pruning 2025-07-17T07:36:45.1056472Z will act. 2025-07-17T07:36:45.1056648Z mask (Tensor): binary mask to be applied to the parameter. 2025-07-17T07:36:45.1056654Z 2025-07-17T07:36:45.1056754Z Returns: 2025-07-17T07:36:45.1056974Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-07-17T07:36:45.1056980Z 2025-07-17T07:36:45.1057064Z Examples: 2025-07-17T07:36:45.1057197Z >>> from torch.nn.utils import prune 2025-07-17T07:36:45.1057311Z >>> m = prune.custom_from_mask( 2025-07-17T07:36:45.1057495Z ... nn.Linear(5, 3), name="bias", mask=torch.tensor([0, 1, 0]) 2025-07-17T07:36:45.1057578Z ... ) 2025-07-17T07:36:45.1057676Z >>> print(m.bias_mask) 2025-07-17T07:36:45.1057815Z tensor([0., 1., 0.]) 2025-07-17T07:36:45.1057824Z 2025-07-17T07:36:45.1057902Z 2025-07-17T07:36:45.1058156Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.1058161Z 2025-07-17T07:36:45.1093951Z msg = Cannot scrape callname=pad_packed_sequence in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py line=342. 2025-07-17T07:36:45.1094314Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.1094470Z Pad a packed batch of variable length sequences. 2025-07-17T07:36:45.1094475Z 2025-07-17T07:36:45.1094647Z It is an inverse operation to :func:`pack_padded_sequence`. 2025-07-17T07:36:45.1094669Z 2025-07-17T07:36:45.1094969Z The returned Tensor's data will be of size ``T x B x *`` (if :attr:`batch_first` is ``False``) 2025-07-17T07:36:45.1095205Z or ``B x T x *`` (if :attr:`batch_first` is ``True``) , where ``T`` is the length of the longest 2025-07-17T07:36:45.1095318Z sequence and ``B`` is the batch size. 2025-07-17T07:36:45.1095474Z 2025-07-17T07:36:45.1095574Z Example: 2025-07-17T07:36:45.1095814Z >>> from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence 2025-07-17T07:36:45.1095973Z >>> seq = torch.tensor([[1, 2, 0], [3, 0, 0], [4, 5, 6]]) 2025-07-17T07:36:45.1096066Z >>> lens = [2, 1, 3] 2025-07-17T07:36:45.1096179Z >>> packed = pack_padded_sequence( 2025-07-17T07:36:45.1096343Z ... seq, lens, batch_first=True, enforce_sorted=False 2025-07-17T07:36:45.1096424Z ... ) 2025-07-17T07:36:45.1096510Z >>> packed 2025-07-17T07:36:45.1096762Z PackedSequence(data=tensor([4, 1, 3, 5, 2, 6]), batch_sizes=tensor([3, 2, 1]), 2025-07-17T07:36:45.1097052Z sorted_indices=tensor([2, 0, 1]), unsorted_indices=tensor([1, 2, 0])) 2025-07-17T07:36:45.1097300Z >>> seq_unpacked, lens_unpacked = pad_packed_sequence(packed, batch_first=True) 2025-07-17T07:36:45.1097405Z >>> seq_unpacked 2025-07-17T07:36:45.1097499Z tensor([[1, 2, 0], 2025-07-17T07:36:45.1097599Z [3, 0, 0], 2025-07-17T07:36:45.1097685Z [4, 5, 6]]) 2025-07-17T07:36:45.1097772Z >>> lens_unpacked 2025-07-17T07:36:45.1097875Z tensor([2, 1, 3]) 2025-07-17T07:36:45.1097879Z 2025-07-17T07:36:45.1097972Z .. note:: 2025-07-17T07:36:45.1098115Z :attr:`total_length` is useful to implement the 2025-07-17T07:36:45.1098395Z ``pack sequence -> recurrent network -> unpack sequence`` pattern in a 2025-07-17T07:36:45.1098609Z :class:`~torch.nn.Module` wrapped in :class:`~torch.nn.DataParallel`. 2025-07-17T07:36:45.1098859Z See :ref:`this FAQ section ` for 2025-07-17T07:36:45.1098942Z details. 2025-07-17T07:36:45.1098947Z 2025-07-17T07:36:45.1099025Z Args: 2025-07-17T07:36:45.1099162Z sequence (PackedSequence): batch to pad 2025-07-17T07:36:45.1099392Z batch_first (bool, optional): if ``True``, the output will be in ``B x T x *`` 2025-07-17T07:36:45.1099503Z format, ``T x B x *`` otherwise. 2025-07-17T07:36:45.1099702Z padding_value (float, optional): values for padded elements. 2025-07-17T07:36:45.1099929Z total_length (int, optional): if not ``None``, the output will be padded to 2025-07-17T07:36:45.1100173Z have length :attr:`total_length`. This method will throw :class:`ValueError` 2025-07-17T07:36:45.1100355Z if :attr:`total_length` is less than the max sequence length in 2025-07-17T07:36:45.1100453Z :attr:`sequence`. 2025-07-17T07:36:45.1100457Z 2025-07-17T07:36:45.1100548Z Returns: 2025-07-17T07:36:45.1100732Z Tuple of Tensor containing the padded sequence, and a Tensor 2025-07-17T07:36:45.1100919Z containing the list of lengths of each sequence in the batch. 2025-07-17T07:36:45.1101144Z Batch elements will be re-ordered as they were ordered originally when 2025-07-17T07:36:45.1101354Z the batch was passed to ``pack_padded_sequence`` or ``pack_sequence``. 2025-07-17T07:36:45.1101448Z 2025-07-17T07:36:45.1101694Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.1101699Z 2025-07-17T07:36:45.1713080Z msg = Cannot scrape callname=SequentialLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=808. 2025-07-17T07:36:45.1713347Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.1713688Z Contains a list of schedulers expected to be called sequentially during the optimization process. 2025-07-17T07:36:45.1713695Z 2025-07-17T07:36:45.1714086Z Specifically, the schedulers will be called according to the milestone points, which should provide exact 2025-07-17T07:36:45.1714319Z intervals by which each scheduler should be called at a given epoch. 2025-07-17T07:36:45.1714324Z 2025-07-17T07:36:45.1714407Z Args: 2025-07-17T07:36:45.1714538Z optimizer (Optimizer): Wrapped optimizer. 2025-07-17T07:36:45.1714930Z schedulers (list): List of chained schedulers. 2025-07-17T07:36:45.1715146Z milestones (list): List of integers that reflects milestone points. 2025-07-17T07:36:45.1715330Z last_epoch (int): The index of last epoch. Default: -1. 2025-07-17T07:36:45.1715335Z 2025-07-17T07:36:45.1715420Z Example: 2025-07-17T07:36:45.1715518Z >>> # xdoctest: +SKIP 2025-07-17T07:36:45.1715682Z >>> # Assuming optimizer uses lr = 0.05 for all groups 2025-07-17T07:36:45.1715785Z >>> # lr = 0.005 if epoch == 0 2025-07-17T07:36:45.1715883Z >>> # lr = 0.005 if epoch == 1 2025-07-17T07:36:45.1716085Z >>> # lr = 0.005 if epoch == 2 2025-07-17T07:36:45.1716172Z >>> # ... 2025-07-17T07:36:45.1716277Z >>> # lr = 0.05 if epoch == 20 2025-07-17T07:36:45.1716390Z >>> # lr = 0.045 if epoch == 21 2025-07-17T07:36:45.1716490Z >>> # lr = 0.0405 if epoch == 22 2025-07-17T07:36:45.1716706Z >>> scheduler1 = ConstantLR(optimizer, factor=0.1, total_iters=20) 2025-07-17T07:36:45.1716857Z >>> scheduler2 = ExponentialLR(optimizer, gamma=0.9) 2025-07-17T07:36:45.1716965Z >>> scheduler = SequentialLR( 2025-07-17T07:36:45.1717069Z ... optimizer, 2025-07-17T07:36:45.1717199Z ... schedulers=[scheduler1, scheduler2], 2025-07-17T07:36:45.1717296Z ... milestones=[20], 2025-07-17T07:36:45.1717392Z ... ) 2025-07-17T07:36:45.1717495Z >>> for epoch in range(100): 2025-07-17T07:36:45.1717586Z >>> train(...) 2025-07-17T07:36:45.1717693Z >>> validate(...) 2025-07-17T07:36:45.1717796Z >>> scheduler.step() 2025-07-17T07:36:45.1717801Z 2025-07-17T07:36:45.1718000Z .. image:: ../scripts/lr_scheduler_images/SequentialLR.png 2025-07-17T07:36:45.1718079Z 2025-07-17T07:36:45.1718329Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.1718337Z 2025-07-17T07:36:45.1748539Z msg = Cannot scrape callname=ReduceLROnPlateau in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1233. 2025-07-17T07:36:45.1748826Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:45.1749022Z Reduce learning rate when a metric has stopped improving. 2025-07-17T07:36:45.1749028Z 2025-07-17T07:36:45.1749230Z Models often benefit from reducing the learning rate by a factor 2025-07-17T07:36:45.1749413Z of 2-10 once learning stagnates. This scheduler reads a metrics 2025-07-17T07:36:45.1749620Z quantity and if no improvement is seen for a 'patience' number 2025-07-17T07:36:45.1749753Z of epochs, the learning rate is reduced. 2025-07-17T07:36:45.1749758Z 2025-07-17T07:36:45.1749853Z Args: 2025-07-17T07:36:45.1749983Z optimizer (Optimizer): Wrapped optimizer. 2025-07-17T07:36:45.1750134Z mode (str): One of `min`, `max`. In `min` mode, lr will 2025-07-17T07:36:45.1750304Z be reduced when the quantity monitored has stopped 2025-07-17T07:36:45.1750465Z decreasing; in `max` mode it will be reduced when the 2025-07-17T07:36:45.1750654Z quantity monitored has stopped increasing. Default: 'min'. 2025-07-17T07:36:45.1750834Z factor (float): Factor by which the learning rate will be 2025-07-17T07:36:45.1750969Z reduced. new_lr = lr * factor. Default: 0.1. 2025-07-17T07:36:45.1751248Z patience (int): The number of allowed epochs with no improvement after 2025-07-17T07:36:45.1751376Z which the learning rate will be reduced. 2025-07-17T07:36:45.1751603Z For example, consider the case of having no patience (`patience = 0`). 2025-07-17T07:36:45.1751981Z In the first epoch, a baseline is established and is always considered good as there's no previous baseline. 2025-07-17T07:36:45.1752184Z In the second epoch, if the performance is worse than the baseline, 2025-07-17T07:36:45.1752443Z we have what is considered an intolerable epoch. 2025-07-17T07:36:45.1752716Z Since the count of intolerable epochs (1) is greater than the patience level (0), 2025-07-17T07:36:45.1752882Z the learning rate is reduced at the end of this epoch. 2025-07-17T07:36:45.1753217Z From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch 2025-07-17T07:36:45.1753531Z if the performance is worse than the baseline. If the performance improves or remains the same, 2025-07-17T07:36:45.1753652Z the learning rate is not adjusted. 2025-07-17T07:36:45.1753761Z Default: 10. 2025-07-17T07:36:45.1754033Z threshold (float): Threshold for measuring the new optimum, 2025-07-17T07:36:45.1754210Z to only focus on significant changes. Default: 1e-4. 2025-07-17T07:36:45.1754382Z threshold_mode (str): One of `rel`, `abs`. In `rel` mode, 2025-07-17T07:36:45.1754538Z dynamic_threshold = best * ( 1 + threshold ) in 'max' 2025-07-17T07:36:45.1754697Z mode or best * ( 1 - threshold ) in `min` mode. 2025-07-17T07:36:45.1754854Z In `abs` mode, dynamic_threshold = best + threshold in 2025-07-17T07:36:45.1755027Z `max` mode or best - threshold in `min` mode. Default: 'rel'. 2025-07-17T07:36:45.1755209Z cooldown (int): Number of epochs to wait before resuming 2025-07-17T07:36:45.1755381Z normal operation after lr has been reduced. Default: 0. 2025-07-17T07:36:45.1755553Z min_lr (float or list): A scalar or a list of scalars. A 2025-07-17T07:36:45.1755708Z lower bound on the learning rate of all param groups 2025-07-17T07:36:45.1755840Z or each group respectively. Default: 0. 2025-07-17T07:36:45.1756033Z eps (float): Minimal decay applied to lr. If the difference 2025-07-17T07:36:45.1756208Z between new and old lr is smaller than eps, the update is 2025-07-17T07:36:45.1756316Z ignored. Default: 1e-8. 2025-07-17T07:36:45.1756321Z 2025-07-17T07:36:45.1756417Z Example: 2025-07-17T07:36:45.1756512Z >>> # xdoctest: +SKIP 2025-07-17T07:36:45.1756736Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-07-17T07:36:45.1756915Z >>> scheduler = ReduceLROnPlateau(optimizer, "min") 2025-07-17T07:36:45.1757072Z >>> for epoch in range(10): 2025-07-17T07:36:45.1757231Z >>> train(...) 2025-07-17T07:36:45.1757399Z >>> val_loss = validate(...) 2025-07-17T07:36:45.1757630Z >>> # Note that step should be called after validate() 2025-07-17T07:36:45.1757753Z >>> scheduler.step(val_loss) 2025-07-17T07:36:45.1757762Z 2025-07-17T07:36:45.1757965Z .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png 2025-07-17T07:36:45.1758044Z 2025-07-17T07:36:45.1758702Z Original Error: IndentationError('unexpected indent', ('', 8, 4, ' scheduler.step(val_loss)\n', 8, -1)) 2025-07-17T07:36:45.1758715Z 2025-07-17T07:36:45.1758902Z scheduler.step(val_loss) 2025-07-17T07:36:45.1759077Z ^ 2025-07-17T07:36:45.1759840Z msg = Cannot scrape callname=CyclicLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1430. 2025-07-17T07:36:45.1760115Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.1760434Z Sets the learning rate of each parameter group according to cyclical learning rate policy (CLR). 2025-07-17T07:36:45.1760439Z 2025-07-17T07:36:45.1760719Z The policy cycles the learning rate between two boundaries with a constant frequency, 2025-07-17T07:36:45.1760992Z as detailed in the paper `Cyclical Learning Rates for Training Neural Networks`_. 2025-07-17T07:36:45.1761221Z The distance between the two boundaries can be scaled on a per-iteration 2025-07-17T07:36:45.1761331Z or per-cycle basis. 2025-07-17T07:36:45.1761336Z 2025-07-17T07:36:45.1761657Z Cyclical learning rate policy changes the learning rate after every batch. 2025-07-17T07:36:45.1761853Z `step` should be called after a batch has been used for training. 2025-07-17T07:36:45.1761858Z 2025-07-17T07:36:45.1762078Z This class has three built-in policies, as put forth in the paper: 2025-07-17T07:36:45.1762082Z 2025-07-17T07:36:45.1762286Z * "triangular": A basic triangular cycle without amplitude scaling. 2025-07-17T07:36:45.1762596Z * "triangular2": A basic triangular cycle that scales initial amplitude by half each cycle. 2025-07-17T07:36:45.1762917Z * "exp_range": A cycle that scales initial amplitude by :math:`\text{gamma}^{\text{cycle iterations}}` 2025-07-17T07:36:45.1763107Z at each cycle iteration. 2025-07-17T07:36:45.1763112Z 2025-07-17T07:36:45.1763363Z This implementation was adapted from the github repo: `bckenstler/CLR`_ 2025-07-17T07:36:45.1763367Z 2025-07-17T07:36:45.1763450Z Args: 2025-07-17T07:36:45.1763597Z optimizer (Optimizer): Wrapped optimizer. 2025-07-17T07:36:45.1763772Z base_lr (float or list): Initial learning rate which is the 2025-07-17T07:36:45.1763937Z lower boundary in the cycle for each parameter group. 2025-07-17T07:36:45.1764147Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-07-17T07:36:45.1764276Z for each parameter group. Functionally, 2025-07-17T07:36:45.1764429Z it defines the cycle amplitude (max_lr - base_lr). 2025-07-17T07:36:45.1764641Z The lr at any cycle is the sum of base_lr 2025-07-17T07:36:45.1764824Z and some scaling of the amplitude; therefore 2025-07-17T07:36:45.1764986Z max_lr may not actually be reached depending on 2025-07-17T07:36:45.1765082Z scaling function. 2025-07-17T07:36:45.1765249Z step_size_up (int): Number of training iterations in the 2025-07-17T07:36:45.1765469Z increasing half of a cycle. Default: 2000 2025-07-17T07:36:45.1765728Z step_size_down (int): Number of training iterations in the 2025-07-17T07:36:45.1766002Z decreasing half of a cycle. If step_size_down is None, 2025-07-17T07:36:45.1766263Z it is set to step_size_up. Default: None 2025-07-17T07:36:45.1766575Z mode (str): One of {triangular, triangular2, exp_range}. 2025-07-17T07:36:45.1766829Z Values correspond to policies detailed above. 2025-07-17T07:36:45.1766993Z If scale_fn is not None, this argument is ignored. 2025-07-17T07:36:45.1767095Z Default: 'triangular' 2025-07-17T07:36:45.1767274Z gamma (float): Constant in 'exp_range' scaling function: 2025-07-17T07:36:45.1767382Z gamma**(cycle iterations) 2025-07-17T07:36:45.1767474Z Default: 1.0 2025-07-17T07:36:45.1767676Z scale_fn (function): Custom scaling policy defined by a single 2025-07-17T07:36:45.1767789Z argument lambda function, where 2025-07-17T07:36:45.1767901Z 0 <= scale_fn(x) <= 1 for all x >= 0. 2025-07-17T07:36:45.1768034Z If specified, then 'mode' is ignored. 2025-07-17T07:36:45.1768124Z Default: None 2025-07-17T07:36:45.1768258Z scale_mode (str): {'cycle', 'iterations'}. 2025-07-17T07:36:45.1768385Z Defines whether scale_fn is evaluated on 2025-07-17T07:36:45.1768513Z cycle number or cycle iterations (training 2025-07-17T07:36:45.1768639Z iterations since start of cycle). 2025-07-17T07:36:45.1768737Z Default: 'cycle' 2025-07-17T07:36:45.1768934Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-07-17T07:36:45.1769133Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-07-17T07:36:45.1769229Z Default: True 2025-07-17T07:36:45.1769443Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-07-17T07:36:45.1769657Z for each parameter group. Note that momentum is cycled inversely 2025-07-17T07:36:45.1769900Z to learning rate; at the peak of a cycle, momentum is 2025-07-17T07:36:45.1770225Z 'base_momentum' and learning rate is 'max_lr'. 2025-07-17T07:36:45.1770318Z Default: 0.8 2025-07-17T07:36:45.1770530Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-07-17T07:36:45.1770674Z for each parameter group. Functionally, 2025-07-17T07:36:45.1770870Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-07-17T07:36:45.1771050Z The momentum at any cycle is the difference of max_momentum 2025-07-17T07:36:45.1771199Z and some scaling of the amplitude; therefore 2025-07-17T07:36:45.1771484Z base_momentum may not actually be reached depending on 2025-07-17T07:36:45.1771673Z scaling function. Note that momentum is cycled inversely 2025-07-17T07:36:45.1771932Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-07-17T07:36:45.1772047Z and learning rate is 'base_lr' 2025-07-17T07:36:45.1772151Z Default: 0.9 2025-07-17T07:36:45.1772372Z last_epoch (int): The index of the last batch. This parameter is used when 2025-07-17T07:36:45.1772586Z resuming a training job. Since `step()` should be invoked after each 2025-07-17T07:36:45.1772811Z batch instead of after each epoch, this number represents the total 2025-07-17T07:36:45.1773074Z number of *batches* computed, not the total number of epochs computed. 2025-07-17T07:36:45.1773278Z When last_epoch=-1, the schedule is started from the beginning. 2025-07-17T07:36:45.1773392Z Default: -1 2025-07-17T07:36:45.1773396Z 2025-07-17T07:36:45.1773485Z Example: 2025-07-17T07:36:45.1773595Z >>> # xdoctest: +SKIP 2025-07-17T07:36:45.1773819Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-07-17T07:36:45.1773966Z >>> scheduler = torch.optim.lr_scheduler.CyclicLR( 2025-07-17T07:36:45.1774074Z ... optimizer, 2025-07-17T07:36:45.1774168Z ... base_lr=0.01, 2025-07-17T07:36:45.1774255Z ... max_lr=0.1, 2025-07-17T07:36:45.1774365Z ... step_size_up=10, 2025-07-17T07:36:45.1774446Z ... ) 2025-07-17T07:36:45.1774605Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-07-17T07:36:45.1774729Z >>> for epoch in range(10): 2025-07-17T07:36:45.1774834Z >>> for batch in data_loader: 2025-07-17T07:36:45.1774943Z >>> train_batch(...) 2025-07-17T07:36:45.1775041Z >>> scheduler.step() 2025-07-17T07:36:45.1775045Z 2025-07-17T07:36:45.1775207Z .. image:: ../scripts/lr_scheduler_images/CyclicLR.png 2025-07-17T07:36:45.1775211Z 2025-07-17T07:36:45.1775534Z .. _Cyclical Learning Rates for Training Neural Networks: https://arxiv.org/abs/1506.01186 2025-07-17T07:36:45.1775695Z .. _bckenstler/CLR: https://github.com/bckenstler/CLR 2025-07-17T07:36:45.1775789Z 2025-07-17T07:36:45.1776039Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.1776043Z 2025-07-17T07:36:45.1776703Z msg = Cannot scrape callname=CosineAnnealingWarmRestarts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1713. 2025-07-17T07:36:45.1776961Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.1777209Z Set the learning rate of each parameter group using a cosine annealing schedule. 2025-07-17T07:36:45.1777214Z 2025-07-17T07:36:45.1777403Z The :math:`\eta_{max}` is set to the initial lr, :math:`T_{cur}` 2025-07-17T07:36:45.1777641Z is the number of epochs since the last restart and :math:`T_{i}` is the number 2025-07-17T07:36:45.1777768Z of epochs between two warm restarts in SGDR: 2025-07-17T07:36:45.1777785Z 2025-07-17T07:36:45.1777870Z .. math:: 2025-07-17T07:36:45.1778046Z \eta_t = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 + 2025-07-17T07:36:45.1778281Z \cos\left(\frac{T_{cur}}{T_{i}}\pi\right)\right) 2025-07-17T07:36:45.1778286Z 2025-07-17T07:36:45.1778448Z When :math:`T_{cur}=T_{i}`, set :math:`\eta_t = \eta_{min}`. 2025-07-17T07:36:45.1778632Z When :math:`T_{cur}=0` after restart, set :math:`\eta_t=\eta_{max}`. 2025-07-17T07:36:45.1778636Z 2025-07-17T07:36:45.1778754Z It has been proposed in 2025-07-17T07:36:45.1778921Z `SGDR: Stochastic Gradient Descent with Warm Restarts`_. 2025-07-17T07:36:45.1778925Z 2025-07-17T07:36:45.1779022Z Args: 2025-07-17T07:36:45.1779153Z optimizer (Optimizer): Wrapped optimizer. 2025-07-17T07:36:45.1779363Z T_0 (int): Number of iterations until the first restart. 2025-07-17T07:36:45.1779656Z T_mult (int, optional): A factor by which :math:`T_{i}` increases after a restart. Default: 1. 2025-07-17T07:36:45.1779840Z eta_min (float, optional): Minimum learning rate. Default: 0. 2025-07-17T07:36:45.1780051Z last_epoch (int, optional): The index of the last epoch. Default: -1. 2025-07-17T07:36:45.1780072Z 2025-07-17T07:36:45.1780236Z .. _SGDR\: Stochastic Gradient Descent with Warm Restarts: 2025-07-17T07:36:45.1780351Z https://arxiv.org/abs/1608.03983 2025-07-17T07:36:45.1780355Z 2025-07-17T07:36:45.1780453Z Example: 2025-07-17T07:36:45.1780549Z >>> # xdoctest: +SKIP 2025-07-17T07:36:45.1780728Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.05) 2025-07-17T07:36:45.1780982Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts( 2025-07-17T07:36:45.1781080Z ... optimizer, T_0=20 2025-07-17T07:36:45.1781163Z ... ) 2025-07-17T07:36:45.1781329Z >>> for epoch in range(100): 2025-07-17T07:36:45.1781419Z >>> train(...) 2025-07-17T07:36:45.1781511Z >>> validate(...) 2025-07-17T07:36:45.1781621Z >>> scheduler.step() 2025-07-17T07:36:45.1781625Z 2025-07-17T07:36:45.1781859Z .. image:: ../scripts/lr_scheduler_images/CosineAnnealingWarmRestarts.png 2025-07-17T07:36:45.1781951Z 2025-07-17T07:36:45.1782200Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.1782204Z 2025-07-17T07:36:45.1788546Z msg = Cannot scrape callname=OneCycleLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1863. 2025-07-17T07:36:45.1789087Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.1789449Z Sets the learning rate of each parameter group according to the 1cycle learning rate policy. 2025-07-17T07:36:45.1789455Z 2025-07-17T07:36:45.1789769Z The 1cycle policy anneals the learning rate from an initial learning rate to some maximum 2025-07-17T07:36:45.1790054Z learning rate and then from that maximum learning rate to some minimum learning rate much 2025-07-17T07:36:45.1790167Z lower than the initial learning rate. 2025-07-17T07:36:45.1790399Z This policy was initially described in the paper `Super-Convergence: 2025-07-17T07:36:45.1790613Z Very Fast Training of Neural Networks Using Large Learning Rates`_. 2025-07-17T07:36:45.1790617Z 2025-07-17T07:36:45.1790873Z The 1cycle learning rate policy changes the learning rate after every batch. 2025-07-17T07:36:45.1791064Z `step` should be called after a batch has been used for training. 2025-07-17T07:36:45.1791069Z 2025-07-17T07:36:45.1791175Z This scheduler is not chainable. 2025-07-17T07:36:45.1791179Z 2025-07-17T07:36:45.1791425Z Note also that the total number of steps in the cycle can be determined in one 2025-07-17T07:36:45.1791605Z of two ways (listed in order of precedence): 2025-07-17T07:36:45.1791614Z 2025-07-17T07:36:45.1791771Z #. A value for total_steps is explicitly provided. 2025-07-17T07:36:45.1791948Z #. A number of epochs (epochs) and a number of steps per epoch 2025-07-17T07:36:45.1792059Z (steps_per_epoch) are provided. 2025-07-17T07:36:45.1792227Z In this case, the number of total steps is inferred by 2025-07-17T07:36:45.1792433Z total_steps = epochs * steps_per_epoch 2025-07-17T07:36:45.1792438Z 2025-07-17T07:36:45.1792712Z You must either provide a value for total_steps or provide a value for both 2025-07-17T07:36:45.1792816Z epochs and steps_per_epoch. 2025-07-17T07:36:45.1792821Z 2025-07-17T07:36:45.1793135Z The default behaviour of this scheduler follows the fastai implementation of 1cycle, which 2025-07-17T07:36:45.1793426Z claims that "unpublished work has shown even better results by using only two phases". To 2025-07-17T07:36:45.1793665Z mimic the behaviour of the original paper instead, set ``three_phase=True``. 2025-07-17T07:36:45.1793742Z 2025-07-17T07:36:45.1793840Z Args: 2025-07-17T07:36:45.1793969Z optimizer (Optimizer): Wrapped optimizer. 2025-07-17T07:36:45.1794165Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-07-17T07:36:45.1794284Z for each parameter group. 2025-07-17T07:36:45.1794576Z total_steps (int): The total number of steps in the cycle. Note that 2025-07-17T07:36:45.1794796Z if a value is not provided here, then it must be inferred by providing 2025-07-17T07:36:45.1794922Z a value for epochs and steps_per_epoch. 2025-07-17T07:36:45.1795015Z Default: None 2025-07-17T07:36:45.1795222Z epochs (int): The number of epochs to train for. This is used along 2025-07-17T07:36:45.1795461Z with steps_per_epoch in order to infer the total number of steps in the cycle 2025-07-17T07:36:45.1795594Z if a value for total_steps is not provided. 2025-07-17T07:36:45.1795697Z Default: None 2025-07-17T07:36:45.1795924Z steps_per_epoch (int): The number of steps per epoch to train for. This is 2025-07-17T07:36:45.1796164Z used along with epochs in order to infer the total number of steps in the 2025-07-17T07:36:45.1796313Z cycle if a value for total_steps is not provided. 2025-07-17T07:36:45.1796407Z Default: None 2025-07-17T07:36:45.1796649Z pct_start (float): The percentage of the cycle (in number of steps) spent 2025-07-17T07:36:45.1796759Z increasing the learning rate. 2025-07-17T07:36:45.1796850Z Default: 0.3 2025-07-17T07:36:45.1796986Z anneal_strategy (str): {'cos', 'linear'} 2025-07-17T07:36:45.1797229Z Specifies the annealing strategy: "cos" for cosine annealing, "linear" for 2025-07-17T07:36:45.1797336Z linear annealing. 2025-07-17T07:36:45.1797426Z Default: 'cos' 2025-07-17T07:36:45.1797619Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-07-17T07:36:45.1797815Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-07-17T07:36:45.1797906Z Default: True 2025-07-17T07:36:45.1798122Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-07-17T07:36:45.1798333Z for each parameter group. Note that momentum is cycled inversely 2025-07-17T07:36:45.1798497Z to learning rate; at the peak of a cycle, momentum is 2025-07-17T07:36:45.1798633Z 'base_momentum' and learning rate is 'max_lr'. 2025-07-17T07:36:45.1798734Z Default: 0.85 2025-07-17T07:36:45.1798941Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-07-17T07:36:45.1799077Z for each parameter group. Functionally, 2025-07-17T07:36:45.1799265Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-07-17T07:36:45.1799384Z Note that momentum is cycled inversely 2025-07-17T07:36:45.1799609Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-07-17T07:36:45.1799720Z and learning rate is 'base_lr' 2025-07-17T07:36:45.1799811Z Default: 0.95 2025-07-17T07:36:45.1800005Z div_factor (float): Determines the initial learning rate via 2025-07-17T07:36:45.1800167Z initial_lr = max_lr/div_factor 2025-07-17T07:36:45.1800267Z Default: 25 2025-07-17T07:36:45.1800466Z final_div_factor (float): Determines the minimum learning rate via 2025-07-17T07:36:45.1800584Z min_lr = initial_lr/final_div_factor 2025-07-17T07:36:45.1800689Z Default: 1e4 2025-07-17T07:36:45.1800929Z three_phase (bool): If ``True``, use a third phase of the schedule to annihilate the 2025-07-17T07:36:45.1801179Z learning rate according to 'final_div_factor' instead of modifying the second 2025-07-17T07:36:45.1801427Z phase (the first two phases will be symmetrical about the step indicated by 2025-07-17T07:36:45.1801572Z 'pct_start'). 2025-07-17T07:36:45.1801803Z last_epoch (int): The index of the last batch. This parameter is used when 2025-07-17T07:36:45.1802015Z resuming a training job. Since `step()` should be invoked after each 2025-07-17T07:36:45.1802224Z batch instead of after each epoch, this number represents the total 2025-07-17T07:36:45.1802459Z number of *batches* computed, not the total number of epochs computed. 2025-07-17T07:36:45.1802645Z When last_epoch=-1, the schedule is started from the beginning. 2025-07-17T07:36:45.1802733Z Default: -1 2025-07-17T07:36:45.1802738Z 2025-07-17T07:36:45.1802872Z Example: 2025-07-17T07:36:45.1802968Z >>> # xdoctest: +SKIP 2025-07-17T07:36:45.1803127Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-07-17T07:36:45.1803356Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9) 2025-07-17T07:36:45.1803514Z >>> scheduler = torch.optim.lr_scheduler.OneCycleLR( 2025-07-17T07:36:45.1803734Z ... optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10 2025-07-17T07:36:45.1803816Z ... ) 2025-07-17T07:36:45.1803916Z >>> for epoch in range(10): 2025-07-17T07:36:45.1804031Z >>> for batch in data_loader: 2025-07-17T07:36:45.1804130Z >>> train_batch(...) 2025-07-17T07:36:45.1804226Z >>> optimizer.step() 2025-07-17T07:36:45.1804334Z >>> scheduler.step() 2025-07-17T07:36:45.1804339Z 2025-07-17T07:36:45.1804503Z .. image:: ../scripts/lr_scheduler_images/OneCycleLR.png 2025-07-17T07:36:45.1804508Z 2025-07-17T07:36:45.1804808Z .. _Super-Convergence\: Very Fast Training of Neural Networks Using Large Learning Rates: 2025-07-17T07:36:45.1804927Z https://arxiv.org/abs/1708.07120 2025-07-17T07:36:45.1805007Z 2025-07-17T07:36:45.1805270Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.1805278Z 2025-07-17T07:36:45.1921616Z msg = Cannot scrape callname=Optimizer.load_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/optimizer.py line=867. 2025-07-17T07:36:45.1922019Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.1922133Z Load the optimizer state. 2025-07-17T07:36:45.1922139Z 2025-07-17T07:36:45.1922222Z Args: 2025-07-17T07:36:45.1922431Z state_dict (dict): optimizer state. Should be an object returned 2025-07-17T07:36:45.1922548Z from a call to :meth:`state_dict`. 2025-07-17T07:36:45.1922553Z 2025-07-17T07:36:45.1922661Z .. warning:: 2025-07-17T07:36:45.1922995Z Make sure this method is called after initializing :class:`torch.optim.lr_scheduler.LRScheduler`, 2025-07-17T07:36:45.1923204Z as calling it beforehand will overwrite the loaded learning rates. 2025-07-17T07:36:45.1923208Z 2025-07-17T07:36:45.1923304Z .. note:: 2025-07-17T07:36:45.1923595Z The names of the parameters (if they exist under the "param_names" key of each param group 2025-07-17T07:36:45.1923791Z in :meth:`state_dict`) will not affect the loading process. 2025-07-17T07:36:45.1924109Z To use the parameters' names for custom cases (such as when the parameters in the loaded state dict 2025-07-17T07:36:45.1924432Z differ from those initialized in the optimizer), 2025-07-17T07:36:45.1924749Z a custom ``register_load_state_dict_pre_hook`` should be implemented to adapt the loaded dict 2025-07-17T07:36:45.1924841Z accordingly. 2025-07-17T07:36:45.1925142Z If ``param_names`` exist in loaded state dict ``param_groups`` they will be saved and override 2025-07-17T07:36:45.1925535Z the current names, if present, in the optimizer state. If they do not exist in loaded state dict, 2025-07-17T07:36:45.1925699Z the optimizer ``param_names`` will remain unchanged. 2025-07-17T07:36:45.1925785Z 2025-07-17T07:36:45.1925905Z Example: 2025-07-17T07:36:45.1926004Z >>> # xdoctest: +SKIP 2025-07-17T07:36:45.1926121Z >>> model = torch.nn.Linear(10, 10) 2025-07-17T07:36:45.1926298Z >>> optim = torch.optim.SGD(model.parameters(), lr=3e-4) 2025-07-17T07:36:45.1926458Z >>> scheduler1 = torch.optim.lr_scheduler.LinearLR( 2025-07-17T07:36:45.1926559Z ... optim, 2025-07-17T07:36:45.1926658Z ... start_factor=0.1, 2025-07-17T07:36:45.1926750Z ... end_factor=1, 2025-07-17T07:36:45.1926858Z ... total_iters=20, 2025-07-17T07:36:45.1926939Z ... ) 2025-07-17T07:36:45.1927126Z >>> scheduler2 = torch.optim.lr_scheduler.CosineAnnealingLR( 2025-07-17T07:36:45.1927228Z ... optim, 2025-07-17T07:36:45.1927320Z ... T_max=80, 2025-07-17T07:36:45.1927417Z ... eta_min=3e-5, 2025-07-17T07:36:45.1927512Z ... ) 2025-07-17T07:36:45.1927656Z >>> lr = torch.optim.lr_scheduler.SequentialLR( 2025-07-17T07:36:45.1927743Z ... optim, 2025-07-17T07:36:45.1927884Z ... schedulers=[scheduler1, scheduler2], 2025-07-17T07:36:45.1927981Z ... milestones=[20], 2025-07-17T07:36:45.1928078Z ... ) 2025-07-17T07:36:45.1928220Z >>> lr.load_state_dict(torch.load("./save_seq.pt")) 2025-07-17T07:36:45.1928422Z >>> # now load the optimizer checkpoint after loading the LRScheduler 2025-07-17T07:36:45.1928597Z >>> optim.load_state_dict(torch.load("./save_optim.pt")) 2025-07-17T07:36:45.1928601Z 2025-07-17T07:36:45.1928681Z 2025-07-17T07:36:45.1928928Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.1928945Z 2025-07-17T07:36:45.2089014Z msg = Cannot scrape callname=AveragedModel in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=120. 2025-07-17T07:36:45.2090218Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.2090967Z Implements averaged model for Stochastic Weight Averaging (SWA) and Exponential Moving Average (EMA). 2025-07-17T07:36:45.2091445Z 2025-07-17T07:36:45.2091705Z Stochastic Weight Averaging was proposed in `Averaging Weights Leads to 2025-07-17T07:36:45.2092289Z Wider Optima and Better Generalization`_ by Pavel Izmailov, Dmitrii 2025-07-17T07:36:45.2092829Z Podoprikhin, Timur Garipov, Dmitry Vetrov and Andrew Gordon Wilson 2025-07-17T07:36:45.2093254Z (UAI 2018). 2025-07-17T07:36:45.2093386Z 2025-07-17T07:36:45.2093613Z Exponential Moving Average is a variation of `Polyak averaging`_, 2025-07-17T07:36:45.2094176Z but using exponential weights instead of equal weights across iterations. 2025-07-17T07:36:45.2094545Z 2025-07-17T07:36:45.2094781Z AveragedModel class creates a copy of the provided module :attr:`model` 2025-07-17T07:36:45.2095390Z on the device :attr:`device` and allows to compute running averages of the 2025-07-17T07:36:45.2095844Z parameters of the :attr:`model`. 2025-07-17T07:36:45.2096051Z 2025-07-17T07:36:45.2096147Z Args: 2025-07-17T07:36:45.2096455Z model (torch.nn.Module): model to use with SWA/EMA 2025-07-17T07:36:45.2097117Z device (torch.device, optional): if provided, the averaged model will be 2025-07-17T07:36:45.2097585Z stored on the :attr:`device` 2025-07-17T07:36:45.2098164Z avg_fn (function, optional): the averaging function used to update 2025-07-17T07:36:45.2098814Z parameters; the function must take in the current value of the 2025-07-17T07:36:45.2099451Z :class:`AveragedModel` parameter, the current value of :attr:`model` 2025-07-17T07:36:45.2099989Z parameter, and the number of models already averaged; if None, 2025-07-17T07:36:45.2100452Z an equally weighted average is used (default: None) 2025-07-17T07:36:45.2101050Z multi_avg_fn (function, optional): the averaging function used to update 2025-07-17T07:36:45.2101636Z parameters inplace; the function must take in the current values of the 2025-07-17T07:36:45.2102254Z :class:`AveragedModel` parameters as a list, the current values of :attr:`model` 2025-07-17T07:36:45.2102881Z parameters as a list, and the number of models already averaged; if None, 2025-07-17T07:36:45.2103394Z an equally weighted average is used (default: None) 2025-07-17T07:36:45.2103876Z use_buffers (bool): if ``True``, it will compute running averages for 2025-07-17T07:36:45.2104413Z both the parameters and the buffers of the model. (default: ``False``) 2025-07-17T07:36:45.2104765Z 2025-07-17T07:36:45.2104851Z Example: 2025-07-17T07:36:45.2105112Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:45.2105466Z >>> loader, optimizer, model, loss_fn = ... 2025-07-17T07:36:45.2105883Z >>> swa_model = torch.optim.swa_utils.AveragedModel(model) 2025-07-17T07:36:45.2106390Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, 2025-07-17T07:36:45.2106848Z >>> T_max=300) 2025-07-17T07:36:45.2107157Z >>> swa_start = 160 2025-07-17T07:36:45.2107475Z >>> swa_scheduler = SWALR(optimizer, swa_lr=0.05) 2025-07-17T07:36:45.2107831Z >>> for i in range(300): 2025-07-17T07:36:45.2108122Z >>> for input, target in loader: 2025-07-17T07:36:45.2108455Z >>> optimizer.zero_grad() 2025-07-17T07:36:45.2108806Z >>> loss_fn(model(input), target).backward() 2025-07-17T07:36:45.2109150Z >>> optimizer.step() 2025-07-17T07:36:45.2109452Z >>> if i > swa_start: 2025-07-17T07:36:45.2109775Z >>> swa_model.update_parameters(model) 2025-07-17T07:36:45.2110125Z >>> swa_scheduler.step() 2025-07-17T07:36:45.2110421Z >>> else: 2025-07-17T07:36:45.2110679Z >>> scheduler.step() 2025-07-17T07:36:45.2110968Z >>> 2025-07-17T07:36:45.2111228Z >>> # Update bn statistics for the swa_model at the end 2025-07-17T07:36:45.2111657Z >>> torch.optim.swa_utils.update_bn(loader, swa_model) 2025-07-17T07:36:45.2111933Z 2025-07-17T07:36:45.2112240Z You can also use custom averaging functions with the `avg_fn` or `multi_avg_fn` parameters. 2025-07-17T07:36:45.2112857Z If no averaging function is provided, the default is to compute 2025-07-17T07:36:45.2113299Z equally-weighted average of the weights (SWA). 2025-07-17T07:36:45.2113566Z 2025-07-17T07:36:45.2113649Z Example: 2025-07-17T07:36:45.2113906Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:45.2114348Z >>> # Compute exponential moving averages of the weights and buffers 2025-07-17T07:36:45.2114847Z >>> ema_model = torch.optim.swa_utils.AveragedModel(model, 2025-07-17T07:36:45.2115352Z >>> torch.optim.swa_utils.get_ema_multi_avg_fn(0.9), use_buffers=True) 2025-07-17T07:36:45.2115685Z 2025-07-17T07:36:45.2115794Z .. note:: 2025-07-17T07:36:45.2116136Z When using SWA/EMA with models containing Batch Normalization you may 2025-07-17T07:36:45.2116682Z need to update the activation statistics for Batch Normalization. 2025-07-17T07:36:45.2117342Z This can be done either by using the :meth:`torch.optim.swa_utils.update_bn` 2025-07-17T07:36:45.2117909Z or by setting :attr:`use_buffers` to `True`. The first approach updates the 2025-07-17T07:36:45.2118500Z statistics in a post-training step by passing data through the model. The 2025-07-17T07:36:45.2119098Z second does it during the parameter update phase by averaging all buffers. 2025-07-17T07:36:45.2119703Z Empirical evidence has shown that updating the statistics in normalization 2025-07-17T07:36:45.2120348Z layers increases accuracy, but you may wish to empirically test which 2025-07-17T07:36:45.2120892Z approach yields the best results in your problem. 2025-07-17T07:36:45.2121155Z 2025-07-17T07:36:45.2121253Z .. note:: 2025-07-17T07:36:45.2121674Z :attr:`avg_fn` and `multi_avg_fn` are not saved in the :meth:`state_dict` of the model. 2025-07-17T07:36:45.2122061Z 2025-07-17T07:36:45.2122144Z .. note:: 2025-07-17T07:36:45.2122473Z When :meth:`update_parameters` is called for the first time (i.e. 2025-07-17T07:36:45.2122981Z :attr:`n_averaged` is `0`) the parameters of `model` are copied 2025-07-17T07:36:45.2123476Z to the parameters of :class:`AveragedModel`. For every subsequent 2025-07-17T07:36:45.2123985Z call of :meth:`update_parameters` the function `avg_fn` is used 2025-07-17T07:36:45.2124395Z to update the parameters. 2025-07-17T07:36:45.2124592Z 2025-07-17T07:36:45.2124812Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-07-17T07:36:45.2125290Z https://arxiv.org/abs/1803.05407 2025-07-17T07:36:45.2125834Z .. _There Are Many Consistent Explanations of Unlabeled Data: Why You Should 2025-07-17T07:36:45.2126286Z Average: 2025-07-17T07:36:45.2126527Z https://arxiv.org/abs/1806.05594 2025-07-17T07:36:45.2126953Z .. _SWALP: Stochastic Weight Averaging in Low-Precision Training: 2025-07-17T07:36:45.2127393Z https://arxiv.org/abs/1904.11943 2025-07-17T07:36:45.2127827Z .. _Stochastic Weight Averaging in Parallel: Large-Batch Training That 2025-07-17T07:36:45.2128269Z Generalizes Well: 2025-07-17T07:36:45.2128559Z https://arxiv.org/abs/2001.02312 2025-07-17T07:36:45.2128874Z .. _Polyak averaging: 2025-07-17T07:36:45.2129198Z https://paperswithcode.com/method/polyak-averaging 2025-07-17T07:36:45.2129560Z 2025-07-17T07:36:45.2129922Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.2130287Z 2025-07-17T07:36:45.2130803Z msg = Cannot scrape callname=SWALR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=375. 2025-07-17T07:36:45.2131642Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.2132257Z Anneals the learning rate in each parameter group to a fixed value. 2025-07-17T07:36:45.2132587Z 2025-07-17T07:36:45.2132828Z This learning rate scheduler is meant to be used with Stochastic Weight 2025-07-17T07:36:45.2133441Z Averaging (SWA) method (see `torch.optim.swa_utils.AveragedModel`). 2025-07-17T07:36:45.2133767Z 2025-07-17T07:36:45.2133848Z Args: 2025-07-17T07:36:45.2134144Z optimizer (torch.optim.Optimizer): wrapped optimizer 2025-07-17T07:36:45.2134637Z swa_lrs (float or list): the learning rate value for all param groups 2025-07-17T07:36:45.2135077Z together or separately for each group. 2025-07-17T07:36:45.2135518Z annealing_epochs (int): number of epochs in the annealing phase 2025-07-17T07:36:45.2135933Z (default: 10) 2025-07-17T07:36:45.2136302Z annealing_strategy (str): "cos" or "linear"; specifies the annealing 2025-07-17T07:36:45.2136843Z strategy: "cos" for cosine annealing, "linear" for linear annealing 2025-07-17T07:36:45.2137297Z (default: "cos") 2025-07-17T07:36:45.2137734Z last_epoch (int): the index of the last epoch (default: -1) 2025-07-17T07:36:45.2138023Z 2025-07-17T07:36:45.2138197Z The :class:`SWALR` scheduler can be used together with other 2025-07-17T07:36:45.2138746Z schedulers to switch to a constant learning rate late in the training 2025-07-17T07:36:45.2139181Z as in the example below. 2025-07-17T07:36:45.2139357Z 2025-07-17T07:36:45.2139445Z Example: 2025-07-17T07:36:45.2139707Z >>> # xdoctest: +SKIP("Undefined variables") 2025-07-17T07:36:45.2140067Z >>> loader, optimizer, model = ... 2025-07-17T07:36:45.2140424Z >>> lr_lambda = lambda epoch: 0.9 2025-07-17T07:36:45.2140964Z >>> scheduler = torch.optim.lr_scheduler.MultiplicativeLR(optimizer, 2025-07-17T07:36:45.2141410Z >>> lr_lambda=lr_lambda) 2025-07-17T07:36:45.2141791Z >>> swa_scheduler = torch.optim.swa_utils.SWALR(optimizer, 2025-07-17T07:36:45.2142243Z >>> anneal_strategy="linear", anneal_epochs=20, swa_lr=0.05) 2025-07-17T07:36:45.2142637Z >>> swa_start = 160 2025-07-17T07:36:45.2142912Z >>> for i in range(300): 2025-07-17T07:36:45.2143200Z >>> for input, target in loader: 2025-07-17T07:36:45.2143537Z >>> optimizer.zero_grad() 2025-07-17T07:36:45.2143884Z >>> loss_fn(model(input), target).backward() 2025-07-17T07:36:45.2144241Z >>> optimizer.step() 2025-07-17T07:36:45.2144533Z >>> if i > swa_start: 2025-07-17T07:36:45.2144830Z >>> swa_scheduler.step() 2025-07-17T07:36:45.2145135Z >>> else: 2025-07-17T07:36:45.2145380Z >>> scheduler.step() 2025-07-17T07:36:45.2145590Z 2025-07-17T07:36:45.2145811Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-07-17T07:36:45.2146275Z https://arxiv.org/abs/1803.05407 2025-07-17T07:36:45.2146563Z 2025-07-17T07:36:45.2146923Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.2147305Z 2025-07-17T07:36:45.6792613Z msg = Cannot scrape callname=assert_close in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_comparison.py line=1331. 2025-07-17T07:36:45.6793906Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:45.6794461Z Asserts that ``actual`` and ``expected`` are close. 2025-07-17T07:36:45.6794818Z 2025-07-17T07:36:45.6795186Z If ``actual`` and ``expected`` are strided, non-quantized, real-valued, and finite, they are considered close if 2025-07-17T07:36:45.6795743Z 2025-07-17T07:36:45.6795858Z .. math:: 2025-07-17T07:36:45.6795986Z 2025-07-17T07:36:45.6796443Z \lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert 2025-07-17T07:36:45.6796962Z 2025-07-17T07:36:45.6797344Z Non-finite values (``-inf`` and ``inf``) are only considered close if and only if they are equal. ``NaN``'s are 2025-07-17T07:36:45.6798103Z only considered equal to each other if ``equal_nan`` is ``True``. 2025-07-17T07:36:45.6798421Z 2025-07-17T07:36:45.6798699Z In addition, they are only considered close if they have the same 2025-07-17T07:36:45.6799014Z 2025-07-17T07:36:45.6799207Z - :attr:`~torch.Tensor.device` (if ``check_device`` is ``True``), 2025-07-17T07:36:45.6799726Z - ``dtype`` (if ``check_dtype`` is ``True``), 2025-07-17T07:36:45.6800133Z - ``layout`` (if ``check_layout`` is ``True``), and 2025-07-17T07:36:45.6800569Z - stride (if ``check_stride`` is ``True``). 2025-07-17T07:36:45.6800806Z 2025-07-17T07:36:45.6801176Z If either ``actual`` or ``expected`` is a meta tensor, only the attribute checks will be performed. 2025-07-17T07:36:45.6801606Z 2025-07-17T07:36:45.6802036Z If ``actual`` and ``expected`` are sparse (either having COO, CSR, CSC, BSR, or BSC layout), their strided members are 2025-07-17T07:36:45.6802960Z checked individually. Indices, namely ``indices`` for COO, ``crow_indices`` and ``col_indices`` for CSR and BSR, 2025-07-17T07:36:45.6804018Z or ``ccol_indices`` and ``row_indices`` for CSC and BSC layouts, respectively, 2025-07-17T07:36:45.6804874Z are always checked for equality whereas the values are checked for closeness according to the definition above. 2025-07-17T07:36:45.6805527Z 2025-07-17T07:36:45.6805879Z If ``actual`` and ``expected`` are quantized, they are considered close if they have the same 2025-07-17T07:36:45.6806714Z :meth:`~torch.Tensor.qscheme` and the result of :meth:`~torch.Tensor.dequantize` is close according to the 2025-07-17T07:36:45.6807342Z definition above. 2025-07-17T07:36:45.6807566Z 2025-07-17T07:36:45.6807978Z ``actual`` and ``expected`` can be :class:`~torch.Tensor`'s or any tensor-or-scalar-likes from which 2025-07-17T07:36:45.6808864Z :class:`torch.Tensor`'s can be constructed with :func:`torch.as_tensor`. Except for Python scalars the input types 2025-07-17T07:36:45.6809840Z have to be directly related. In addition, ``actual`` and ``expected`` can be :class:`~collections.abc.Sequence`'s 2025-07-17T07:36:45.6810796Z or :class:`~collections.abc.Mapping`'s in which case they are considered close if their structure matches and all 2025-07-17T07:36:45.6811577Z their elements are considered close according to the above definition. 2025-07-17T07:36:45.6811983Z 2025-07-17T07:36:45.6812073Z .. note:: 2025-07-17T07:36:45.6812261Z 2025-07-17T07:36:45.6812607Z Python scalars are an exception to the type relation requirement, because their :func:`type`, i.e. 2025-07-17T07:36:45.6813446Z :class:`int`, :class:`float`, and :class:`complex`, is equivalent to the ``dtype`` of a tensor-like. Thus, 2025-07-17T07:36:45.6814234Z Python scalars of different types can be checked, but require ``check_dtype=False``. 2025-07-17T07:36:45.6814704Z 2025-07-17T07:36:45.6814788Z Args: 2025-07-17T07:36:45.6815011Z actual (Any): Actual input. 2025-07-17T07:36:45.6815342Z expected (Any): Expected input. 2025-07-17T07:36:45.6815973Z allow_subclasses (bool): If ``True`` (default) and except for Python scalars, inputs of directly related types 2025-07-17T07:36:45.6816680Z are allowed. Otherwise type equality is required. 2025-07-17T07:36:45.6817381Z rtol (Optional[float]): Relative tolerance. If specified ``atol`` must also be specified. If omitted, default 2025-07-17T07:36:45.6818189Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-07-17T07:36:45.6819004Z atol (Optional[float]): Absolute tolerance. If specified ``rtol`` must also be specified. If omitted, default 2025-07-17T07:36:45.6819826Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-07-17T07:36:45.6820513Z equal_nan (Union[bool, str]): If ``True``, two ``NaN`` values will be considered equal. 2025-07-17T07:36:45.6821233Z check_device (bool): If ``True`` (default), asserts that corresponding tensors are on the same 2025-07-17T07:36:45.6821959Z :attr:`~torch.Tensor.device`. If this check is disabled, tensors on different 2025-07-17T07:36:45.6822683Z :attr:`~torch.Tensor.device`'s are moved to the CPU before being compared. 2025-07-17T07:36:45.6823444Z check_dtype (bool): If ``True`` (default), asserts that corresponding tensors have the same ``dtype``. If this 2025-07-17T07:36:45.6824333Z check is disabled, tensors with different ``dtype``'s are promoted to a common ``dtype`` (according to 2025-07-17T07:36:45.6825024Z :func:`torch.promote_types`) before being compared. 2025-07-17T07:36:45.6825681Z check_layout (bool): If ``True`` (default), asserts that corresponding tensors have the same ``layout``. If this 2025-07-17T07:36:45.6826586Z check is disabled, tensors with different ``layout``'s are converted to strided tensors before being 2025-07-17T07:36:45.6827131Z compared. 2025-07-17T07:36:45.6827814Z check_stride (bool): If ``True`` and corresponding tensors are strided, asserts that they have the same stride. 2025-07-17T07:36:45.6828734Z msg (Optional[Union[str, Callable[[str], str]]]): Optional error message to use in case a failure occurs during 2025-07-17T07:36:45.6829656Z the comparison. Can also passed as callable in which case it will be called with the generated message and 2025-07-17T07:36:45.6830296Z should return the new message. 2025-07-17T07:36:45.6830581Z 2025-07-17T07:36:45.6830682Z Raises: 2025-07-17T07:36:45.6831023Z ValueError: If no :class:`torch.Tensor` can be constructed from an input. 2025-07-17T07:36:45.6831693Z ValueError: If only ``rtol`` or ``atol`` is specified. 2025-07-17T07:36:45.6832302Z AssertionError: If corresponding inputs are not Python scalars and are not directly related. 2025-07-17T07:36:45.6833192Z AssertionError: If ``allow_subclasses`` is ``False``, but corresponding inputs are not Python scalars and have 2025-07-17T07:36:45.6833770Z different types. 2025-07-17T07:36:45.6834318Z AssertionError: If the inputs are :class:`~collections.abc.Sequence`'s, but their length does not match. 2025-07-17T07:36:45.6835241Z AssertionError: If the inputs are :class:`~collections.abc.Mapping`'s, but their set of keys do not match. 2025-07-17T07:36:45.6836049Z AssertionError: If corresponding tensors do not have the same :attr:`~torch.Tensor.shape`. 2025-07-17T07:36:45.6836771Z AssertionError: If ``check_layout`` is ``True``, but corresponding tensors do not have the same 2025-07-17T07:36:45.6837306Z :attr:`~torch.Tensor.layout`. 2025-07-17T07:36:45.6837752Z AssertionError: If only one of corresponding tensors is quantized. 2025-07-17T07:36:45.6838468Z AssertionError: If corresponding tensors are quantized, but have different :meth:`~torch.Tensor.qscheme`'s. 2025-07-17T07:36:45.6839343Z AssertionError: If ``check_device`` is ``True``, but corresponding tensors are not on the same 2025-07-17T07:36:45.6839897Z :attr:`~torch.Tensor.device`. 2025-07-17T07:36:45.6840455Z AssertionError: If ``check_dtype`` is ``True``, but corresponding tensors do not have the same ``dtype``. 2025-07-17T07:36:45.6841252Z AssertionError: If ``check_stride`` is ``True``, but corresponding strided tensors do not have the same stride. 2025-07-17T07:36:45.6842095Z AssertionError: If the values of corresponding tensors are not close according to the definition above. 2025-07-17T07:36:45.6842588Z 2025-07-17T07:36:45.6842954Z The following table displays the default ``rtol`` and ``atol`` for different ``dtype``'s. In case of mismatching 2025-07-17T07:36:45.6843585Z ``dtype``'s, the maximum of both tolerances is used. 2025-07-17T07:36:45.6843842Z 2025-07-17T07:36:45.6843965Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6844329Z | ``dtype`` | ``rtol`` | ``atol`` | 2025-07-17T07:36:45.6844678Z +===========================+============+==========+ 2025-07-17T07:36:45.6845026Z | :attr:`~torch.float16` | ``1e-3`` | ``1e-5`` | 2025-07-17T07:36:45.6845471Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6845899Z | :attr:`~torch.bfloat16` | ``1.6e-2`` | ``1e-5`` | 2025-07-17T07:36:45.6846285Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6846645Z | :attr:`~torch.float32` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:45.6847013Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6847392Z | :attr:`~torch.float64` | ``1e-7`` | ``1e-7`` | 2025-07-17T07:36:45.6847841Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6848214Z | :attr:`~torch.complex32` | ``1e-3`` | ``1e-5`` | 2025-07-17T07:36:45.6848590Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6848963Z | :attr:`~torch.complex64` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:45.6849434Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6849854Z | :attr:`~torch.complex128` | ``1e-7`` | ``1e-7`` | 2025-07-17T07:36:45.6850228Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6850584Z | :attr:`~torch.quint8` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:45.6850954Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6851321Z | :attr:`~torch.quint2x4` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:45.6851674Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6852098Z | :attr:`~torch.quint4x2` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:45.6852466Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6852842Z | :attr:`~torch.qint8` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:45.6853197Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6853575Z | :attr:`~torch.qint32` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:45.6853946Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6854293Z | other | ``0.0`` | ``0.0`` | 2025-07-17T07:36:45.6854649Z +---------------------------+------------+----------+ 2025-07-17T07:36:45.6854898Z 2025-07-17T07:36:45.6854991Z .. note:: 2025-07-17T07:36:45.6855120Z 2025-07-17T07:36:45.6855518Z :func:`~torch.testing.assert_close` is highly configurable with strict default settings. Users are encouraged 2025-07-17T07:36:45.6856363Z to :func:`~functools.partial` it to fit their use case. For example, if an equality check is needed, one might 2025-07-17T07:36:45.6857104Z define an ``assert_equal`` that uses zero tolerances for every ``dtype`` by default: 2025-07-17T07:36:45.6857494Z 2025-07-17T07:36:45.6857595Z >>> import functools 2025-07-17T07:36:45.6858073Z >>> assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=0) 2025-07-17T07:36:45.6858554Z >>> assert_equal(1e-9, 1e-10) 2025-07-17T07:36:45.6858886Z Traceback (most recent call last): 2025-07-17T07:36:45.6859209Z ... 2025-07-17T07:36:45.6859515Z AssertionError: Scalars are not equal! 2025-07-17T07:36:45.6859849Z 2025-07-17T07:36:45.6860106Z Expected 1e-10 but got 1e-09. 2025-07-17T07:36:45.6860427Z Absolute difference: 9.000000000000001e-10 2025-07-17T07:36:45.6860775Z Relative difference: 9.0 2025-07-17T07:36:45.6860963Z 2025-07-17T07:36:45.6861062Z Examples: 2025-07-17T07:36:45.6861291Z >>> # tensor to tensor comparison 2025-07-17T07:36:45.6861647Z >>> expected = torch.tensor([1e0, 1e-1, 1e-2]) 2025-07-17T07:36:45.6862027Z >>> actual = torch.acos(torch.cos(expected)) 2025-07-17T07:36:45.6862412Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:45.6862660Z 2025-07-17T07:36:45.6862768Z >>> # scalar to scalar comparison 2025-07-17T07:36:45.6863080Z >>> import math 2025-07-17T07:36:45.6863343Z >>> expected = math.sqrt(2.0) 2025-07-17T07:36:45.6863644Z >>> actual = 2.0 / math.sqrt(2.0) 2025-07-17T07:36:45.6864014Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:45.6864263Z 2025-07-17T07:36:45.6864439Z >>> # numpy array to numpy array comparison 2025-07-17T07:36:45.6864777Z >>> import numpy as np 2025-07-17T07:36:45.6865070Z >>> expected = np.array([1e0, 1e-1, 1e-2]) 2025-07-17T07:36:45.6865430Z >>> actual = np.arccos(np.cos(expected)) 2025-07-17T07:36:45.6865807Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:45.6866056Z 2025-07-17T07:36:45.6866176Z >>> # sequence to sequence comparison 2025-07-17T07:36:45.6866506Z >>> import numpy as np 2025-07-17T07:36:45.6866942Z >>> # The types of the sequences do not have to match. They only have to have the same 2025-07-17T07:36:45.6867431Z >>> # length and their elements have to match. 2025-07-17T07:36:45.6867911Z >>> expected = [torch.tensor([1.0]), 2.0, np.array(3.0)] 2025-07-17T07:36:45.6868288Z >>> actual = tuple(expected) 2025-07-17T07:36:45.6868636Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:45.6868884Z 2025-07-17T07:36:45.6868998Z >>> # mapping to mapping comparison 2025-07-17T07:36:45.6869345Z >>> from collections import OrderedDict 2025-07-17T07:36:45.6869680Z >>> import numpy as np 2025-07-17T07:36:45.6870115Z >>> foo = torch.tensor(1.0) 2025-07-17T07:36:45.6870411Z >>> bar = 2.0 2025-07-17T07:36:45.6870665Z >>> baz = np.array(3.0) 2025-07-17T07:36:45.6871198Z >>> # The types and a possible ordering of mappings do not have to match. They only 2025-07-17T07:36:45.6871778Z >>> # have to have the same set of keys and their elements have to match. 2025-07-17T07:36:45.6872307Z >>> expected = OrderedDict([("foo", foo), ("bar", bar), ("baz", baz)]) 2025-07-17T07:36:45.6872777Z >>> actual = {"baz": baz, "bar": bar, "foo": foo} 2025-07-17T07:36:45.6873162Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:45.6873428Z 2025-07-17T07:36:45.6873549Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-07-17T07:36:45.6873893Z >>> actual = expected.clone() 2025-07-17T07:36:45.6874252Z >>> # By default, directly related instances can be compared 2025-07-17T07:36:45.6874752Z >>> torch.testing.assert_close(torch.nn.Parameter(actual), expected) 2025-07-17T07:36:45.6875275Z >>> # This check can be made more strict with allow_subclasses=False 2025-07-17T07:36:45.6875703Z >>> torch.testing.assert_close( 2025-07-17T07:36:45.6876106Z ... torch.nn.Parameter(actual), expected, allow_subclasses=False 2025-07-17T07:36:45.6876508Z ... ) 2025-07-17T07:36:45.6876758Z Traceback (most recent call last): 2025-07-17T07:36:45.6877052Z ... 2025-07-17T07:36:45.6877381Z TypeError: No comparison pair was able to handle inputs of type 2025-07-17T07:36:45.6877921Z and . 2025-07-17T07:36:45.6878478Z >>> # If the inputs are not directly related, they are never considered close 2025-07-17T07:36:45.6878984Z >>> torch.testing.assert_close(actual.numpy(), expected) 2025-07-17T07:36:45.6879386Z Traceback (most recent call last): 2025-07-17T07:36:45.6879720Z ... 2025-07-17T07:36:45.6880120Z TypeError: No comparison pair was able to handle inputs of type 2025-07-17T07:36:45.6880634Z and . 2025-07-17T07:36:45.6881106Z >>> # Exceptions to these rules are Python scalars. They can be checked regardless of 2025-07-17T07:36:45.6881592Z >>> # their type if check_dtype=False. 2025-07-17T07:36:45.6881989Z >>> torch.testing.assert_close(1.0, 1, check_dtype=False) 2025-07-17T07:36:45.6882286Z 2025-07-17T07:36:45.6882383Z >>> # NaN != NaN by default. 2025-07-17T07:36:45.6882710Z >>> expected = torch.tensor(float("Nan")) 2025-07-17T07:36:45.6883098Z >>> actual = expected.clone() 2025-07-17T07:36:45.6883453Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:45.6883826Z Traceback (most recent call last): 2025-07-17T07:36:45.6884120Z ... 2025-07-17T07:36:45.6884364Z AssertionError: Scalars are not close! 2025-07-17T07:36:45.6884689Z 2025-07-17T07:36:45.6884926Z Expected nan but got nan. 2025-07-17T07:36:45.6885271Z Absolute difference: nan (up to 1e-05 allowed) 2025-07-17T07:36:45.6885857Z Relative difference: nan (up to 1.3e-06 allowed) 2025-07-17T07:36:45.6886318Z >>> torch.testing.assert_close(actual, expected, equal_nan=True) 2025-07-17T07:36:45.6886633Z 2025-07-17T07:36:45.6886755Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-07-17T07:36:45.6887232Z >>> actual = torch.tensor([1.0, 4.0, 5.0]) 2025-07-17T07:36:45.6887604Z >>> # The default error message can be overwritten. 2025-07-17T07:36:45.6888137Z >>> torch.testing.assert_close(actual, expected, msg="Argh, the tensors are not close!") 2025-07-17T07:36:45.6888671Z Traceback (most recent call last): 2025-07-17T07:36:45.6888977Z ... 2025-07-17T07:36:45.6889240Z AssertionError: Argh, the tensors are not close! 2025-07-17T07:36:45.6889730Z >>> # If msg is a callable, it can be used to augment the generated message with 2025-07-17T07:36:45.6890173Z >>> # extra information 2025-07-17T07:36:45.6890478Z >>> torch.testing.assert_close( 2025-07-17T07:36:45.6890940Z ... actual, expected, msg=lambda msg: f"Header\n\n{msg}\n\nFooter" 2025-07-17T07:36:45.6891343Z ... ) 2025-07-17T07:36:45.6891591Z Traceback (most recent call last): 2025-07-17T07:36:45.6891888Z ... 2025-07-17T07:36:45.6892159Z AssertionError: Header 2025-07-17T07:36:45.6892446Z 2025-07-17T07:36:45.6892686Z Tensor-likes are not close! 2025-07-17T07:36:45.6892985Z 2025-07-17T07:36:45.6893243Z Mismatched elements: 2 / 3 (66.7%) 2025-07-17T07:36:45.6893675Z Greatest absolute difference: 2.0 at index (1,) (up to 1e-05 allowed) 2025-07-17T07:36:45.6894252Z Greatest relative difference: 1.0 at index (1,) (up to 1.3e-06 allowed) 2025-07-17T07:36:45.6894696Z 2025-07-17T07:36:45.6894930Z Footer 2025-07-17T07:36:45.6895134Z 2025-07-17T07:36:45.6895500Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:45.6895865Z 2025-07-17T07:36:46.9555587Z msg = Cannot scrape callname=register_pytree_node in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py line=134. 2025-07-17T07:36:46.9556555Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:46.9557087Z Register a container-like type as pytree node. 2025-07-17T07:36:46.9557350Z 2025-07-17T07:36:46.9557432Z Args: 2025-07-17T07:36:46.9557743Z cls (type): A Python type to treat as an internal pytree node. 2025-07-17T07:36:46.9558311Z flatten_fn (callable): A function to be used during flattening, taking an instance of 2025-07-17T07:36:46.9558954Z ``cls`` and returning a pair, with (1) an iterable for the children to be flattened 2025-07-17T07:36:46.9559620Z recursively, and (2) some hashable auxiliary data to be stored in the treespec and to be 2025-07-17T07:36:46.9560144Z passed to the ``unflatten_fn``. 2025-07-17T07:36:46.9560640Z unflatten_fn (callable): A function taking two arguments: the auxiliary data that was 2025-07-17T07:36:46.9561297Z returned by ``flatten_fn`` and stored in the treespec, and the unflattened children. 2025-07-17T07:36:46.9561835Z The function should return an instance of ``cls``. 2025-07-17T07:36:46.9562361Z serialized_type_name (str, optional): A keyword argument used to specify the fully 2025-07-17T07:36:46.9562914Z qualified name used when serializing the tree spec. 2025-07-17T07:36:46.9563503Z to_dumpable_context (callable, optional): An optional keyword argument to custom specify how 2025-07-17T07:36:46.9564214Z to convert the context of the pytree to a custom json dumpable representation. This is 2025-07-17T07:36:46.9564877Z used for json serialization, which is being used in :mod:`torch.export` right now. 2025-07-17T07:36:46.9565638Z from_dumpable_context (callable, optional): An optional keyword argument to custom specify 2025-07-17T07:36:46.9566336Z how to convert the custom json dumpable representation of the context back to the 2025-07-17T07:36:46.9566978Z original context. This is used for json deserialization, which is being used in 2025-07-17T07:36:46.9567461Z :mod:`torch.export` right now. 2025-07-17T07:36:46.9567938Z 2025-07-17T07:36:46.9568038Z Example:: 2025-07-17T07:36:46.9568166Z 2025-07-17T07:36:46.9568276Z >>> # xdoctest: +SKIP 2025-07-17T07:36:46.9568589Z >>> # Registry a Python type with lambda functions 2025-07-17T07:36:46.9568952Z >>> register_pytree_node( 2025-07-17T07:36:46.9569234Z ... set, 2025-07-17T07:36:46.9569500Z ... lambda s: (sorted(s), None, None), 2025-07-17T07:36:46.9569846Z ... lambda children, _: set(children), 2025-07-17T07:36:46.9570410Z ... ) 2025-07-17T07:36:46.9570625Z 2025-07-17T07:36:46.9570980Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:46.9571475Z 2025-07-17T07:36:47.0107114Z msg = Cannot scrape callname=SelectiveCheckpointContext in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1218. 2025-07-17T07:36:47.0108198Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:47.0108650Z 2025-07-17T07:36:47.0108884Z Context passed to policy function during selective checkpointing. 2025-07-17T07:36:47.0109211Z 2025-07-17T07:36:47.0109498Z This class is used to pass relevant metadata to the policy function during 2025-07-17T07:36:47.0110124Z selective checkpointing. The metadata includes whether the current invocation 2025-07-17T07:36:47.0110753Z of the policy function is during recomputation or not. 2025-07-17T07:36:47.0111089Z 2025-07-17T07:36:47.0111189Z Example: 2025-07-17T07:36:47.0111400Z >>> # xdoctest: +SKIP(stub) 2025-07-17T07:36:47.0111676Z >>> 2025-07-17T07:36:47.0111984Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-07-17T07:36:47.0112323Z >>> print(ctx.is_recompute) 2025-07-17T07:36:47.0112673Z >>> 2025-07-17T07:36:47.0113108Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-07-17T07:36:47.0113666Z >>> 2025-07-17T07:36:47.0113925Z >>> out = torch.utils.checkpoint.checkpoint( 2025-07-17T07:36:47.0114368Z >>> fn, x, y, 2025-07-17T07:36:47.0114612Z >>> use_reentrant=False, 2025-07-17T07:36:47.0114905Z >>> context_fn=context_fn, 2025-07-17T07:36:47.0115187Z >>> ) 2025-07-17T07:36:47.0115302Z 2025-07-17T07:36:47.0115566Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:47.0115930Z 2025-07-17T07:36:47.0116601Z msg = Cannot scrape callname=create_selective_checkpoint_contexts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1358. 2025-07-17T07:36:47.0117593Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:47.0117985Z 2025-07-17T07:36:47.0118220Z Helper to avoid recomputing certain ops during activation checkpointing. 2025-07-17T07:36:47.0118569Z 2025-07-17T07:36:47.0118790Z Use this with `torch.utils.checkpoint.checkpoint` to control which 2025-07-17T07:36:47.0119279Z operations are recomputed during the backward pass. 2025-07-17T07:36:47.0119552Z 2025-07-17T07:36:47.0119630Z Args: 2025-07-17T07:36:47.0119862Z policy_fn_or_list (Callable or List): 2025-07-17T07:36:47.0120259Z - If a policy function is provided, it should accept a 2025-07-17T07:36:47.0120766Z :class:`SelectiveCheckpointContext`, the :class:`OpOverload`, args and 2025-07-17T07:36:47.0121334Z kwargs to the op, and return a :class:`CheckpointPolicy` enum value 2025-07-17T07:36:47.0121897Z indicating whether the execution of the op should be recomputed or not. 2025-07-17T07:36:47.0122448Z - If a list of operations is provided, it is equivalent to a policy 2025-07-17T07:36:47.0122957Z returning `CheckpointPolicy.MUST_SAVE` for the specified 2025-07-17T07:36:47.0123474Z operations and `CheckpointPolicy.PREFER_RECOMPUTE` for all other 2025-07-17T07:36:47.0123903Z operations. 2025-07-17T07:36:47.0124252Z allow_cache_entry_mutation (bool, optional): By default, an error is 2025-07-17T07:36:47.0124978Z raised if any tensors cached by selective activation checkpoint are 2025-07-17T07:36:47.0125599Z mutated in order to ensure correctness. If set to `True`, this check 2025-07-17T07:36:47.0126007Z is disabled. 2025-07-17T07:36:47.0126245Z Returns: 2025-07-17T07:36:47.0126476Z A tuple of two context managers. 2025-07-17T07:36:47.0126681Z 2025-07-17T07:36:47.0126778Z Example: 2025-07-17T07:36:47.0126990Z >>> # xdoctest: +REQUIRES(LINUX) 2025-07-17T07:36:47.0127295Z >>> import functools 2025-07-17T07:36:47.0127545Z >>> 2025-07-17T07:36:47.0127770Z >>> x = torch.rand(10, 10, requires_grad=True) 2025-07-17T07:36:47.0128238Z >>> y = torch.rand(10, 10, requires_grad=True) 2025-07-17T07:36:47.0128562Z >>> 2025-07-17T07:36:47.0128759Z >>> ops_to_save = [ 2025-07-17T07:36:47.0129033Z >>> torch.ops.aten.mm.default, 2025-07-17T07:36:47.0129334Z >>> ] 2025-07-17T07:36:47.0129526Z >>> 2025-07-17T07:36:47.0129765Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-07-17T07:36:47.0130110Z >>> if op in ops_to_save: 2025-07-17T07:36:47.0130472Z >>> return CheckpointPolicy.MUST_SAVE 2025-07-17T07:36:47.0130792Z >>> else: 2025-07-17T07:36:47.0131065Z >>> return CheckpointPolicy.PREFER_RECOMPUTE 2025-07-17T07:36:47.0131388Z >>> 2025-07-17T07:36:47.0131770Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-07-17T07:36:47.0132244Z >>> 2025-07-17T07:36:47.0132454Z >>> # or equivalently 2025-07-17T07:36:47.0132882Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, ops_to_save) 2025-07-17T07:36:47.0133359Z >>> 2025-07-17T07:36:47.0133567Z >>> def fn(x, y): 2025-07-17T07:36:47.0133907Z >>> return torch.sigmoid(torch.matmul(torch.matmul(x, y), y)) * y 2025-07-17T07:36:47.0134306Z >>> 2025-07-17T07:36:47.0134556Z >>> out = torch.utils.checkpoint.checkpoint( 2025-07-17T07:36:47.0134880Z >>> fn, x, y, 2025-07-17T07:36:47.0135134Z >>> use_reentrant=False, 2025-07-17T07:36:47.0135426Z >>> context_fn=context_fn, 2025-07-17T07:36:47.0135697Z >>> ) 2025-07-17T07:36:47.0135822Z 2025-07-17T07:36:47.0136070Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:47.0136448Z 2025-07-17T07:36:47.0353158Z msg = Cannot scrape callname=CppExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1147. 2025-07-17T07:36:47.0354207Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:47.0354609Z 2025-07-17T07:36:47.0354827Z Create a :class:`setuptools.Extension` for C++. 2025-07-17T07:36:47.0355086Z 2025-07-17T07:36:47.0355325Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-07-17T07:36:47.0355983Z bare minimum (but often sufficient) arguments to build a C++ extension. 2025-07-17T07:36:47.0356365Z 2025-07-17T07:36:47.0356605Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-07-17T07:36:47.0357082Z constructor. Full list arguments can be found at 2025-07-17T07:36:47.0357731Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-07-17T07:36:47.0358260Z 2025-07-17T07:36:47.0358362Z .. warning:: 2025-07-17T07:36:47.0358795Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-07-17T07:36:47.0359696Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-07-17T07:36:47.0360316Z the user's responsibility in their library to not use APIs from 2025-07-17T07:36:47.0361187Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-07-17T07:36:47.0362126Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-07-17T07:36:47.0362668Z example, to give access to custom ops from python, the library should 2025-07-17T07:36:47.0363127Z register the ops through the dispatcher. 2025-07-17T07:36:47.0363539Z 2025-07-17T07:36:47.0363779Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-07-17T07:36:47.0364316Z as a compile flag when py_limited_api is specified as an option for 2025-07-17T07:36:47.0364859Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-07-17T07:36:47.0365483Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-07-17T07:36:47.0366236Z safety, and sanity in order to encourage best practices. To target a 2025-07-17T07:36:47.0366943Z different version, set min_supported_cpython to the hexcode of the 2025-07-17T07:36:47.0367384Z CPython version of choice. 2025-07-17T07:36:47.0367567Z 2025-07-17T07:36:47.0367780Z Example: 2025-07-17T07:36:47.0367988Z >>> # xdoctest: +SKIP 2025-07-17T07:36:47.0368308Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-07-17T07:36:47.0368677Z >>> from setuptools import setup 2025-07-17T07:36:47.0369104Z >>> from torch.utils.cpp_extension import BuildExtension, CppExtension 2025-07-17T07:36:47.0369521Z >>> setup( 2025-07-17T07:36:47.0369749Z ... name='extension', 2025-07-17T07:36:47.0370192Z ... ext_modules=[ 2025-07-17T07:36:47.0370446Z ... CppExtension( 2025-07-17T07:36:47.0370735Z ... name='extension', 2025-07-17T07:36:47.0371060Z ... sources=['extension.cpp'], 2025-07-17T07:36:47.0371395Z ... extra_compile_args=['-g'], 2025-07-17T07:36:47.0371776Z ... extra_link_args=['-Wl,--no-as-needed', '-lm']) 2025-07-17T07:36:47.0372126Z ... ], 2025-07-17T07:36:47.0372333Z ... cmdclass={ 2025-07-17T07:36:47.0372600Z ... 'build_ext': BuildExtension 2025-07-17T07:36:47.0372904Z ... }) 2025-07-17T07:36:47.0373029Z 2025-07-17T07:36:47.0373289Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:47.0373655Z 2025-07-17T07:36:47.0374263Z msg = Cannot scrape callname=CUDAExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1217. 2025-07-17T07:36:47.0375192Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:47.0375567Z 2025-07-17T07:36:47.0375722Z Create a :class:`setuptools.Extension` for CUDA/C++. 2025-07-17T07:36:47.0376022Z 2025-07-17T07:36:47.0376262Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-07-17T07:36:47.0377054Z bare minimum (but often sufficient) arguments to build a CUDA/C++ 2025-07-17T07:36:47.0377885Z extension. This includes the CUDA include path, library path and runtime 2025-07-17T07:36:47.0378672Z library. 2025-07-17T07:36:47.0378906Z 2025-07-17T07:36:47.0379162Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-07-17T07:36:47.0379620Z constructor. Full list arguments can be found at 2025-07-17T07:36:47.0380209Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-07-17T07:36:47.0380674Z 2025-07-17T07:36:47.0380773Z .. warning:: 2025-07-17T07:36:47.0381139Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-07-17T07:36:47.0381686Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-07-17T07:36:47.0382220Z the user's responsibility in their library to not use APIs from 2025-07-17T07:36:47.0382768Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-07-17T07:36:47.0383327Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-07-17T07:36:47.0383880Z example, to give access to custom ops from python, the library should 2025-07-17T07:36:47.0384345Z register the ops through the dispatcher. 2025-07-17T07:36:47.0384574Z 2025-07-17T07:36:47.0384811Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-07-17T07:36:47.0385343Z as a compile flag when py_limited_api is specified as an option for 2025-07-17T07:36:47.0386027Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-07-17T07:36:47.0386571Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-07-17T07:36:47.0387122Z safety, and sanity in order to encourage best practices. To target a 2025-07-17T07:36:47.0387919Z different version, set min_supported_cpython to the hexcode of the 2025-07-17T07:36:47.0388480Z CPython version of choice. 2025-07-17T07:36:47.0388769Z 2025-07-17T07:36:47.0388918Z Example: 2025-07-17T07:36:47.0389124Z >>> # xdoctest: +SKIP 2025-07-17T07:36:47.0389438Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-07-17T07:36:47.0389809Z >>> from setuptools import setup 2025-07-17T07:36:47.0390367Z >>> from torch.utils.cpp_extension import BuildExtension, CUDAExtension 2025-07-17T07:36:47.0390799Z >>> setup( 2025-07-17T07:36:47.0391040Z ... name='cuda_extension', 2025-07-17T07:36:47.0391323Z ... ext_modules=[ 2025-07-17T07:36:47.0391590Z ... CUDAExtension( 2025-07-17T07:36:47.0391924Z ... name='cuda_extension', 2025-07-17T07:36:47.0392312Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-07-17T07:36:47.0392712Z ... extra_compile_args={'cxx': ['-g'], 2025-07-17T07:36:47.0393073Z ... 'nvcc': ['-O2']}, 2025-07-17T07:36:47.0393469Z ... extra_link_args=['-Wl,--no-as-needed', '-lcuda']) 2025-07-17T07:36:47.0393848Z ... ], 2025-07-17T07:36:47.0394066Z ... cmdclass={ 2025-07-17T07:36:47.0394329Z ... 'build_ext': BuildExtension 2025-07-17T07:36:47.0394619Z ... }) 2025-07-17T07:36:47.0394755Z 2025-07-17T07:36:47.0394854Z Compute capabilities: 2025-07-17T07:36:47.0395021Z 2025-07-17T07:36:47.0395315Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-07-17T07:36:47.0396022Z building process of the extension, plus PTX. If down the road a new card is installed the 2025-07-17T07:36:47.0396719Z extension may need to be recompiled. If a visible card has a compute capability (CC) that's 2025-07-17T07:36:47.0397434Z newer than the newest version for which your nvcc can build fully-compiled binaries, PyTorch 2025-07-17T07:36:47.0398143Z will make nvcc fall back to building kernels with the newest version of PTX your nvcc does 2025-07-17T07:36:47.0398669Z support (see below for details on PTX). 2025-07-17T07:36:47.0398888Z 2025-07-17T07:36:47.0399194Z You can override the default behavior using `TORCH_CUDA_ARCH_LIST` to explicitly specify which 2025-07-17T07:36:47.0399742Z CCs you want the extension to support: 2025-07-17T07:36:47.0399958Z 2025-07-17T07:36:47.0400161Z ``TORCH_CUDA_ARCH_LIST="6.1 8.6" python build_my_extension.py`` 2025-07-17T07:36:47.0400682Z ``TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" python build_my_extension.py`` 2025-07-17T07:36:47.0401048Z 2025-07-17T07:36:47.0401365Z The +PTX option causes extension kernel binaries to include PTX instructions for the specified 2025-07-17T07:36:47.0402119Z CC. PTX is an intermediate representation that allows kernels to runtime-compile for any CC >= 2025-07-17T07:36:47.0402857Z the specified CC (for example, 8.6+PTX generates PTX that can runtime-compile for any GPU with 2025-07-17T07:36:47.0403559Z CC >= 8.6). This improves your binary's forward compatibility. However, relying on older PTX to 2025-07-17T07:36:47.0404289Z provide forward compat by runtime-compiling for newer CCs can modestly reduce performance on 2025-07-17T07:36:47.0405004Z those newer CCs. If you know exact CC(s) of the GPUs you want to target, you're always better 2025-07-17T07:36:47.0405810Z off specifying them individually. For example, if you want your extension to run on 8.0 and 8.6, 2025-07-17T07:36:47.0406556Z "8.0+PTX" would work functionally because it includes PTX that can runtime-compile for 8.6, but 2025-07-17T07:36:47.0407089Z "8.0 8.6" would be better. 2025-07-17T07:36:47.0407256Z 2025-07-17T07:36:47.0407650Z Note that while it's possible to include all supported archs, the more archs get included the 2025-07-17T07:36:47.0408359Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-07-17T07:36:47.0408765Z 2025-07-17T07:36:47.0409093Z Note that CUDA-11.5 nvcc will hit internal compiler error while parsing torch/extension.h on Windows. 2025-07-17T07:36:47.0409760Z To workaround the issue, move python binding logic to pure C++ file. 2025-07-17T07:36:47.0410083Z 2025-07-17T07:36:47.0410184Z Example use: 2025-07-17T07:36:47.0410402Z #include 2025-07-17T07:36:47.0410787Z at::Tensor SigmoidAlphaBlendForwardCuda(....) 2025-07-17T07:36:47.0411051Z 2025-07-17T07:36:47.0411194Z Instead of: 2025-07-17T07:36:47.0411426Z #include 2025-07-17T07:36:47.0411766Z torch::Tensor SigmoidAlphaBlendForwardCuda(...) 2025-07-17T07:36:47.0412038Z 2025-07-17T07:36:47.0412310Z Currently open issue for nvcc bug: https://github.com/pytorch/pytorch/issues/69460 2025-07-17T07:36:47.0413218Z Complete workaround code example: https://github.com/facebookresearch/pytorch3d/commit/cb170ac024a949f1f9614ffe6af1c38d972f7d48 2025-07-17T07:36:47.0413837Z 2025-07-17T07:36:47.0413955Z Relocatable device code linking: 2025-07-17T07:36:47.0414148Z 2025-07-17T07:36:47.0414425Z If you want to reference device symbols across compilation units (across object files), 2025-07-17T07:36:47.0415082Z the object files need to be built with `relocatable device code` (-rdc=true or -dc). 2025-07-17T07:36:47.0415819Z An exception to this rule is "dynamic parallelism" (nested kernel launches) which is not used a lot anymore. 2025-07-17T07:36:47.0416619Z `Relocatable device code` is less optimized so it needs to be used only on object files that need it. 2025-07-17T07:36:47.0417388Z Using `-dlto` (Device Link Time Optimization) at the device code compilation step and `dlink` step 2025-07-17T07:36:47.0418013Z helps reduce the protentional perf degradation of `-rdc`. 2025-07-17T07:36:47.0418477Z Note that it needs to be used at both steps to be useful. 2025-07-17T07:36:47.0418754Z 2025-07-17T07:36:47.0419118Z If you have `rdc` objects you need to have an extra `-dlink` (device linking) step before the CPU symbol linking step. 2025-07-17T07:36:47.0419777Z There is also a case where `-dlink` is used without `-rdc`: 2025-07-17T07:36:47.0420320Z when an extension is linked against a static lib containing rdc-compiled objects 2025-07-17T07:36:47.0420905Z like the [NVSHMEM library](https://developer.nvidia.com/nvshmem). 2025-07-17T07:36:47.0421225Z 2025-07-17T07:36:47.0421421Z Note: Ninja is required to build a CUDA Extension with RDC linking. 2025-07-17T07:36:47.0421744Z 2025-07-17T07:36:47.0421831Z Example: 2025-07-17T07:36:47.0422087Z >>> # xdoctest: +SKIP 2025-07-17T07:36:47.0422390Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-07-17T07:36:47.0422743Z >>> CUDAExtension( 2025-07-17T07:36:47.0423004Z ... name='cuda_extension', 2025-07-17T07:36:47.0423371Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-07-17T07:36:47.0423724Z ... dlink=True, 2025-07-17T07:36:47.0424009Z ... dlink_libraries=["dlink_lib"], 2025-07-17T07:36:47.0424361Z ... extra_compile_args={'cxx': ['-g'], 2025-07-17T07:36:47.0424706Z ... 'nvcc': ['-O2', '-rdc=true']}) 2025-07-17T07:36:47.0424955Z 2025-07-17T07:36:47.0425202Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:47.0425569Z 2025-07-17T07:36:47.0426133Z msg = Cannot scrape callname=SyclExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1408. 2025-07-17T07:36:47.0427065Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:47.0427445Z 2025-07-17T07:36:47.0427609Z Creates a :class:`setuptools.Extension` for SYCL/C++. 2025-07-17T07:36:47.0427913Z 2025-07-17T07:36:47.0428152Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-07-17T07:36:47.0428776Z bare minimum (but often sufficient) arguments to build a SYCL/C++ 2025-07-17T07:36:47.0437808Z extension. 2025-07-17T07:36:47.0437951Z 2025-07-17T07:36:47.0438183Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-07-17T07:36:47.0438593Z constructor. 2025-07-17T07:36:47.0438740Z 2025-07-17T07:36:47.0438833Z .. warning:: 2025-07-17T07:36:47.0439201Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-07-17T07:36:47.0439767Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-07-17T07:36:47.0440284Z the user's responsibility in their library to not use APIs from 2025-07-17T07:36:47.0440977Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-07-17T07:36:47.0441551Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-07-17T07:36:47.0442093Z example, to give access to custom ops from python, the library should 2025-07-17T07:36:47.0442563Z register the ops through the dispatcher. 2025-07-17T07:36:47.0442805Z 2025-07-17T07:36:47.0443029Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-07-17T07:36:47.0443577Z as a compile flag when py_limited_api is specified as an option for 2025-07-17T07:36:47.0444094Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-07-17T07:36:47.0444635Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-07-17T07:36:47.0445182Z safety, and sanity in order to encourage best practices. To target a 2025-07-17T07:36:47.0445830Z different version, set min_supported_cpython to the hexcode of the 2025-07-17T07:36:47.0446275Z CPython version of choice. 2025-07-17T07:36:47.0446476Z 2025-07-17T07:36:47.0446562Z Example: 2025-07-17T07:36:47.0446785Z >>> # xdoctest: +SKIP 2025-07-17T07:36:47.0447093Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-07-17T07:36:47.0447592Z >>> from torch.utils.cpp_extension import BuildExtension, SyclExtension 2025-07-17T07:36:47.0448021Z >>> setup( 2025-07-17T07:36:47.0448246Z ... name='xpu_extension', 2025-07-17T07:36:47.0448534Z ... ext_modules=[ 2025-07-17T07:36:47.0448798Z ... SyclExtension( 2025-07-17T07:36:47.0449069Z ... name='xpu_extension', 2025-07-17T07:36:47.0449460Z ... sources=['extension.cpp', 'extension_kernel.cpp'], 2025-07-17T07:36:47.0449926Z ... extra_compile_args={'cxx': ['-g', '-std=c++20', '-fPIC']}) 2025-07-17T07:36:47.0450311Z ... ], 2025-07-17T07:36:47.0450523Z ... cmdclass={ 2025-07-17T07:36:47.0450793Z ... 'build_ext': BuildExtension 2025-07-17T07:36:47.0451098Z ... }) 2025-07-17T07:36:47.0451224Z 2025-07-17T07:36:47.0451520Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-07-17T07:36:47.0452193Z building process of the extension. If down the road a new card is installed the 2025-07-17T07:36:47.0452826Z extension may need to be recompiled. You can override the default behavior using 2025-07-17T07:36:47.0453491Z `TORCH_XPU_ARCH_LIST` to explicitly specify which device architectures you want the extension 2025-07-17T07:36:47.0454007Z to support: 2025-07-17T07:36:47.0454142Z 2025-07-17T07:36:47.0454347Z ``TORCH_XPU_ARCH_LIST="pvc,xe-lpg" python build_my_extension.py`` 2025-07-17T07:36:47.0454657Z 2025-07-17T07:36:47.0454965Z Note that while it's possible to include all supported archs, the more archs get included the 2025-07-17T07:36:47.0455663Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-07-17T07:36:47.0456087Z 2025-07-17T07:36:47.0456222Z Note: Ninja is required to build SyclExtension. 2025-07-17T07:36:47.0456480Z 2025-07-17T07:36:47.0456731Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:47.0457096Z 2025-07-17T07:36:47.0457664Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1585. 2025-07-17T07:36:47.0458661Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:47.0459036Z 2025-07-17T07:36:47.0459192Z Load a PyTorch C++ extension just-in-time (JIT). 2025-07-17T07:36:47.0459439Z 2025-07-17T07:36:47.0459645Z To load an extension, a Ninja build file is emitted, which is used to 2025-07-17T07:36:47.0460174Z compile the given sources into a dynamic library. This library is 2025-07-17T07:36:47.0460720Z subsequently loaded into the current Python process as a module and 2025-07-17T07:36:47.0461244Z returned from this function, ready for use. 2025-07-17T07:36:47.0461475Z 2025-07-17T07:36:47.0461680Z By default, the directory to which the build file is emitted and the 2025-07-17T07:36:47.0462278Z resulting library compiled to is ``/torch_extensions/``, where 2025-07-17T07:36:47.0462834Z ```` is the temporary folder on the current platform and ```` 2025-07-17T07:36:47.0463372Z the name of the extension. This location can be overridden in two ways. 2025-07-17T07:36:47.0463898Z First, if the ``TORCH_EXTENSIONS_DIR`` environment variable is set, it 2025-07-17T07:36:47.0464440Z replaces ``/torch_extensions`` and all extensions will be compiled 2025-07-17T07:36:47.0464994Z into subfolders of this directory. Second, if the ``build_directory`` 2025-07-17T07:36:47.0465546Z argument to this function is supplied, it overrides the entire path, i.e. 2025-07-17T07:36:47.0466063Z the library will be compiled into that folder directly. 2025-07-17T07:36:47.0466331Z 2025-07-17T07:36:47.0466555Z To compile the sources, the default system compiler (``c++``) is used, 2025-07-17T07:36:47.0467131Z which can be overridden by setting the ``CXX`` environment variable. To pass 2025-07-17T07:36:47.0467702Z additional arguments to the compilation process, ``extra_cflags`` or 2025-07-17T07:36:47.0468270Z ``extra_ldflags`` can be provided. For example, to compile your extension 2025-07-17T07:36:47.0468827Z with optimizations, pass ``extra_cflags=['-O3']``. You can also use 2025-07-17T07:36:47.0469297Z ``extra_cflags`` to pass further include directories. 2025-07-17T07:36:47.0469571Z 2025-07-17T07:36:47.0469809Z CUDA support with mixed compilation is provided. Simply pass CUDA source 2025-07-17T07:36:47.0470515Z files (``.cu`` or ``.cuh``) along with other sources. Such files will be 2025-07-17T07:36:47.0471063Z detected and compiled with nvcc rather than the C++ compiler. This includes 2025-07-17T07:36:47.0471623Z passing the CUDA lib64 directory as a library directory, and linking 2025-07-17T07:36:47.0472107Z ``cudart``. You can pass additional flags to nvcc via 2025-07-17T07:36:47.0472574Z ``extra_cuda_cflags``, just like with ``extra_cflags`` for C++. Various 2025-07-17T07:36:47.0473119Z heuristics for finding the CUDA install directory are used, which usually 2025-07-17T07:36:47.0473683Z work fine. If not, setting the ``CUDA_HOME`` environment variable is the 2025-07-17T07:36:47.0474105Z safest option. 2025-07-17T07:36:47.0474239Z 2025-07-17T07:36:47.0474486Z SYCL support with mixed compilation is provided. Simply pass SYCL source 2025-07-17T07:36:47.0475033Z files (``.sycl``) along with other sources. Such files will be detected 2025-07-17T07:36:47.0475575Z and compiled with SYCL compiler (such as Intel DPC++ Compiler) rather 2025-07-17T07:36:47.0476118Z than the C++ compiler. You can pass additional flags to SYCL compiler 2025-07-17T07:36:47.0476622Z via ``extra_sycl_cflags``, just like with ``extra_cflags`` for C++. 2025-07-17T07:36:47.0477137Z SYCL compiler is expected to be found via system PATH environment 2025-07-17T07:36:47.0477550Z variable. 2025-07-17T07:36:47.0477668Z 2025-07-17T07:36:47.0477791Z Args: 2025-07-17T07:36:47.0478106Z name: The name of the extension to build. This MUST be the same as the 2025-07-17T07:36:47.0478548Z name of the pybind11 module! 2025-07-17T07:36:47.0478963Z sources: A list of relative or absolute paths to C++ source files. 2025-07-17T07:36:47.0479614Z extra_cflags: optional list of compiler flags to forward to the build. 2025-07-17T07:36:47.0480176Z extra_cuda_cflags: optional list of compiler flags to forward to nvcc 2025-07-17T07:36:47.0480623Z when building CUDA sources. 2025-07-17T07:36:47.0481034Z extra_sycl_cflags: optional list of compiler flags to forward to SYCL 2025-07-17T07:36:47.0481494Z compiler when building SYCL sources. 2025-07-17T07:36:47.0481943Z extra_ldflags: optional list of linker flags to forward to the build. 2025-07-17T07:36:47.0482501Z extra_include_paths: optional list of include directories to forward 2025-07-17T07:36:47.0482994Z to the build. 2025-07-17T07:36:47.0483338Z build_directory: optional path to use as build workspace. 2025-07-17T07:36:47.0483818Z verbose: If ``True``, turns on verbose logging of load steps. 2025-07-17T07:36:47.0484323Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-07-17T07:36:47.0484834Z the build. If set to ``None`` (default), this value is 2025-07-17T07:36:47.0485391Z automatically determined based on the existence of ``.cu`` or 2025-07-17T07:36:47.0485896Z ``.cuh`` in ``sources``. Set it to `True`` to force CUDA headers 2025-07-17T07:36:47.0486281Z and libraries to be included. 2025-07-17T07:36:47.0486715Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-07-17T07:36:47.0487217Z the build. If set to ``None`` (default), this value is 2025-07-17T07:36:47.0487692Z automatically determined based on the existence of ``.sycl`` in 2025-07-17T07:36:47.0488195Z ``sources``. Set it to `True`` to force SYCL headers and 2025-07-17T07:36:47.0488581Z libraries to be included. 2025-07-17T07:36:47.0489008Z is_python_module: If ``True`` (default), imports the produced shared 2025-07-17T07:36:47.0489509Z library as a Python module. If ``False``, behavior depends on 2025-07-17T07:36:47.0489918Z ``is_standalone``. 2025-07-17T07:36:47.0490297Z is_standalone: If ``False`` (default) loads the constructed extension 2025-07-17T07:36:47.0490807Z into the process as a plain dynamic library. If ``True``, build a 2025-07-17T07:36:47.0491228Z standalone executable. 2025-07-17T07:36:47.0491411Z 2025-07-17T07:36:47.0491507Z Returns: 2025-07-17T07:36:47.0491724Z If ``is_python_module`` is ``True``: 2025-07-17T07:36:47.0492122Z Returns the loaded PyTorch extension as a Python module. 2025-07-17T07:36:47.0492425Z 2025-07-17T07:36:47.0492624Z If ``is_python_module`` is ``False`` and ``is_standalone`` is ``False``: 2025-07-17T07:36:47.0493165Z Returns nothing. (The shared library is loaded into the process as 2025-07-17T07:36:47.0493575Z a side effect.) 2025-07-17T07:36:47.0493742Z 2025-07-17T07:36:47.0493848Z If ``is_standalone`` is ``True``. 2025-07-17T07:36:47.0494256Z Return the path to the executable. (On Windows, TORCH_LIB_PATH is 2025-07-17T07:36:47.0494740Z added to the PATH environment variable as a side effect.) 2025-07-17T07:36:47.0495038Z 2025-07-17T07:36:47.0495167Z Example: 2025-07-17T07:36:47.0495432Z >>> # xdoctest: +SKIP 2025-07-17T07:36:47.0495741Z >>> from torch.utils.cpp_extension import load 2025-07-17T07:36:47.0496067Z >>> module = load( 2025-07-17T07:36:47.0496321Z ... name='extension', 2025-07-17T07:36:47.0496662Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-07-17T07:36:47.0497054Z ... extra_cflags=['-O2'], 2025-07-17T07:36:47.0497342Z ... verbose=True) 2025-07-17T07:36:47.0497503Z 2025-07-17T07:36:47.0497769Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:47.0498136Z 2025-07-17T07:36:47.0498679Z msg = Cannot scrape callname=load_inline in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1890. 2025-07-17T07:36:47.0499571Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:47.0500034Z 2025-07-17T07:36:47.0500240Z Load a PyTorch C++ extension just-in-time (JIT) from string sources. 2025-07-17T07:36:47.0500560Z 2025-07-17T07:36:47.0500803Z This function behaves exactly like :func:`load`, but takes its sources as 2025-07-17T07:36:47.0501381Z strings rather than filenames. These strings are stored to files in the 2025-07-17T07:36:47.0501927Z build directory, after which the behavior of :func:`load_inline` is 2025-07-17T07:36:47.0502356Z identical to :func:`load`. 2025-07-17T07:36:47.0502528Z 2025-07-17T07:36:47.0502624Z See `the 2025-07-17T07:36:47.0503191Z tests `_ 2025-07-17T07:36:47.0503774Z for good examples of using this function. 2025-07-17T07:36:47.0503999Z 2025-07-17T07:36:47.0504240Z Sources may omit two required parts of a typical non-inline C++ extension: 2025-07-17T07:36:47.0504821Z the necessary header includes, as well as the (pybind11) binding code. More 2025-07-17T07:36:47.0505426Z precisely, strings passed to ``cpp_sources`` are first concatenated into a 2025-07-17T07:36:47.0505974Z single ``.cpp`` file. This file is then prepended with ``#include 2025-07-17T07:36:47.0506379Z `` 2025-07-17T07:36:47.0506531Z 2025-07-17T07:36:47.0506752Z Furthermore, if the ``functions`` argument is supplied, bindings will be 2025-07-17T07:36:47.0507331Z automatically generated for each function specified. ``functions`` can 2025-07-17T07:36:47.0507902Z either be a list of function names, or a dictionary mapping from function 2025-07-17T07:36:47.0508454Z names to docstrings. If a list is given, the name of each function is used 2025-07-17T07:36:47.0508889Z as its docstring. 2025-07-17T07:36:47.0509027Z 2025-07-17T07:36:47.0509251Z The sources in ``cuda_sources`` are concatenated into a separate ``.cu`` 2025-07-17T07:36:47.0509757Z file and prepended with ``torch/types.h``, ``cuda.h`` and 2025-07-17T07:36:47.0510241Z ``cuda_runtime.h`` includes. The ``.cpp`` and ``.cu`` files are compiled 2025-07-17T07:36:47.0510793Z separately, but ultimately linked into a single library. Note that no 2025-07-17T07:36:47.0511363Z bindings are generated for functions in ``cuda_sources`` per se. To bind 2025-07-17T07:36:47.0511915Z to a CUDA kernel, you must create a C++ function that calls it, and either 2025-07-17T07:36:47.0512460Z declare or define this C++ function in one of the ``cpp_sources`` (and 2025-07-17T07:36:47.0512899Z include its name in ``functions``). 2025-07-17T07:36:47.0513103Z 2025-07-17T07:36:47.0513356Z The sources in ``sycl_sources`` are concatenated into a separate ``.sycl`` 2025-07-17T07:36:47.0513899Z file and prepended with ``torch/types.h``, ``sycl/sycl.hpp`` includes. 2025-07-17T07:36:47.0514429Z The ``.cpp`` and ``.sycl`` files are compiled separately, but ultimately 2025-07-17T07:36:47.0514960Z linked into a single library. Note that no bindings are generated for 2025-07-17T07:36:47.0515494Z functions in ``sycl_sources`` per se. To bind to a SYCL kernel, you must 2025-07-17T07:36:47.0516032Z create a C++ function that calls it, and either declare or define this 2025-07-17T07:36:47.0516541Z C++ function in one of the ``cpp_sources`` (and include its name 2025-07-17T07:36:47.0516946Z in ``functions``). 2025-07-17T07:36:47.0517087Z 2025-07-17T07:36:47.0517091Z 2025-07-17T07:36:47.0517095Z 2025-07-17T07:36:47.0517273Z See :func:`load` for a description of arguments omitted below. 2025-07-17T07:36:47.0517574Z 2025-07-17T07:36:47.0517652Z Args: 2025-07-17T07:36:47.0517982Z cpp_sources: A string, or list of strings, containing C++ source code. 2025-07-17T07:36:47.0518542Z cuda_sources: A string, or list of strings, containing CUDA source code. 2025-07-17T07:36:47.0519092Z sycl_sources: A string, or list of strings, containing SYCL source code. 2025-07-17T07:36:47.0519672Z functions: A list of function names for which to generate function 2025-07-17T07:36:47.0520209Z bindings. If a dictionary is given, it should map function names to 2025-07-17T07:36:47.0520796Z docstrings (which are otherwise just the function names). 2025-07-17T07:36:47.0521320Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-07-17T07:36:47.0521819Z the build. If set to ``None`` (default), this value is 2025-07-17T07:36:47.0522301Z automatically determined based on whether ``cuda_sources`` is 2025-07-17T07:36:47.0522761Z provided. Set it to ``True`` to force CUDA headers 2025-07-17T07:36:47.0523138Z and libraries to be included. 2025-07-17T07:36:47.0523566Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-07-17T07:36:47.0524102Z the build. If set to ``None`` (default), this value is 2025-07-17T07:36:47.0524578Z automatically determined based on whether ``sycl_sources`` is 2025-07-17T07:36:47.0525054Z provided. Set it to ``True`` to force SYCL headers 2025-07-17T07:36:47.0525489Z and libraries to be included. 2025-07-17T07:36:47.0525914Z with_pytorch_error_handling: Determines whether pytorch error and 2025-07-17T07:36:47.0526442Z warning macros are handled by pytorch instead of pybind. To do 2025-07-17T07:36:47.0526974Z this, each function ``foo`` is called via an intermediary ``_safe_foo`` 2025-07-17T07:36:47.0527500Z function. This redirection might cause issues in obscure cases 2025-07-17T07:36:47.0528002Z of cpp. This flag should be set to ``False`` when this redirect 2025-07-17T07:36:47.0528398Z causes issues. 2025-07-17T07:36:47.0528791Z no_implicit_headers: If ``True``, skips automatically adding headers, most notably 2025-07-17T07:36:47.0529396Z ``#include `` and ``#include `` lines. 2025-07-17T07:36:47.0529898Z Use this option to improve cold start times when you 2025-07-17T07:36:47.0530426Z already include the necessary headers in your source code. Default: ``False``. 2025-07-17T07:36:47.0530804Z 2025-07-17T07:36:47.0530888Z Example: 2025-07-17T07:36:47.0531156Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-07-17T07:36:47.0531569Z >>> from torch.utils.cpp_extension import load_inline 2025-07-17T07:36:47.0531913Z >>> source = """ 2025-07-17T07:36:47.0532213Z at::Tensor sin_add(at::Tensor x, at::Tensor y) { 2025-07-17T07:36:47.0532607Z return x.sin() + y.sin(); 2025-07-17T07:36:47.0532872Z } 2025-07-17T07:36:47.0533055Z """ 2025-07-17T07:36:47.0533308Z >>> module = load_inline(name='inline_extension', 2025-07-17T07:36:47.0533674Z ... cpp_sources=[source], 2025-07-17T07:36:47.0534013Z ... functions=['sin_add']) 2025-07-17T07:36:47.0534251Z 2025-07-17T07:36:47.0534334Z .. note:: 2025-07-17T07:36:47.0534693Z Since load_inline will just-in-time compile the source code, please ensure 2025-07-17T07:36:47.0535267Z that you have the right toolchains installed in the runtime. For example, 2025-07-17T07:36:47.0535836Z when loading C++, make sure a C++ compiler is available. If you're loading 2025-07-17T07:36:47.0536414Z a CUDA extension, you will need to additionally install the corresponding CUDA 2025-07-17T07:36:47.0537026Z toolkit (nvcc and any other dependencies your code has). Compiling toolchains 2025-07-17T07:36:47.0542126Z are not included when you install torch and must be additionally installed. 2025-07-17T07:36:47.0542499Z 2025-07-17T07:36:47.0542754Z During compiling, by default, the Ninja backend uses #CPUS + 2 workers to build 2025-07-17T07:36:47.0543353Z the extension. This may use up too many resources on some systems. One 2025-07-17T07:36:47.0543914Z can control the number of workers by setting the `MAX_JOBS` environment 2025-07-17T07:36:47.0544452Z variable to a non-negative number. 2025-07-17T07:36:47.0544729Z 2025-07-17T07:36:47.0545119Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:47.0545758Z 2025-07-17T07:36:47.0582544Z msg = Cannot scrape callname=ThroughputBenchmark in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/throughput_benchmark.py line=61. 2025-07-17T07:36:47.0583552Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:47.0583927Z 2025-07-17T07:36:47.0584227Z This class is a wrapper around a c++ component throughput_benchmark::ThroughputBenchmark. 2025-07-17T07:36:47.0584673Z 2025-07-17T07:36:47.0584981Z This wrapper on the throughput_benchmark::ThroughputBenchmark component is responsible 2025-07-17T07:36:47.0585633Z for executing a PyTorch module (nn.Module or ScriptModule) under an inference 2025-07-17T07:36:47.0586370Z server like load. It can emulate multiple calling threads to a single module 2025-07-17T07:36:47.0586962Z provided. In the future we plan to enhance this component to support inter and 2025-07-17T07:36:47.0587557Z intra-op parallelism as well as multiple models running in a single process. 2025-07-17T07:36:47.0587941Z 2025-07-17T07:36:47.0588189Z Please note that even though nn.Module is supported, it might incur an overhead 2025-07-17T07:36:47.0588837Z from the need to hold GIL every time we execute Python code or pass around 2025-07-17T07:36:47.0589419Z inputs as Python objects. As soon as you have a ScriptModule version of your 2025-07-17T07:36:47.0590006Z model for inference deployment it is better to switch to using it in this 2025-07-17T07:36:47.0590456Z benchmark. 2025-07-17T07:36:47.0590578Z 2025-07-17T07:36:47.0590679Z Example:: 2025-07-17T07:36:47.0590798Z 2025-07-17T07:36:47.0590928Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:47.0591288Z >>> from torch.utils import ThroughputBenchmark 2025-07-17T07:36:47.0591678Z >>> bench = ThroughputBenchmark(my_module) 2025-07-17T07:36:47.0592081Z >>> # Pre-populate benchmark's data set with the inputs 2025-07-17T07:36:47.0592452Z >>> for input in inputs: 2025-07-17T07:36:47.0592848Z ... # Both args and kwargs work, same as any PyTorch Module / ScriptModule 2025-07-17T07:36:47.0593318Z ... bench.add_input(input[0], x2=input[1]) 2025-07-17T07:36:47.0593742Z >>> # Inputs supplied above are randomly used during the execution 2025-07-17T07:36:47.0594158Z >>> stats = bench.benchmark( 2025-07-17T07:36:47.0594456Z ... num_calling_threads=4, 2025-07-17T07:36:47.0594762Z ... num_warmup_iters = 100, 2025-07-17T07:36:47.0595046Z ... num_iters = 1000, 2025-07-17T07:36:47.0595308Z ... ) 2025-07-17T07:36:47.0595603Z >>> print("Avg latency (ms): {}".format(stats.latency_avg_ms)) 2025-07-17T07:36:47.0596059Z >>> print("Number of iterations: {}".format(stats.num_iters)) 2025-07-17T07:36:47.0596363Z 2025-07-17T07:36:47.0596612Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:47.0596979Z 2025-07-17T07:36:47.1501558Z msg = Cannot scrape callname=DistributedSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/distributed.py line=18. 2025-07-17T07:36:47.1502570Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:47.1503145Z Sampler that restricts data loading to a subset of the dataset. 2025-07-17T07:36:47.1503496Z 2025-07-17T07:36:47.1503630Z It is especially useful in conjunction with 2025-07-17T07:36:47.1504359Z :class:`torch.nn.parallel.DistributedDataParallel`. In such a case, each 2025-07-17T07:36:47.1504986Z process can pass a :class:`~torch.utils.data.DistributedSampler` instance as a 2025-07-17T07:36:47.1505582Z :class:`~torch.utils.data.DataLoader` sampler, and load a subset of the 2025-07-17T07:36:47.1506063Z original dataset that is exclusive to it. 2025-07-17T07:36:47.1506312Z 2025-07-17T07:36:47.1506407Z .. note:: 2025-07-17T07:36:47.1506771Z Dataset is assumed to be of constant size and that any instance of it always 2025-07-17T07:36:47.1507257Z returns the same elements in the same order. 2025-07-17T07:36:47.1507584Z 2025-07-17T07:36:47.1507667Z Args: 2025-07-17T07:36:47.1507902Z dataset: Dataset used for sampling. 2025-07-17T07:36:47.1508362Z num_replicas (int, optional): Number of processes participating in 2025-07-17T07:36:47.1508951Z distributed training. By default, :attr:`world_size` is retrieved from the 2025-07-17T07:36:47.1509434Z current distributed group. 2025-07-17T07:36:47.1509891Z rank (int, optional): Rank of the current process within :attr:`num_replicas`. 2025-07-17T07:36:47.1510444Z By default, :attr:`rank` is retrieved from the current distributed 2025-07-17T07:36:47.1510848Z group. 2025-07-17T07:36:47.1511303Z shuffle (bool, optional): If ``True`` (default), sampler will shuffle the 2025-07-17T07:36:47.1511730Z indices. 2025-07-17T07:36:47.1512070Z seed (int, optional): random seed used to shuffle the sampler if 2025-07-17T07:36:47.1512576Z :attr:`shuffle=True`. This number should be identical across all 2025-07-17T07:36:47.1513047Z processes in the distributed group. Default: ``0``. 2025-07-17T07:36:47.1513538Z drop_last (bool, optional): if ``True``, then the sampler will drop the 2025-07-17T07:36:47.1514067Z tail of the data to make it evenly divisible across the number of 2025-07-17T07:36:47.1514579Z replicas. If ``False``, the sampler will add extra indices to make 2025-07-17T07:36:47.1515097Z the data evenly divisible across the replicas. Default: ``False``. 2025-07-17T07:36:47.1515433Z 2025-07-17T07:36:47.1515522Z .. warning:: 2025-07-17T07:36:47.1515852Z In distributed mode, calling the :meth:`set_epoch` method at 2025-07-17T07:36:47.1516399Z the beginning of each epoch **before** creating the :class:`DataLoader` iterator 2025-07-17T07:36:47.1517014Z is necessary to make shuffling work properly across multiple epochs. Otherwise, 2025-07-17T07:36:47.1517511Z the same ordering will be always used. 2025-07-17T07:36:47.1517738Z 2025-07-17T07:36:47.1517833Z Example:: 2025-07-17T07:36:47.1517957Z 2025-07-17T07:36:47.1518053Z >>> # xdoctest: +SKIP 2025-07-17T07:36:47.1518451Z >>> sampler = DistributedSampler(dataset) if is_distributed else None 2025-07-17T07:36:47.1518960Z >>> loader = DataLoader(dataset, shuffle=(sampler is None), 2025-07-17T07:36:47.1519361Z ... sampler=sampler) 2025-07-17T07:36:47.1519708Z >>> for epoch in range(start_epoch, n_epochs): 2025-07-17T07:36:47.1520055Z ... if is_distributed: 2025-07-17T07:36:47.1520363Z ... sampler.set_epoch(epoch) 2025-07-17T07:36:47.1520670Z ... train(loader) 2025-07-17T07:36:47.1520934Z 2025-07-17T07:36:47.1521298Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:47.1521665Z 2025-07-17T07:36:47.3443405Z gathering tests 2025-07-17T07:36:47.3454278Z running 719 test(s) 2025-07-17T07:36:47.3475137Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::typename:0, line 1074 <- wrt source file 2025-07-17T07:36:47.3482659Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::typename:0 2025-07-17T07:36:47.3483775Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::is_tensor:0, line 1110 <- wrt source file 2025-07-17T07:36:47.3487570Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::is_tensor:0 2025-07-17T07:36:47.3489034Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_device:0, line 1195 <- wrt source file 2025-07-17T07:36:47.3490586Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_device:0 2025-07-17T07:36:47.3491912Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_tensor_type:0, line 1244 <- wrt source file 2025-07-17T07:36:47.3493775Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_tensor_type:0 2025-07-17T07:36:47.3495325Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_dtype:0, line 1281 <- wrt source file 2025-07-17T07:36:47.3496544Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_dtype:0 2025-07-17T07:36:47.3498180Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::use_deterministic_algorithms:0, line 1436 <- wrt source file 2025-07-17T07:36:47.3499909Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::use_deterministic_algorithms:0 2025-07-17T07:36:47.3501466Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::compile:0, line 2559 <- wrt source file 2025-07-17T07:36:47.3502796Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::compile:0 2025-07-17T07:36:47.3504111Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0, line 2832 <- wrt source file 2025-07-17T07:36:47.3505485Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0 2025-07-17T07:36:47.3506808Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::Generator:0, line 15 <- wrt source file 2025-07-17T07:36:47.3508151Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::Generator:0 2025-07-17T07:36:47.3509458Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::_LinAlgError:0, line 5 <- wrt source file 2025-07-17T07:36:47.3510831Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::_LinAlgError:0 2025-07-17T07:36:47.3512042Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::custom_op:0, line 55 <- wrt source file 2025-07-17T07:36:47.3513178Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::custom_op:0 2025-07-17T07:36:47.3514272Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl:0, line 138 <- wrt source file 2025-07-17T07:36:47.3515354Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl:0 2025-07-17T07:36:47.3516466Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl_abstract:0, line 208 <- wrt source file 2025-07-17T07:36:47.3918521Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl_abstract:0 2025-07-17T07:36:47.3919920Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_namedtensor_internals.py::update_names:0, line 118 <- wrt source file 2025-07-17T07:36:47.3921560Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_namedtensor_internals.py::update_names:0 2025-07-17T07:36:47.3922866Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_hook:0, line 649 <- wrt source file 2025-07-17T07:36:47.3945166Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_hook:0 2025-07-17T07:36:47.3946478Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0, line 706 <- wrt source file 2025-07-17T07:36:47.3962465Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0 2025-07-17T07:36:47.3963759Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.refine_names:0, line 1333 <- wrt source file 2025-07-17T07:36:47.4045488Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.refine_names:0 2025-07-17T07:36:47.4046685Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.align_to:0, line 1378 <- wrt source file 2025-07-17T07:36:47.4050717Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.align_to:0 2025-07-17T07:36:47.4051873Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.rename:0, line 1451 <- wrt source file 2025-07-17T07:36:47.4063838Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.rename:0 2025-07-17T07:36:47.4065013Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0, line 1481 <- wrt source file 2025-07-17T07:36:47.4088567Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0 2025-07-17T07:36:47.4089778Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor_str.py::set_printoptions:0, line 53 <- wrt source file 2025-07-17T07:36:47.4108373Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor_str.py::set_printoptions:0 2025-07-17T07:36:47.4109592Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_tensors:0, line 64 <- wrt source file 2025-07-17T07:36:47.4114550Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_tensors:0 2025-07-17T07:36:47.4115759Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_shapes:0, line 92 <- wrt source file 2025-07-17T07:36:47.4117529Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_shapes:0 2025-07-17T07:36:47.4118679Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::split:0, line 193 <- wrt source file 2025-07-17T07:36:47.4130268Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::split:0 2025-07-17T07:36:47.4131380Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::einsum:0, line 307 <- wrt source file 2025-07-17T07:36:47.4159981Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::einsum:0 2025-07-17T07:36:47.4161192Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_unique_consecutive_impl:0, line 1041 <- wrt source file 2025-07-17T07:36:47.4183095Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_unique_consecutive_impl:0 2025-07-17T07:36:47.4184451Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::tensordot:0, line 1316 <- wrt source file 2025-07-17T07:36:47.4256230Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::tensordot:0 2025-07-17T07:36:47.4257420Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cartesian_prod:0, line 1400 <- wrt source file 2025-07-17T07:36:47.4263473Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cartesian_prod:0 2025-07-17T07:36:47.4264735Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::block_diag:0, line 1434 <- wrt source file 2025-07-17T07:36:47.4273317Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::block_diag:0 2025-07-17T07:36:47.4274451Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cdist:0, line 1490 <- wrt source file 2025-07-17T07:36:47.4296260Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cdist:0 2025-07-17T07:36:47.4297545Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_1d:0, line 1531 <- wrt source file 2025-07-17T07:36:47.4312171Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_1d:0 2025-07-17T07:36:47.4313331Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_2d:0, line 1567 <- wrt source file 2025-07-17T07:36:47.4329044Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_2d:0 2025-07-17T07:36:47.4330196Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_3d:0, line 1605 <- wrt source file 2025-07-17T07:36:47.4349661Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_3d:0 2025-07-17T07:36:47.4350784Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::norm:0, line 1778 <- wrt source file 2025-07-17T07:36:47.4381389Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::norm:0 2025-07-17T07:36:47.4382542Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::unravel_index:0, line 1946 <- wrt source file 2025-07-17T07:36:47.4407670Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::unravel_index:0 2025-07-17T07:36:47.4409043Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::chain_matmul:0, line 2046 <- wrt source file 2025-07-17T07:36:47.4410689Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::chain_matmul:0 2025-07-17T07:36:47.4411953Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_lu_impl:0, line 2146 <- wrt source file 2025-07-17T07:36:47.4413121Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_lu_impl:0 2025-07-17T07:36:47.4414166Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::list:0, line 468 <- wrt source file 2025-07-17T07:36:47.4415506Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::list:0 2025-07-17T07:36:47.4416533Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::help:0, line 528 <- wrt source file 2025-07-17T07:36:47.4417564Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::help:0 2025-07-17T07:36:47.4418754Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.define:0, line 152 <- wrt source file 2025-07-17T07:36:47.4419920Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.define:0 2025-07-17T07:36:47.4421150Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library._impl_with_aoti_compile:0, line 246 <- wrt source file 2025-07-17T07:36:47.4428058Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library._impl_with_aoti_compile:0 2025-07-17T07:36:47.4429388Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.impl:0, line 306 <- wrt source file 2025-07-17T07:36:47.4432362Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.impl:0 2025-07-17T07:36:47.4433464Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::define:0, line 511 <- wrt source file 2025-07-17T07:36:47.4463244Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::define:0 2025-07-17T07:36:47.4464426Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::impl:0, line 617 <- wrt source file 2025-07-17T07:36:47.4478979Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::impl:0 2025-07-17T07:36:47.4480514Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_kernel:0, line 798 <- wrt source file 2025-07-17T07:36:47.4481719Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_kernel:0 2025-07-17T07:36:47.4482879Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_autocast:0, line 866 <- wrt source file 2025-07-17T07:36:47.4484082Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_autocast:0 2025-07-17T07:36:47.4485280Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_torch_dispatch:0, line 1217 <- wrt source file 2025-07-17T07:36:47.4561181Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_torch_dispatch:0 2025-07-17T07:36:47.4562377Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_vmap:0, line 1306 <- wrt source file 2025-07-17T07:36:47.4707327Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_vmap:0 2025-07-17T07:36:47.4708513Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_ignored_functions:0, line 116 <- wrt source file 2025-07-17T07:36:47.4713609Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_ignored_functions:0 2025-07-17T07:36:47.4714847Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_testing_overrides:0, line 422 <- wrt source file 2025-07-17T07:36:47.4750298Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_testing_overrides:0 2025-07-17T07:36:47.4751529Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::wrap_torch_function:0, line 1575 <- wrt source file 2025-07-17T07:36:47.4753786Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::wrap_torch_function:0 2025-07-17T07:36:47.4755022Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::handle_torch_function:0, line 1710 <- wrt source file 2025-07-17T07:36:47.4757279Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::handle_torch_function:0 2025-07-17T07:36:47.4758688Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_method_or_property:0, line 1958 <- wrt source file 2025-07-17T07:36:47.4783796Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_method_or_property:0 2025-07-17T07:36:47.4785048Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_like:0, line 1977 <- wrt source file 2025-07-17T07:36:47.4790936Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_like:0 2025-07-17T07:36:47.4792431Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/quasirandom.py::SobolEngine:0, line 39 <- wrt source file 2025-07-17T07:36:47.4794013Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/quasirandom.py::SobolEngine:0 2025-07-17T07:36:47.4795533Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::add_safe_globals:0, line 299 <- wrt source file 2025-07-17T07:36:47.4796941Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::add_safe_globals:0 2025-07-17T07:36:47.4798154Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::safe_globals:0, line 324 <- wrt source file 2025-07-17T07:36:47.4799735Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::safe_globals:0 2025-07-17T07:36:47.4801394Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::skip_data:0, line 400 <- wrt source file 2025-07-17T07:36:47.4802622Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::skip_data:0 2025-07-17T07:36:47.4804178Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::register_package:0, line 472 <- wrt source file 2025-07-17T07:36:47.4805951Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::register_package:0 2025-07-17T07:36:47.4807121Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::save:0, line 950 <- wrt source file 2025-07-17T07:36:47.4808243Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::save:0 2025-07-17T07:36:47.4809391Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/torch_version.py::TorchVersion:0, line 19 <- wrt source file 2025-07-17T07:36:47.4810589Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/torch_version.py::TorchVersion:0 2025-07-17T07:36:47.4811799Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_mode_options:0, line 320 <- wrt source file 2025-07-17T07:36:47.4813071Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_mode_options:0 2025-07-17T07:36:47.4814303Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_options:0, line 357 <- wrt source file 2025-07-17T07:36:47.4817355Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_options:0 2025-07-17T07:36:47.4818638Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::current_accelerator:0, line 113 <- wrt source file 2025-07-17T07:36:47.4822816Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::current_accelerator:0 2025-07-17T07:36:47.4824504Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::device_index:0, line 249 <- wrt source file 2025-07-17T07:36:47.4825795Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::device_index:0 2025-07-17T07:36:47.4827030Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::allow_in_graph:0, line 123 <- wrt source file 2025-07-17T07:36:47.4828275Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::allow_in_graph:0 2025-07-17T07:36:47.4829576Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::substitute_in_graph:0, line 179 <- wrt source file 2025-07-17T07:36:48.1193399Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::substitute_in_graph:0 2025-07-17T07:36:48.1194731Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::wrap_numpy:0, line 406 <- wrt source file 2025-07-17T07:36:48.1196504Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::wrap_numpy:0 2025-07-17T07:36:48.1197976Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_compiling:0, line 438 <- wrt source file 2025-07-17T07:36:48.1199416Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_compiling:0 2025-07-17T07:36:48.1200835Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_dynamo_compiling:0, line 459 <- wrt source file 2025-07-17T07:36:48.1202564Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_dynamo_compiling:0 2025-07-17T07:36:48.1204587Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_exporting:0, line 477 <- wrt source file 2025-07-17T07:36:48.1206357Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_exporting:0 2025-07-17T07:36:48.1207854Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0, line 492 <- wrt source file 2025-07-17T07:36:48.1209434Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0 2025-07-17T07:36:48.1211083Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0, line 507 <- wrt source file 2025-07-17T07:36:48.1212929Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0 2025-07-17T07:36:48.1214690Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/__init__.py::_compile_kernel:0, line 1760 <- wrt source file 2025-07-17T07:36:48.1216218Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/__init__.py::_compile_kernel:0 2025-07-17T07:36:48.1217419Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::save:0, line 357 <- wrt source file 2025-07-17T07:36:48.1218547Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::save:0 2025-07-17T07:36:48.1219665Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::load:0, line 427 <- wrt source file 2025-07-17T07:36:48.1220792Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::load:0 2025-07-17T07:36:48.1221979Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::register_dataclass:0, line 575 <- wrt source file 2025-07-17T07:36:48.1223396Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::register_dataclass:0 2025-07-17T07:36:48.1224696Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::Future.add_done_callback:0, line 197 <- wrt source file 2025-07-17T07:36:48.1226046Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::Future.add_done_callback:0 2025-07-17T07:36:48.1227353Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::Future.set_exception:0, line 261 <- wrt source file 2025-07-17T07:36:48.1228722Z * SKIPPED: 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/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::functionalize:0, line 1505 <- wrt source file 2025-07-17T07:36:48.2768807Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::functionalize:0 2025-07-17T07:36:48.2771630Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::linearize:0, line 1704 <- wrt source file 2025-07-17T07:36:48.2939331Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::linearize:0 2025-07-17T07:36:48.2941931Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/functional_call.py::functional_call:0, line 36 <- wrt source file 2025-07-17T07:36:48.2944631Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/functional_call.py::functional_call:0 2025-07-17T07:36:48.2947155Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/fx_minifier.py::minifier:0, line 194 <- wrt source file 2025-07-17T07:36:48.2949765Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/fx_minifier.py::minifier:0 2025-07-17T07:36:48.2952543Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0, line 1066 <- wrt source file 2025-07-17T07:36:48.2955662Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0 2025-07-17T07:36:48.2958540Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0, line 133 <- wrt source file 2025-07-17T07:36:48.2961378Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0 2025-07-17T07:36:48.2964262Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0, line 269 <- wrt source file 2025-07-17T07:36:48.2967323Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0 2025-07-17T07:36:48.2969913Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/cond.py::cond:0, line 107 <- wrt source file 2025-07-17T07:36:48.2972419Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/cond.py::cond:0 2025-07-17T07:36:48.2974908Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0, line 80 <- wrt source file 2025-07-17T07:36:48.2977644Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0 2025-07-17T07:36:48.2980105Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/map.py::map:0, line 148 <- wrt source file 2025-07-17T07:36:48.2982420Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/map.py::map:0 2025-07-17T07:36:48.2984673Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::scan:0, line 163 <- wrt source file 2025-07-17T07:36:48.2987017Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::scan:0 2025-07-17T07:36:48.2989449Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::ScanAutogradOp:0, line 431 <- wrt source file 2025-07-17T07:36:48.2992130Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::ScanAutogradOp:0 2025-07-17T07:36:48.2994920Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0, line 1457 <- wrt source file 2025-07-17T07:36:48.2997890Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0 2025-07-17T07:36:48.3000827Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0, line 3289 <- wrt source file 2025-07-17T07:36:48.3003636Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0 2025-07-17T07:36:48.3006223Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::custom_op:0, line 98 <- wrt source file 2025-07-17T07:36:48.3524227Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::custom_op:0 2025-07-17T07:36:48.3525877Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0, line 237 <- wrt source file 2025-07-17T07:36:48.3610963Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0 2025-07-17T07:36:48.3612425Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0, line 306 <- wrt source file 2025-07-17T07:36:48.3613867Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0 2025-07-17T07:36:48.3615269Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autograd:0, line 540 <- wrt source file 2025-07-17T07:36:48.3778883Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autograd:0 2025-07-17T07:36:48.3780298Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0, line 708 <- wrt source file 2025-07-17T07:36:48.3944331Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0 2025-07-17T07:36:48.3946000Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autocast:0, line 794 <- wrt source file 2025-07-17T07:36:48.3947637Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autocast:0 2025-07-17T07:36:48.3949051Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0, line 197 <- wrt source file 2025-07-17T07:36:48.3950478Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0 2025-07-17T07:36:48.3951861Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0, line 175 <- wrt source file 2025-07-17T07:36:48.4021238Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0 2025-07-17T07:36:48.4022600Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/infer_schema.py::infer_schema:0, line 51 <- wrt source file 2025-07-17T07:36:48.4027822Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/infer_schema.py::infer_schema:0 2025-07-17T07:36:48.4029056Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_logging/_internal.py::set_logs:0, line 457 <- wrt source file 2025-07-17T07:36:48.4030280Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_logging/_internal.py::set_logs:0 2025-07-17T07:36:48.4031504Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_equal:0, line 171 <- wrt source file 2025-07-17T07:36:48.4066700Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_equal:0 2025-07-17T07:36:48.4067989Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0, line 1008 <- wrt source file 2025-07-17T07:36:48.4117006Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0 2025-07-17T07:36:48.4118572Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0, line 1073 <- wrt source file 2025-07-17T07:36:48.4119953Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0 2025-07-17T07:36:48.4121246Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0, line 1294 <- wrt source file 2025-07-17T07:36:48.4178723Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0 2025-07-17T07:36:48.4180101Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0, line 1360 <- wrt source file 2025-07-17T07:36:48.4182862Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0 2025-07-17T07:36:48.4184248Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0, line 1423 <- wrt source file 2025-07-17T07:36:48.4187424Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0 2025-07-17T07:36:48.4188779Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0, line 1468 <- wrt source file 2025-07-17T07:36:48.4190039Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0 2025-07-17T07:36:48.4191276Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_warns:0, line 1578 <- wrt source file 2025-07-17T07:36:48.4194377Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_warns:0 2025-07-17T07:36:48.4196185Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims/context.py::TorchRefsMode:0, line 95 <- wrt source file 2025-07-17T07:36:48.4197953Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims/context.py::TorchRefsMode:0 2025-07-17T07:36:48.4199422Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/amp/grad_scaler.py::GradScaler:0, line 64 <- wrt source file 2025-07-17T07:36:48.4200841Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/amp/grad_scaler.py::GradScaler:0 2025-07-17T07:36:48.4202182Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0, line 30 <- wrt source file 2025-07-17T07:36:48.4203841Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0 2025-07-17T07:36:48.4205516Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0, line 24 <- wrt source file 2025-07-17T07:36:48.4207238Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0 2025-07-17T07:36:48.4208913Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0, line 25 <- wrt source file 2025-07-17T07:36:48.4210508Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0 2025-07-17T07:36:48.4212094Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0, line 67 <- wrt source file 2025-07-17T07:36:48.4213834Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0 2025-07-17T07:36:48.4215424Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0, line 142 <- wrt source file 2025-07-17T07:36:48.4217006Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0 2025-07-17T07:36:48.4218479Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0, line 30 <- wrt source file 2025-07-17T07:36:48.4295863Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0 2025-07-17T07:36:48.4297356Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0, line 413 <- wrt source file 2025-07-17T07:36:48.4327668Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0 2025-07-17T07:36:48.4329934Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0, line 211 <- wrt source file 2025-07-17T07:36:48.4331882Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0 2025-07-17T07:36:48.4333278Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv2d:0, line 283 <- wrt source file 2025-07-17T07:36:48.4334587Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv2d:0 2025-07-17T07:36:48.4335871Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0, line 359 <- wrt source file 2025-07-17T07:36:48.4337370Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0 2025-07-17T07:36:48.4338819Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0, line 95 <- wrt source file 2025-07-17T07:36:48.4340210Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0 2025-07-17T07:36:48.4341726Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0, line 145 <- wrt source file 2025-07-17T07:36:48.4343889Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0 2025-07-17T07:36:48.4346058Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0, line 43 <- wrt source file 2025-07-17T07:36:48.4348205Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0 2025-07-17T07:36:48.4350265Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0, line 124 <- wrt source file 2025-07-17T07:36:48.4352207Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0 2025-07-17T07:36:48.4353603Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0, line 209 <- wrt source file 2025-07-17T07:36:48.4355352Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0 2025-07-17T07:36:48.4357460Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0, line 296 <- wrt source file 2025-07-17T07:36:48.4359680Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0 2025-07-17T07:36:48.4361425Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0, line 378 <- wrt source file 2025-07-17T07:36:48.4362994Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0 2025-07-17T07:36:48.4364511Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0, line 460 <- wrt source file 2025-07-17T07:36:48.4366136Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0 2025-07-17T07:36:48.4367637Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0, line 30 <- wrt source file 2025-07-17T07:36:48.4369089Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0 2025-07-17T07:36:48.4370648Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0, line 515 <- wrt source file 2025-07-17T07:36:48.4372655Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0 2025-07-17T07:36:48.4375346Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0, line 801 <- wrt source file 2025-07-17T07:36:48.4378090Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0 2025-07-17T07:36:48.4380819Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0, line 1206 <- wrt source file 2025-07-17T07:36:48.4383653Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0 2025-07-17T07:36:48.4386538Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0, line 1273 <- wrt source file 2025-07-17T07:36:48.4389924Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0 2025-07-17T07:36:48.4393257Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0, line 1326 <- wrt source file 2025-07-17T07:36:48.4396411Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0 2025-07-17T07:36:48.4399560Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0, line 36 <- wrt source file 2025-07-17T07:36:48.4402758Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0 2025-07-17T07:36:48.4405794Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0, line 505 <- wrt source file 2025-07-17T07:36:48.4408397Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0 2025-07-17T07:36:48.4410948Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0, line 635 <- wrt source file 2025-07-17T07:36:48.4413650Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0 2025-07-17T07:36:48.4416325Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0, line 892 <- wrt source file 2025-07-17T07:36:48.4419154Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0 2025-07-17T07:36:48.4421946Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0, line 1014 <- wrt source file 2025-07-17T07:36:48.4424797Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0 2025-07-17T07:36:48.4427591Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0, line 1140 <- wrt source file 2025-07-17T07:36:48.4430429Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0 2025-07-17T07:36:48.4433231Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0, line 111 <- wrt source file 2025-07-17T07:36:48.4436158Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0 2025-07-17T07:36:48.4439037Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0, line 275 <- wrt source file 2025-07-17T07:36:48.4442026Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0 2025-07-17T07:36:48.4445046Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0, line 23 <- wrt source file 2025-07-17T07:36:48.4448617Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0 2025-07-17T07:36:48.4451674Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0, line 176 <- wrt source file 2025-07-17T07:36:48.4454762Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0 2025-07-17T07:36:48.4457567Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0, line 138 <- wrt source file 2025-07-17T07:36:48.4460354Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0 2025-07-17T07:36:48.4463424Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0, line 55 <- wrt source file 2025-07-17T07:36:48.4466988Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0 2025-07-17T07:36:48.4470279Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0, line 24 <- wrt source file 2025-07-17T07:36:48.4473174Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0 2025-07-17T07:36:48.4476031Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0, line 47 <- wrt source file 2025-07-17T07:36:48.4479146Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0 2025-07-17T07:36:48.4481936Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0, line 176 <- wrt source file 2025-07-17T07:36:48.4484649Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0 2025-07-17T07:36:48.4487402Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0, line 31 <- wrt source file 2025-07-17T07:36:48.4490297Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0 2025-07-17T07:36:48.4493179Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0, line 76 <- wrt source file 2025-07-17T07:36:48.4496173Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0 2025-07-17T07:36:48.4499096Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0, line 130 <- wrt source file 2025-07-17T07:36:48.4502047Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0 2025-07-17T07:36:48.4505039Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0, line 163 <- wrt source file 2025-07-17T07:36:48.4508162Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0 2025-07-17T07:36:48.4510961Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_args:0, line 110 <- wrt source file 2025-07-17T07:36:48.4513537Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_args:0 2025-07-17T07:36:48.4516178Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0, line 132 <- wrt source file 2025-07-17T07:36:48.4518964Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0 2025-07-17T07:36:48.4521578Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0, line 218 <- wrt source file 2025-07-17T07:36:48.4524227Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0 2025-07-17T07:36:48.4526904Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0, line 288 <- wrt source file 2025-07-17T07:36:48.4529538Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0 2025-07-17T07:36:48.4532253Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0, line 427 <- wrt source file 2025-07-17T07:36:48.4534996Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0 2025-07-17T07:36:48.4537646Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0, line 608 <- wrt source file 2025-07-17T07:36:48.4540287Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0 2025-07-17T07:36:48.4543111Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0, line 668 <- wrt source file 2025-07-17T07:36:48.4546027Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0 2025-07-17T07:36:48.4549042Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0, line 720 <- wrt source file 2025-07-17T07:36:48.4552216Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0 2025-07-17T07:36:48.4555115Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0, line 51 <- wrt source file 2025-07-17T07:36:48.4557877Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0 2025-07-17T07:36:48.4560605Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0, line 130 <- wrt source file 2025-07-17T07:36:48.4563451Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0 2025-07-17T07:36:48.4566220Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0, line 228 <- wrt source file 2025-07-17T07:36:48.4568966Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0 2025-07-17T07:36:48.4571749Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0, line 149 <- wrt source file 2025-07-17T07:36:48.4574427Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0 2025-07-17T07:36:48.4577022Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0, line 521 <- wrt source file 2025-07-17T07:36:48.4579737Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0 2025-07-17T07:36:48.4582415Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0, line 543 <- wrt source file 2025-07-17T07:36:48.4585229Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0 2025-07-17T07:36:48.4587913Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0, line 557 <- wrt source file 2025-07-17T07:36:48.4590604Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0 2025-07-17T07:36:48.4593254Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0, line 579 <- wrt source file 2025-07-17T07:36:48.4595979Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0 2025-07-17T07:36:48.4598558Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0, line 706 <- wrt source file 2025-07-17T07:36:48.4601198Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0 2025-07-17T07:36:48.4604196Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0, line 85 <- wrt source file 2025-07-17T07:36:48.4607404Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0 2025-07-17T07:36:48.4610534Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_get_reduction_params:0, line 102 <- wrt source file 2025-07-17T07:36:48.4613711Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_get_reduction_params:0 2025-07-17T07:36:48.4616791Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_register_custom_op:0, line 148 <- wrt source file 2025-07-17T07:36:48.4619938Z * SKIPPED: 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/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/anomaly_mode.py::detect_anomaly:0, line 28 <- wrt source file 2025-07-17T07:36:48.4637838Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/anomaly_mode.py::detect_anomaly:0 2025-07-17T07:36:48.4640280Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::make_dual:0, line 82 <- wrt source file 2025-07-17T07:36:48.4642664Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::make_dual:0 2025-07-17T07:36:48.4645054Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::unpack_dual:0, line 151 <- wrt source file 2025-07-17T07:36:48.4647618Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::unpack_dual:0 2025-07-17T07:36:48.4650027Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::dual_level:0, line 187 <- wrt source file 2025-07-17T07:36:48.4652432Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::dual_level:0 2025-07-17T07:36:48.4655028Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_backward:0, line 71 <- wrt source file 2025-07-17T07:36:48.4657913Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_backward:0 2025-07-17T07:36:48.4660684Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_forward:0, line 115 <- wrt source file 2025-07-17T07:36:48.4663499Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_forward:0 2025-07-17T07:36:48.4666266Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_dirty:0, line 167 <- wrt source file 2025-07-17T07:36:48.4668961Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_dirty:0 2025-07-17T07:36:48.4671926Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_non_differentiable:0, line 214 <- wrt source file 2025-07-17T07:36:48.4674872Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_non_differentiable:0 2025-07-17T07:36:48.4677759Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.set_materialize_grads:0, line 243 <- wrt source file 2025-07-17T07:36:48.4680684Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.set_materialize_grads:0 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/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::jacobian:0, line 630 <- wrt source file 2025-07-17T07:36:48.4723461Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::jacobian:0 2025-07-17T07:36:48.4726077Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hessian:0, line 894 <- wrt source file 2025-07-17T07:36:48.4728530Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hessian:0 2025-07-17T07:36:48.4730863Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::vhp:0, line 1010 <- wrt source file 2025-07-17T07:36:48.4733427Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::vhp:0 2025-07-17T07:36:48.4735721Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hvp:0, line 1109 <- wrt source file 2025-07-17T07:36:48.4738064Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hvp:0 2025-07-17T07:36:48.4740320Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::no_grad:0, line 50 <- wrt source file 2025-07-17T07:36:48.4742702Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::no_grad:0 2025-07-17T07:36:48.4745068Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::enable_grad:0, line 108 <- wrt source file 2025-07-17T07:36:48.4747479Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::enable_grad:0 2025-07-17T07:36:48.4749919Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::set_grad_enabled:0, line 166 <- wrt source file 2025-07-17T07:36:48.4752575Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::set_grad_enabled:0 2025-07-17T07:36:48.4755077Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::inference_mode:0, line 238 <- wrt source file 2025-07-17T07:36:48.4757575Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::inference_mode:0 2025-07-17T07:36:48.4759922Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.name:0, line 53 <- wrt source file 2025-07-17T07:36:48.4762247Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.name:0 2025-07-17T07:36:48.4764619Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_hook:0, line 110 <- wrt source file 2025-07-17T07:36:48.4767294Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_hook:0 2025-07-17T07:36:48.4769804Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_prehook:0, line 147 <- wrt source file 2025-07-17T07:36:48.4772547Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_prehook:0 2025-07-17T07:36:48.4775039Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::saved_tensors_hooks:0, line 271 <- wrt source file 2025-07-17T07:36:48.4777565Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::saved_tensors_hooks:0 2025-07-17T07:36:48.4779940Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::save_on_cpu:0, line 341 <- wrt source file 2025-07-17T07:36:48.4782290Z * SKIPPED: 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/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::allow_mutation_on_saved_tensors:0 2025-07-17T07:36:48.4800768Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::profile:0, line 182 <- wrt source file 2025-07-17T07:36:48.4803218Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::profile:0 2025-07-17T07:36:48.4805599Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_itt:0, line 880 <- wrt source file 2025-07-17T07:36:48.4808002Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_itt:0 2025-07-17T07:36:48.4810329Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_nvtx:0, line 953 <- wrt source file 2025-07-17T07:36:48.4812813Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_nvtx:0 2025-07-17T07:36:48.4815129Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_register_buffer:0, line 42 <- wrt source file 2025-07-17T07:36:48.4817467Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_register_buffer:0 2025-07-17T07:36:48.4819817Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0, line 58 <- wrt source file 2025-07-17T07:36:48.4822263Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0 2025-07-17T07:36:48.4824496Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::GdsFile:0, line 85 <- wrt source file 2025-07-17T07:36:48.4826641Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::GdsFile:0 2025-07-17T07:36:48.4828887Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0, line 114 <- wrt source file 2025-07-17T07:36:48.4831278Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0 2025-07-17T07:36:48.4833631Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1, line 125 <- wrt source file 2025-07-17T07:36:48.4836000Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1 2025-07-17T07:36:48.4838356Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2, line 140 <- wrt source file 2025-07-17T07:36:48.4840742Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2 2025-07-17T07:36:48.4843247Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0, line 173 <- wrt source file[39;49;00m 2025-07-17T07:36:48.4846004Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0 2025-07-17T07:36:48.4848416Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/profiler.py::profile:0, line 75 <- wrt source file 2025-07-17T07:36:48.4850919Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/profiler.py::profile:0 2025-07-17T07:36:48.4853734Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::DeviceMesh:0, line 424 <- wrt source file 2025-07-17T07:36:48.4856817Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::DeviceMesh:0 2025-07-17T07:36:48.4859489Z * DOCTEST : 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: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0, line 2676 <- wrt source file 2025-07-17T07:36:48.4879322Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0 2025-07-17T07:36:48.4882081Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0, line 3143 <- wrt source file 2025-07-17T07:36:48.4884913Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0 2025-07-17T07:36:48.4887754Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0, line 3372 <- wrt source file 2025-07-17T07:36:48.4890571Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0 2025-07-17T07:36:48.4893325Z * DOCTEST : 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* DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/autograd/__init__.py::context:0, line 47 <- wrt source file 2025-07-17T07:36:48.4962636Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/autograd/__init__.py::context:0 2025-07-17T07:36:48.4965473Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_composable/checkpoint_activation.py::checkpoint:0, line 53 <- wrt source file 2025-07-17T07:36:48.4968520Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_composable/checkpoint_activation.py::checkpoint:0 2025-07-17T07:36:48.4971451Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_composable/contract.py::contract:0, line 66 <- wrt source file 2025-07-17T07:36:48.4974178Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_composable/contract.py::contract:0 2025-07-17T07:36:48.4976887Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_composable/replicate.py::replicate:0, line 190 <- wrt source file 2025-07-17T07:36:48.4979759Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_composable/replicate.py::replicate:0 2025-07-17T07:36:48.4982736Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_optim/__init__.py::named_params_with_sharded_tensor:0, line 31 <- wrt source file 2025-07-17T07:36:48.4986037Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_optim/__init__.py::named_params_with_sharded_tensor:0 2025-07-17T07:36:48.4989194Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py::custom_sharded_op_impl:0, line 457 <- wrt source file 2025-07-17T07:36:48.4992392Z * SKIPPED: 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file 2025-07-17T07:36:48.5009678Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/join.py::Join:0 2025-07-17T07:36:48.5012524Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/__init__.py::register_ddp_comm_hook:0, line 107 <- wrt source file 2025-07-17T07:36:48.5015823Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/__init__.py::register_ddp_comm_hook:0 2025-07-17T07:36:48.5018999Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/debugging_hooks.py::noop_hook:0, line 23 <- wrt source file 2025-07-17T07:36:48.5022206Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/debugging_hooks.py::noop_hook:0 2025-07-17T07:36:48.5025375Z * DOCTEST : 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line 54 <- wrt source file 2025-07-17T07:36:48.5197314Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/sharded_grad_scaler.py::ShardedGradScaler:0 2025-07-17T07:36:48.5200564Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/wrap.py::CustomPolicy:0, line 224 <- wrt source file 2025-07-17T07:36:48.5203482Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/wrap.py::CustomPolicy:0 2025-07-17T07:36:48.5206510Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/functional.py::_all_gather_base:0, line 134 <- wrt source file 2025-07-17T07:36:48.5209598Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/functional.py::_all_gather_base:0 2025-07-17T07:36:48.5213022Z * DOCTEST : 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wrt source file 2025-07-17T07:36:48.5333760Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py::SequenceParallel:0 2025-07-17T07:36:48.5336462Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/bernoulli.py::Bernoulli:0, line 30 <- wrt source file 2025-07-17T07:36:48.5339015Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/bernoulli.py::Bernoulli:0 2025-07-17T07:36:48.5341385Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/beta.py::Beta:0, line 21 <- wrt source file 2025-07-17T07:36:48.5343694Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/beta.py::Beta:0 2025-07-17T07:36:48.5346075Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/binomial.py::Binomial:0, line 31 <- wrt source file 2025-07-17T07:36:48.5348554Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/binomial.py::Binomial:0 2025-07-17T07:36:48.5351103Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/categorical.py::Categorical:0, line 42 <- wrt source file 2025-07-17T07:36:48.5353857Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/categorical.py::Categorical:0 2025-07-17T07:36:48.5356322Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/cauchy.py::Cauchy:0, line 23 <- wrt source file 2025-07-17T07:36:48.5358724Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/cauchy.py::Cauchy:0 2025-07-17T07:36:48.5361019Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/chi2.py::Chi2:0, line 18 <- wrt source file 2025-07-17T07:36:48.5363333Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/chi2.py::Chi2:0 2025-07-17T07:36:48.5365859Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::is_dependent:0, line 166 <- wrt source file 2025-07-17T07:36:48.5368539Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::is_dependent:0 2025-07-17T07:36:48.5371376Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::_DependentProperty:0, line 187 <- wrt source file 2025-07-17T07:36:48.5374312Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::_DependentProperty:0 2025-07-17T07:36:48.5377219Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0, line 35 <- wrt source file 2025-07-17T07:36:48.5380284Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0 2025-07-17T07:36:48.5383041Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/dirichlet.py::Dirichlet:0, line 42 <- wrt source file 2025-07-17T07:36:48.5385625Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/dirichlet.py::Dirichlet:0 2025-07-17T07:36:48.5388198Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/exponential.py::Exponential:0, line 20 <- wrt source file 2025-07-17T07:36:48.5390867Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/exponential.py::Exponential:0 2025-07-17T07:36:48.5393684Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0, line 21 <- wrt source file 2025-07-17T07:36:48.5396499Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0 2025-07-17T07:36:48.5399000Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gamma.py::Gamma:0, line 24 <- wrt source file 2025-07-17T07:36:48.5401359Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gamma.py::Gamma:0 2025-07-17T07:36:48.5404006Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0, line 26 <- wrt source file 2025-07-17T07:36:48.5407008Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0 2025-07-17T07:36:48.5409722Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/geometric.py::Geometric:0, line 36 <- wrt source file 2025-07-17T07:36:48.5412272Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/geometric.py::Geometric:0 2025-07-17T07:36:48.5414687Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gumbel.py::Gumbel:0, line 23 <- wrt source file 2025-07-17T07:36:48.5417085Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gumbel.py::Gumbel:0 2025-07-17T07:36:48.5419506Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0, line 24 <- wrt source file 2025-07-17T07:36:48.5422109Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0 2025-07-17T07:36:48.5424653Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_normal.py::HalfNormal:0, line 24 <- wrt source file 2025-07-17T07:36:48.5427256Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_normal.py::HalfNormal:0 2025-07-17T07:36:48.5429846Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/independent.py::Independent:0, line 27 <- wrt source file 2025-07-17T07:36:48.5432507Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/independent.py::Independent:0 2025-07-17T07:36:48.5435141Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0, line 24 <- wrt source file 2025-07-17T07:36:48.5437919Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0 2025-07-17T07:36:48.5440554Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0, line 30 <- wrt source file 2025-07-17T07:36:48.5443222Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0 2025-07-17T07:36:48.5445816Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/laplace.py::Laplace:0, line 20 <- wrt source file 2025-07-17T07:36:48.5448269Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/laplace.py::Laplace:0 2025-07-17T07:36:48.5450755Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0, line 43 <- wrt source file 2025-07-17T07:36:48.5453431Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0 2025-07-17T07:36:48.5456076Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/log_normal.py::LogNormal:0, line 23 <- wrt source file 2025-07-17T07:36:48.5458637Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/log_normal.py::LogNormal:0 2025-07-17T07:36:48.5461288Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0, line 28 <- wrt source file 2025-07-17T07:36:48.5464084Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0 2025-07-17T07:36:48.5466766Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multinomial.py::Multinomial:0, line 38 <- wrt source file 2025-07-17T07:36:48.5469431Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multinomial.py::Multinomial:0 2025-07-17T07:36:48.5472359Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0, line 103 <- wrt source file 2025-07-17T07:36:48.5475375Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0 2025-07-17T07:36:48.5478023Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/normal.py::Normal:0, line 22 <- wrt source file 2025-07-17T07:36:48.5480415Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/normal.py::Normal:0 2025-07-17T07:36:48.5483056Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0, line 34 <- wrt source file 2025-07-17T07:36:48.5486058Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0 2025-07-17T07:36:48.5488661Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/pareto.py::Pareto:0, line 20 <- wrt source file 2025-07-17T07:36:48.5491074Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/pareto.py::Pareto:0 2025-07-17T07:36:48.5493470Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/poisson.py::Poisson:0, line 25 <- wrt source file 2025-07-17T07:36:48.5495913Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/poisson.py::Poisson:0 2025-07-17T07:36:48.5498456Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/studentT.py::StudentT:0, line 22 <- wrt source file 2025-07-17T07:36:48.5500943Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/studentT.py::StudentT:0 2025-07-17T07:36:48.5503515Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::CatTransform:0, line 1065 <- wrt source file 2025-07-17T07:36:48.5506197Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::CatTransform:0 2025-07-17T07:36:48.5508912Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::StackTransform:0, line 1177 <- wrt source file 2025-07-17T07:36:48.5511659Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::StackTransform:0 2025-07-17T07:36:48.5514585Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::CumulativeDistributionTransform:0, line 1253 <- wrt source file 2025-07-17T07:36:48.5517870Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::CumulativeDistributionTransform:0 2025-07-17T07:36:48.5520593Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/uniform.py::Uniform:0, line 21 <- wrt source file 2025-07-17T07:36:48.5523029Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/uniform.py::Uniform:0 2025-07-17T07:36:48.5525504Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/utils.py::clamp_probs:0, line 114 <- wrt source file 2025-07-17T07:36:48.5527983Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/utils.py::clamp_probs:0 2025-07-17T07:36:48.5530421Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/von_mises.py::VonMises:0, line 117 <- wrt source file 2025-07-17T07:36:48.5532913Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/von_mises.py::VonMises:0 2025-07-17T07:36:48.5535331Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/weibull.py::Weibull:0, line 22 <- wrt source file 2025-07-17T07:36:48.5537764Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/weibull.py::Weibull:0 2025-07-17T07:36:48.5540164Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/wishart.py::Wishart:0, line 39 <- wrt source file 2025-07-17T07:36:48.5542587Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/wishart.py::Wishart:0 2025-07-17T07:36:48.5544933Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::Dim:0, line 103 <- wrt source file 2025-07-17T07:36:48.5547287Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::Dim:0 2025-07-17T07:36:48.5549760Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:0, line 715 <- wrt source file 2025-07-17T07:36:48.5552413Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:0 2025-07-17T07:36:48.5555034Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:1, line 731 <- wrt source file 2025-07-17T07:36:48.5557695Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:1 2025-07-17T07:36:48.5560409Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::AdditionalInputs:0, line 815 <- wrt source file 2025-07-17T07:36:48.5563079Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::AdditionalInputs:0 2025-07-17T07:36:48.5565485Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::_snake_case:0, line 102 <- wrt source file 2025-07-17T07:36:48.5567702Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::_snake_case:0 2025-07-17T07:36:48.5570264Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::Graph.eliminate_dead_code:0, line 1762 <- wrt source file 2025-07-17T07:36:48.5572811Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::Graph.eliminate_dead_code:0 2025-07-17T07:36:48.5575251Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::Graph.on_generate_code:0, line 1856 <- wrt source file 2025-07-17T07:36:48.5577679Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::Graph.on_generate_code:0 2025-07-17T07:36:48.5580187Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/interpreter.py::Interpreter:0, line 48 <- wrt source file 2025-07-17T07:36:48.5582564Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/interpreter.py::Interpreter:0 2025-07-17T07:36:48.5584888Z * DOCTEST : 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file 2025-07-17T07:36:48.5846661Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/shape_prop.py::ShapeProp:0 2025-07-17T07:36:48.5849474Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/split_module.py::split_module:0, line 89 <- wrt source file 2025-07-17T07:36:48.5852502Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/split_module.py::split_module:0 2025-07-17T07:36:48.5855988Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/utils/matcher_with_name_node_map_utils.py::SubgraphMatcherWithNameNodeMap:0, line 51 <- wrt source file 2025-07-17T07:36:48.5860040Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/utils/matcher_with_name_node_map_utils.py::SubgraphMatcherWithNameNodeMap:0 2025-07-17T07:36:48.5863548Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/_check.py::AttributeTypeIsSupportedChecker:0, 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/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool2d_with_indices:0, line 464 <- wrt source file 2025-07-17T07:36:48.5903426Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool2d_with_indices:0 2025-07-17T07:36:48.5906621Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool3d_with_indices:0, line 583 <- wrt source file 2025-07-17T07:36:48.6448942Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool3d_with_indices:0 2025-07-17T07:36:48.6468423Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::gumbel_softmax:0, line 2178 <- wrt source file 2025-07-17T07:36:48.6478264Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::gumbel_softmax:0 2025-07-17T07:36:48.6481000Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding:0, line 2482 <- wrt source file 2025-07-17T07:36:48.6487400Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding:0 2025-07-17T07:36:48.6489909Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding_bag:0, line 2622 <- wrt source file 2025-07-17T07:36:48.6525979Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding_bag:0 2025-07-17T07:36:48.6528273Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::ctc_loss:0, line 3055 <- wrt source file 2025-07-17T07:36:48.6556923Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::ctc_loss:0 2025-07-17T07:36:48.6559332Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::nll_loss:0, line 3125 <- wrt source file 2025-07-17T07:36:48.6596431Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::nll_loss:0 2025-07-17T07:36:48.6599101Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::cross_entropy:0, line 3434 <- wrt source file 2025-07-17T07:36:48.6621248Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::cross_entropy:0 2025-07-17T07:36:48.6624089Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy:0, line 3499 <- wrt source file 2025-07-17T07:36:48.6650158Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy:0 2025-07-17T07:36:48.6652795Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0, line 3569 <- wrt source file 2025-07-17T07:36:48.6664642Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0 2025-07-17T07:36:48.6667514Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::pad:0, line 5267 <- wrt source file 2025-07-17T07:36:48.6675003Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::pad:0 2025-07-17T07:36:48.6677160Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_input:0, line 32 <- wrt source file 2025-07-17T07:36:48.6742627Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_input:0 2025-07-17T07:36:48.6744817Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_weight:0, line 79 <- wrt source file 2025-07-17T07:36:48.6747758Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_weight:0 2025-07-17T07:36:48.6749937Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_input:0, line 130 <- wrt source file 2025-07-17T07:36:48.6763401Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_input:0 2025-07-17T07:36:48.6765618Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_weight:0, line 177 <- wrt source file 2025-07-17T07:36:48.6768170Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_weight:0 2025-07-17T07:36:48.6770483Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_input:0, line 228 <- wrt source file 2025-07-17T07:36:48.7190684Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_input:0 2025-07-17T07:36:48.7193400Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_weight:0, line 275 <- wrt source file 2025-07-17T07:36:48.7234045Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_weight:0 2025-07-17T07:36:48.7236564Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::uniform_:0, line 230 <- wrt source file 2025-07-17T07:36:48.7238853Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::uniform_:0 2025-07-17T07:36:48.7240947Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::normal_:0, line 257 <- wrt source file 2025-07-17T07:36:48.7243059Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::normal_:0 2025-07-17T07:36:48.7245210Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::trunc_normal_:0, line 292 <- wrt source file 2025-07-17T07:36:48.7264747Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::trunc_normal_:0 2025-07-17T07:36:48.7266923Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::constant_:0, line 306 <- wrt source file 2025-07-17T07:36:48.7269157Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::constant_:0 2025-07-17T07:36:48.7271366Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::ones_:0, line 323 <- wrt source file 2025-07-17T07:36:48.7274104Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::ones_:0 2025-07-17T07:36:48.7276182Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::zeros_:0, line 336 <- wrt source file 2025-07-17T07:36:48.7278280Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::zeros_:0 2025-07-17T07:36:48.7280308Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::eye_:0, line 352 <- wrt source file 2025-07-17T07:36:48.7282378Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::eye_:0 2025-07-17T07:36:48.7284408Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::dirac_:0, line 374 <- wrt source file 2025-07-17T07:36:48.7286560Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::dirac_:0 2025-07-17T07:36:48.7288712Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_uniform_:0, line 460 <- wrt source file 2025-07-17T07:36:48.7290981Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_uniform_:0 2025-07-17T07:36:48.7293554Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_normal_:0, line 492 <- wrt source file 2025-07-17T07:36:48.7295816Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_normal_:0 2025-07-17T07:36:48.7298019Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_uniform_:0, line 543 <- wrt source file 2025-07-17T07:36:48.7300304Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_uniform_:0 2025-07-17T07:36:48.7302619Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_normal_:0, line 608 <- wrt source file 2025-07-17T07:36:48.7304878Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_normal_:0 2025-07-17T07:36:48.7307058Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::orthogonal_:0, line 647 <- wrt source file 2025-07-17T07:36:48.7309255Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::orthogonal_:0 2025-07-17T07:36:48.7311510Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::sparse_:0, line 700 <- wrt source file 2025-07-17T07:36:48.7313651Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::sparse_:0 2025-07-17T07:36:48.7315906Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0, line 119 <- wrt source file 2025-07-17T07:36:48.7318390Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0 2025-07-17T07:36:48.7320797Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/bias.py::CausalBias:0, line 95 <- wrt source file 2025-07-17T07:36:48.7323188Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/bias.py::CausalBias:0 2025-07-17T07:36:48.7325675Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Threshold:0, line 72 <- wrt source file 2025-07-17T07:36:48.7328146Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Threshold:0 2025-07-17T07:36:48.7330531Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU:0, line 114 <- wrt source file 2025-07-17T07:36:48.7332947Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU:0 2025-07-17T07:36:48.7335286Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::RReLU:0, line 173 <- wrt source file 2025-07-17T07:36:48.7337686Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::RReLU:0 2025-07-17T07:36:48.7340065Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardtanh:0, line 229 <- wrt source file 2025-07-17T07:36:48.7342523Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardtanh:0 2025-07-17T07:36:48.7344877Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU6:0, line 294 <- wrt source file 2025-07-17T07:36:48.7347274Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU6:0 2025-07-17T07:36:48.7349613Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Sigmoid:0, line 322 <- wrt source file 2025-07-17T07:36:48.7352106Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Sigmoid:0 2025-07-17T07:36:48.7354545Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0, line 354 <- wrt source file 2025-07-17T07:36:48.7357081Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0 2025-07-17T07:36:48.7359467Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanh:0, line 387 <- wrt source file 2025-07-17T07:36:48.7361883Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanh:0 2025-07-17T07:36:48.7364216Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SiLU:0, line 420 <- wrt source file 2025-07-17T07:36:48.7374085Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SiLU:0 2025-07-17T07:36:48.7376411Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Mish:0, line 459 <- wrt source file 2025-07-17T07:36:48.7379412Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Mish:0 2025-07-17T07:36:48.7381826Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardswish:0, line 504 <- wrt source file 2025-07-17T07:36:48.7391766Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardswish:0 2025-07-17T07:36:48.7394180Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ELU:0, line 547 <- wrt source file 2025-07-17T07:36:48.7396590Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ELU:0 2025-07-17T07:36:48.7398912Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::CELU:0, line 589 <- wrt source file 2025-07-17T07:36:48.7401323Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::CELU:0 2025-07-17T07:36:48.7403670Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SELU:0, line 642 <- wrt source file 2025-07-17T07:36:48.7406145Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SELU:0 2025-07-17T07:36:48.7408459Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GLU:0, line 682 <- wrt source file 2025-07-17T07:36:48.7419597Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GLU:0 2025-07-17T07:36:48.7421948Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GELU:0, line 724 <- wrt source file 2025-07-17T07:36:48.7486624Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GELU:0 2025-07-17T07:36:48.7489036Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardshrink:0, line 767 <- wrt source file 2025-07-17T07:36:48.7502566Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardshrink:0 2025-07-17T07:36:48.7505036Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LeakyReLU:0, line 816 <- wrt source file 2025-07-17T07:36:48.7507527Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LeakyReLU:0 2025-07-17T07:36:48.7510326Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSigmoid:0, line 852 <- wrt source file 2025-07-17T07:36:48.7513236Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSigmoid:0 2025-07-17T07:36:48.7516116Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softplus:0, line 885 <- wrt source file 2025-07-17T07:36:48.7518578Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softplus:0 2025-07-17T07:36:48.7521065Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softshrink:0, line 928 <- wrt source file 2025-07-17T07:36:48.7523578Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softshrink:0 2025-07-17T07:36:48.7526216Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0, line 1036 <- wrt source file 2025-07-17T07:36:48.7529068Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0 2025-07-17T07:36:48.7531587Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::PReLU:0, line 1501 <- wrt source file 2025-07-17T07:36:48.7534020Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::PReLU:0 2025-07-17T07:36:48.7536407Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softsign:0, line 1543 <- wrt source file 2025-07-17T07:36:48.7538861Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softsign:0 2025-07-17T07:36:48.7541703Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanhshrink:0, line 1566 <- wrt source file 2025-07-17T07:36:48.7544628Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanhshrink:0 2025-07-17T07:36:48.7547440Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmin:0, line 1601 <- wrt source file 2025-07-17T07:36:48.7550234Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmin:0 2025-07-17T07:36:48.7553026Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax:0, line 1659 <- wrt source file 2025-07-17T07:36:48.7555857Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax:0 2025-07-17T07:36:48.7558675Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax2d:0, line 1700 <- wrt source file 2025-07-17T07:36:48.7561531Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax2d:0 2025-07-17T07:36:48.7563987Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSoftmax:0, line 1736 <- wrt source file 2025-07-17T07:36:48.7566600Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSoftmax:0 2025-07-17T07:36:48.7569077Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0, line 330 <- wrt source file 2025-07-17T07:36:48.7594122Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0 2025-07-17T07:36:48.7596783Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0, line 441 <- wrt source file 2025-07-17T07:36:48.7798291Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0 2025-07-17T07:36:48.7801192Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0, line 552 <- wrt source file 2025-07-17T07:36:49.0244283Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0 2025-07-17T07:36:49.0375769Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0, line 21 <- wrt source file 2025-07-17T07:36:49.0397604Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0 2025-07-17T07:36:49.0400171Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential:0, line 81 <- wrt source file 2025-07-17T07:36:49.0402658Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential:0 2025-07-17T07:36:49.0405468Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.append:0, line 254 <- wrt source file 2025-07-17T07:36:49.0408540Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.append:0 2025-07-17T07:36:49.0411141Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.insert:0, line 277 <- wrt source file 2025-07-17T07:36:49.0419590Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.insert:0 2025-07-17T07:36:49.0422192Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.extend:0, line 308 <- wrt source file 2025-07-17T07:36:49.0428102Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.extend:0 2025-07-17T07:36:49.0430626Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleList:0, line 337 <- wrt source file 2025-07-17T07:36:49.0433101Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleList:0 2025-07-17T07:36:49.0435548Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleDict:0, line 517 <- wrt source file 2025-07-17T07:36:49.0438020Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleDict:0 2025-07-17T07:36:49.0440498Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterList:0, line 647 <- wrt source file 2025-07-17T07:36:49.0443060Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterList:0 2025-07-17T07:36:49.0445637Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterDict:0, line 799 <- wrt source file 2025-07-17T07:36:49.0448206Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterDict:0 2025-07-17T07:36:49.0450747Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0, line 38 <- wrt source file 2025-07-17T07:36:49.0453365Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0 2025-07-17T07:36:49.0456043Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0, line 78 <- wrt source file 2025-07-17T07:36:49.0458633Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0 2025-07-17T07:36:49.0461053Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout:0, line 60 <- wrt source file 2025-07-17T07:36:49.0463423Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout:0 2025-07-17T07:36:49.0465814Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout1d:0, line 105 <- wrt source file 2025-07-17T07:36:49.0468231Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout1d:0 2025-07-17T07:36:49.0470753Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout2d:0, line 157 <- wrt source file 2025-07-17T07:36:49.0482730Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout2d:0 2025-07-17T07:36:49.0485694Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout3d:0, line 202 <- wrt source file 2025-07-17T07:36:49.0556596Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout3d:0 2025-07-17T07:36:49.0559156Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0, line 245 <- wrt source file 2025-07-17T07:36:49.0562689Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0 2025-07-17T07:36:49.0565615Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0, line 294 <- wrt source file 2025-07-17T07:36:49.0635937Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0 2025-07-17T07:36:49.0638556Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py::Flatten:0, line 30 <- wrt source file 2025-07-17T07:36:49.0644463Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py::Flatten:0 2025-07-17T07:36:49.0646642Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Fold:0, line 224 <- wrt source file 2025-07-17T07:36:49.0651732Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Fold:0 2025-07-17T07:36:49.0653954Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Unfold:0, line 389 <- wrt source file 2025-07-17T07:36:49.0689431Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Unfold:0 2025-07-17T07:36:49.0691960Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0, line 187 <- wrt source file 2025-07-17T07:36:49.0702557Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0 2025-07-17T07:36:49.0705303Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0, line 303 <- wrt source file 2025-07-17T07:36:49.0882331Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0 2025-07-17T07:36:49.0885489Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0, line 419 <- wrt source file 2025-07-17T07:36:49.3266327Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0 2025-07-17T07:36:49.3398894Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0, line 77 <- wrt source file 2025-07-17T07:36:49.3402649Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0 2025-07-17T07:36:49.3405014Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Identity:0, line 34 <- wrt source file 2025-07-17T07:36:49.3408795Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Identity:0 2025-07-17T07:36:49.3411090Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Linear:0, line 80 <- wrt source file 2025-07-17T07:36:49.3435473Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Linear:0 2025-07-17T07:36:49.3438086Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Bilinear:0, line 179 <- wrt source file 2025-07-17T07:36:49.3457117Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Bilinear:0 2025-07-17T07:36:49.3459421Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::L1Loss:0, line 115 <- wrt source file 2025-07-17T07:36:49.3465132Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::L1Loss:0 2025-07-17T07:36:49.3467411Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::NLLLoss:0, line 212 <- wrt source file 2025-07-17T07:36:49.3493765Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::NLLLoss:0 2025-07-17T07:36:49.3496425Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0, line 323 <- wrt source file 2025-07-17T07:36:49.3501724Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0 2025-07-17T07:36:49.3504197Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0, line 409 <- wrt source file 2025-07-17T07:36:49.3517394Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0 2025-07-17T07:36:49.3519770Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::KLDivLoss:0, line 523 <- wrt source file 2025-07-17T07:36:49.3526415Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::KLDivLoss:0 2025-07-17T07:36:49.3529076Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MSELoss:0, line 602 <- wrt source file 2025-07-17T07:36:49.3533688Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MSELoss:0 2025-07-17T07:36:49.3535961Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCELoss:0, line 685 <- wrt source file 2025-07-17T07:36:49.3541519Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCELoss:0 2025-07-17T07:36:49.3543949Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0, line 757 <- wrt source file 2025-07-17T07:36:49.3554230Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0 2025-07-17T07:36:49.3557134Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1, line 805 <- wrt source file 2025-07-17T07:36:49.3560573Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1 2025-07-17T07:36:49.3563554Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0, line 951 <- wrt source file 2025-07-17T07:36:49.3569834Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0 2025-07-17T07:36:49.3572616Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0, line 1277 <- wrt source file 2025-07-17T07:36:49.3579334Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0 2025-07-17T07:36:49.3582289Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0, line 1419 <- wrt source file 2025-07-17T07:36:49.3597616Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0 2025-07-17T07:36:49.3600178Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0, line 1485 <- wrt source file 2025-07-17T07:36:49.3605007Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0 2025-07-17T07:36:49.3607579Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0, line 1565 <- wrt source file 2025-07-17T07:36:49.3613347Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0 2025-07-17T07:36:49.3615854Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0, line 1666 <- wrt source file 2025-07-17T07:36:49.3625393Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0 2025-07-17T07:36:49.3627984Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.register_buffer:0, line 551 <- wrt source file 2025-07-17T07:36:49.3630682Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.register_buffer:0 2025-07-17T07:36:49.3633221Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.apply:0, line 1037 <- wrt source file 2025-07-17T07:36:49.3641758Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.apply:0 2025-07-17T07:36:49.3644163Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.to:0, line 1288 <- wrt source file 2025-07-17T07:36:49.3648943Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.to:0 2025-07-17T07:36:49.3651388Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.state_dict:0, line 2224 <- wrt source file 2025-07-17T07:36:49.3653986Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.state_dict:0 2025-07-17T07:36:49.3656540Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.parameters:0, line 2665 <- wrt source file 2025-07-17T07:36:49.3659141Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.parameters:0 2025-07-17T07:36:49.3661893Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_parameters:0, line 2693 <- wrt source file 2025-07-17T07:36:49.3664639Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_parameters:0 2025-07-17T07:36:49.3667216Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.buffers:0, line 2720 <- wrt source file 2025-07-17T07:36:49.3669813Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.buffers:0 2025-07-17T07:36:49.3672537Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_buffers:0, line 2747 <- wrt source file 2025-07-17T07:36:49.3675188Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_buffers:0 2025-07-17T07:36:49.3677809Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_children:0, line 2778 <- wrt source file 2025-07-17T07:36:49.3680605Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_children:0 2025-07-17T07:36:49.3683076Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.modules:0, line 2802 <- wrt source file 2025-07-17T07:36:49.3685673Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.modules:0 2025-07-17T07:36:49.3688732Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_modules:0, line 2840 <- wrt source file 2025-07-17T07:36:49.3691866Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_modules:0 2025-07-17T07:36:49.3695485Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0, line 38 <- wrt source file 2025-07-17T07:36:49.3708151Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0 2025-07-17T07:36:49.3711310Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LayerNorm:0, line 151 <- wrt source file 2025-07-17T07:36:49.3738681Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LayerNorm:0 2025-07-17T07:36:49.3741452Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::GroupNorm:0, line 262 <- wrt source file 2025-07-17T07:36:49.3763440Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::GroupNorm:0 2025-07-17T07:36:49.3765765Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::RMSNorm:0, line 355 <- wrt source file 2025-07-17T07:36:49.3769745Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::RMSNorm:0 2025-07-17T07:36:49.3772104Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad1d:0, line 70 <- wrt source file 2025-07-17T07:36:49.3778273Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad1d:0 2025-07-17T07:36:49.3780530Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad2d:0, line 122 <- wrt source file 2025-07-17T07:36:49.3800914Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad2d:0 2025-07-17T07:36:49.3803174Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad3d:0, line 187 <- wrt source file 2025-07-17T07:36:49.9967434Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad3d:0 2025-07-17T07:36:50.0200296Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0, line 241 <- wrt source file 2025-07-17T07:36:50.0210000Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0 2025-07-17T07:36:50.0212502Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0, line 294 <- wrt source file 2025-07-17T07:36:50.0217005Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0 2025-07-17T07:36:50.0219508Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0, line 350 <- wrt source file 2025-07-17T07:36:50.0240836Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0 2025-07-17T07:36:50.0243382Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0, line 395 <- wrt source file 2025-07-17T07:36:50.0256943Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0 2025-07-17T07:36:50.0259499Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0, line 439 <- wrt source file 2025-07-17T07:36:50.0273125Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0 2025-07-17T07:36:50.0275690Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0, line 497 <- wrt source file 2025-07-17T07:36:50.0286153Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0 2025-07-17T07:36:50.0288687Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0, line 556 <- wrt source file 2025-07-17T07:36:50.0292763Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0 2025-07-17T07:36:50.0295366Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0, line 600 <- wrt source file 2025-07-17T07:36:50.0308586Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0 2025-07-17T07:36:50.0311126Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0, line 658 <- wrt source file 2025-07-17T07:36:50.5275200Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0 2025-07-17T07:36:50.5511351Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0, line 692 <- wrt source file 2025-07-17T07:36:50.5522211Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0 2025-07-17T07:36:50.5524406Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0, line 747 <- wrt source file 2025-07-17T07:36:50.5530441Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0 2025-07-17T07:36:50.5532641Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0, line 806 <- wrt source file 2025-07-17T07:36:50.5555420Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0 2025-07-17T07:36:50.5557960Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0, line 40 <- wrt source file 2025-07-17T07:36:50.5561055Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0 2025-07-17T07:36:50.5563688Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0, line 93 <- wrt source file 2025-07-17T07:36:50.5573795Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0 2025-07-17T07:36:50.5576320Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0, line 129 <- wrt source file 2025-07-17T07:36:50.5587037Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0 2025-07-17T07:36:50.5589441Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0, line 206 <- wrt source file 2025-07-17T07:36:50.5646525Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0 2025-07-17T07:36:50.5648946Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0, line 289 <- wrt source file 2025-07-17T07:36:50.7890688Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0 2025-07-17T07:36:50.7937015Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0, line 363 <- wrt source file 2025-07-17T07:36:50.7948562Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0 2025-07-17T07:36:50.7950992Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0, line 545 <- wrt source file 2025-07-17T07:36:50.8742601Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0 2025-07-17T07:36:50.8745087Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0, line 636 <- wrt source file 2025-07-17T07:36:50.8764469Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0 2025-07-17T07:36:50.8766950Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0, line 731 <- wrt source file 2025-07-17T07:36:50.8805018Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0 2025-07-17T07:36:50.8807503Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0, line 847 <- wrt source file 2025-07-17T07:36:51.0434446Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0 2025-07-17T07:36:51.0482466Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0, line 937 <- wrt source file 2025-07-17T07:36:51.0530003Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0 2025-07-17T07:36:51.0532979Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0, line 1024 <- wrt source file 2025-07-17T07:36:51.1247123Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0 2025-07-17T07:36:51.1249670Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool1d:0, line 1143 <- wrt source file 2025-07-17T07:36:51.1256451Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool1d:0 2025-07-17T07:36:51.1259344Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool2d:0, line 1194 <- wrt source file 2025-07-17T07:36:51.1311001Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool2d:0 2025-07-17T07:36:51.1313991Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool3d:0, line 1253 <- wrt source file 2025-07-17T07:36:51.3432716Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool3d:0 2025-07-17T07:36:51.3478814Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0, line 1308 <- wrt source file 2025-07-17T07:36:51.3498019Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0 2025-07-17T07:36:51.3500426Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0, line 1342 <- wrt source file 2025-07-17T07:36:51.3509461Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0 2025-07-17T07:36:51.3512359Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0, line 1385 <- wrt source file 2025-07-17T07:36:51.3591736Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0 2025-07-17T07:36:51.3594372Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0, line 1432 <- wrt source file 2025-07-17T07:36:51.3605677Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0 2025-07-17T07:36:51.3608311Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0, line 1463 <- wrt source file 2025-07-17T07:36:51.3613271Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0 2025-07-17T07:36:51.3615945Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0, line 1502 <- wrt source file 2025-07-17T07:36:51.3633605Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0 2025-07-17T07:36:51.3635961Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNN:0, line 595 <- wrt source file 2025-07-17T07:36:51.3646509Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNN:0 2025-07-17T07:36:51.3648714Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTM:0, line 950 <- wrt source file 2025-07-17T07:36:51.4098700Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTM:0 2025-07-17T07:36:51.4101670Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRU:0, line 1285 <- wrt source file 2025-07-17T07:36:51.4115095Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRU:0 2025-07-17T07:36:51.4117359Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNNCell:0, line 1534 <- wrt source file 2025-07-17T07:36:51.4127881Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNNCell:0 2025-07-17T07:36:51.4130312Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTMCell:0, line 1656 <- wrt source file 2025-07-17T07:36:51.4139813Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTMCell:0 2025-07-17T07:36:51.4142092Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRUCell:0, line 1770 <- wrt source file 2025-07-17T07:36:51.4154001Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRUCell:0 2025-07-17T07:36:51.4157200Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding:0, line 71 <- wrt source file 2025-07-17T07:36:51.4169157Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding:0 2025-07-17T07:36:51.4171667Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0, line 243 <- wrt source file 2025-07-17T07:36:51.4175777Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0 2025-07-17T07:36:51.4178388Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0, line 521 <- wrt source file 2025-07-17T07:36:51.4184446Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0 2025-07-17T07:36:51.4187131Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::Transformer:0, line 90 <- wrt source file 2025-07-17T07:36:52.2293942Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::Transformer:0 2025-07-17T07:36:52.2310227Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0, line 336 <- wrt source file 2025-07-17T07:36:52.3403246Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0 2025-07-17T07:36:52.3408298Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0, line 562 <- wrt source file 2025-07-17T07:36:52.5777526Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0 2025-07-17T07:36:52.5809228Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0, line 686 <- wrt source file 2025-07-17T07:36:52.6096367Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0 2025-07-17T07:36:52.6099285Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0, line 995 <- wrt source file 2025-07-17T07:36:52.6632383Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0 2025-07-17T07:36:52.6635182Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::Upsample:0, line 77 <- wrt source file 2025-07-17T07:36:52.6688354Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::Upsample:0 2025-07-17T07:36:52.6691036Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0, line 223 <- wrt source file 2025-07-17T07:36:52.6701617Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0 2025-07-17T07:36:52.6704629Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0, line 273 <- wrt source file 2025-07-17T07:36:52.6711004Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0 2025-07-17T07:36:52.6713713Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0, line 127 <- wrt source file 2025-07-17T07:36:52.6726700Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0 2025-07-17T07:36:52.6729511Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0, line 642 <- wrt source file 2025-07-17T07:36:52.6732448Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0 2025-07-17T07:36:52.6735433Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0, line 1446 <- wrt source file 2025-07-17T07:36:52.6738544Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0 2025-07-17T07:36:52.6741719Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0, line 1999 <- wrt source file 2025-07-17T07:36:52.6745062Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0 2025-07-17T07:36:52.6748342Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1, line 2009 <- wrt source file 2025-07-17T07:36:52.6751713Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1 2025-07-17T07:36:52.6755089Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0, line 2044 <- wrt source file 2025-07-17T07:36:52.6758563Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0 2025-07-17T07:36:52.6761610Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0, line 35 <- wrt source file 2025-07-17T07:36:52.6764421Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0 2025-07-17T07:36:52.6767031Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/init.py::skip_init:0, line 33 <- wrt source file 2025-07-17T07:36:52.6769304Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/init.py::skip_init:0 2025-07-17T07:36:52.6772064Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0, line 265 <- wrt source file 2025-07-17T07:36:52.6774740Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0 2025-07-17T07:36:52.6777360Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0, line 360 <- wrt source file 2025-07-17T07:36:52.6780022Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0 2025-07-17T07:36:52.6782799Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0, line 591 <- wrt source file 2025-07-17T07:36:52.6785523Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0 2025-07-17T07:36:52.6787990Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::identity:0, line 849 <- wrt source file 2025-07-17T07:36:52.6790323Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::identity:0 2025-07-17T07:36:52.6792866Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_unstructured:0, line 885 <- wrt source file 2025-07-17T07:36:52.6795440Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_unstructured:0 2025-07-17T07:36:52.6797907Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::l1_unstructured:0, line 928 <- wrt source file 2025-07-17T07:36:52.6800358Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::l1_unstructured:0 2025-07-17T07:36:52.6802805Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_structured:0, line 968 <- wrt source file 2025-07-17T07:36:52.6805265Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_structured:0 2025-07-17T07:36:52.6807688Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::remove:0, line 1197 <- wrt source file 2025-07-17T07:36:52.6809987Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::remove:0 2025-07-17T07:36:52.6812329Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::is_pruned:0, line 1225 <- wrt source file 2025-07-17T07:36:52.6814655Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::is_pruned:0 2025-07-17T07:36:52.6816941Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pad_sequence:0, line 431 <- wrt source file 2025-07-17T07:36:52.6819275Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pad_sequence:0 2025-07-17T07:36:52.6821583Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0, line 492 <- wrt source file 2025-07-17T07:36:52.6823936Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0 2025-07-17T07:36:52.6826249Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pack_sequence:0, line 548 <- wrt source file 2025-07-17T07:36:52.6828606Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pack_sequence:0 2025-07-17T07:36:52.6830931Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0, line 576 <- wrt source file 2025-07-17T07:36:52.6838890Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0 2025-07-17T07:36:52.6841358Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0, line 314 <- wrt source file 2025-07-17T07:36:52.6847802Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0 2025-07-17T07:36:52.6850428Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0, line 346 <- wrt source file 2025-07-17T07:36:52.6856693Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0 2025-07-17T07:36:52.6859339Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/stateless.py::functional_call:0, line 196 <- wrt source file 2025-07-17T07:36:52.6861962Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/stateless.py::functional_call:0 2025-07-17T07:36:52.6864312Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0, line 134 <- wrt source file 2025-07-17T07:36:52.6879456Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0 2025-07-17T07:36:52.6881718Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0, line 156 <- wrt source file 2025-07-17T07:36:52.6886788Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0 2025-07-17T07:36:52.6889272Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0, line 315 <- wrt source file 2025-07-17T07:36:52.6891818Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0 2025-07-17T07:36:52.6894778Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/expanded_weights_utils.py::sum_over_all_but_batch_and_last_n:0, line 178 <- wrt source file 2025-07-17T07:36:52.6898048Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/expanded_weights_utils.py::sum_over_all_but_batch_and_last_n:0 2025-07-17T07:36:52.6900743Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0, line 280 <- wrt source file 2025-07-17T07:36:52.6902993Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0 2025-07-17T07:36:52.6905333Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0, line 388 <- wrt source file 2025-07-17T07:36:52.6907756Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0 2025-07-17T07:36:52.6910092Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::StepLR:0, line 491 <- wrt source file 2025-07-17T07:36:52.6912397Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::StepLR:0 2025-07-17T07:36:52.6914659Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0, line 547 <- wrt source file 2025-07-17T07:36:52.6917084Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0 2025-07-17T07:36:52.6919623Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0, line 608 <- wrt source file 2025-07-17T07:36:52.6921939Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0 2025-07-17T07:36:52.6923937Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LinearLR:0, line 683 <- wrt source file 2025-07-17T07:36:52.6926071Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LinearLR:0 2025-07-17T07:36:52.6928456Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0, line 773 <- wrt source file 2025-07-17T07:36:52.6930701Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0 2025-07-17T07:36:52.6932974Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::PolynomialLR:0, line 971 <- wrt source file 2025-07-17T07:36:52.6935278Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::PolynomialLR:0 2025-07-17T07:36:52.6937707Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0, line 1062 <- wrt source file 2025-07-17T07:36:52.6939860Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0 2025-07-17T07:36:52.6942092Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0, line 1134 <- wrt source file 2025-07-17T07:36:52.6944434Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0 2025-07-17T07:36:52.6946598Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0, line 1794 <- wrt source file 2025-07-17T07:36:52.6949392Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0 2025-07-17T07:36:52.6952070Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1, line 1810 <- wrt source file 2025-07-17T07:36:52.6954863Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1 2025-07-17T07:36:52.6957386Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py::update_bn:0, line 337 <- wrt source file 2025-07-17T07:36:52.6959483Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py::update_bn:0 2025-07-17T07:36:52.6961583Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/package/glob_group.py::GlobGroup:0, line 22 <- wrt source file 2025-07-17T07:36:52.6963898Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/package/glob_group.py::GlobGroup:0 2025-07-17T07:36:52.6966748Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0, line 295 <- wrt source file 2025-07-17T07:36:52.6969614Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0 2025-07-17T07:36:52.6972442Z * DOCTEST : 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<- wrt source file 2025-07-17T07:36:52.7021821Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/distributed/_tensor/common_dtensor.py::skip_unless_torch_gpu:0 2025-07-17T07:36:52.7024942Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/optests/autograd_registration.py::autograd_registration_check:0, line 29 <- wrt source file 2025-07-17T07:36:52.7028189Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/optests/autograd_registration.py::autograd_registration_check:0 2025-07-17T07:36:52.7030947Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0, line 277 <- wrt source file 2025-07-17T07:36:52.7033362Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0 2025-07-17T07:36:52.7035462Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0, line 320 <- wrt source file 2025-07-17T07:36:52.7037724Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0 2025-07-17T07:36:52.7039873Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0, line 357 <- wrt source file 2025-07-17T07:36:52.7042010Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0 2025-07-17T07:36:52.7043876Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0, line 387 <- wrt source file 2025-07-17T07:36:52.7046187Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0 2025-07-17T07:36:52.7048388Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0, line 422 <- wrt source file 2025-07-17T07:36:52.7050648Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0 2025-07-17T07:36:52.7052945Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0, line 457 <- wrt source file 2025-07-17T07:36:52.7055360Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0 2025-07-17T07:36:52.7057384Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_map:0, line 494 <- wrt source file 2025-07-17T07:36:52.7059567Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_map:0 2025-07-17T07:36:52.7061822Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0, line 910 <- wrt source file 2025-07-17T07:36:52.7064265Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0 2025-07-17T07:36:52.7066593Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_dataclass:0, line 307 <- wrt source file 2025-07-17T07:36:52.7069066Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_dataclass:0 2025-07-17T07:36:52.7071528Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_constant:0, line 423 <- wrt source file 2025-07-17T07:36:52.7073901Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_constant:0 2025-07-17T07:36:52.7076139Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_is_leaf:0, line 1030 <- wrt source file 2025-07-17T07:36:52.7078357Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_is_leaf:0 2025-07-17T07:36:52.7080677Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_map:0, line 1349 <- wrt source file 2025-07-17T07:36:52.7082862Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_map:0 2025-07-17T07:36:52.7085054Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0, line 69 <- wrt source file 2025-07-17T07:36:52.7087424Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0 2025-07-17T07:36:52.7090017Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::generate_methods_for_privateuse1_backend:0, line 375 <- wrt source file 2025-07-17T07:36:52.7092913Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::generate_methods_for_privateuse1_backend:0 2025-07-17T07:36:52.7095765Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::_get_custom_mod_func:0, line 410 <- wrt source file 2025-07-17T07:36:52.7098248Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::_get_custom_mod_func:0 2025-07-17T07:36:52.7100598Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py::checkpoint_sequential:0, line 547 <- wrt source file 2025-07-17T07:36:52.7103080Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py::checkpoint_sequential:0 2025-07-17T07:36:52.7105626Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py::set_checkpoint_early_stop:0, line 749 <- wrt source file 2025-07-17T07:36:52.7107985Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py::set_checkpoint_early_stop:0 2025-07-17T07:36:52.7110040Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/dlpack.py::from_dlpack:0, line 80 <- wrt source file 2025-07-17T07:36:52.7111435Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/dlpack.py::from_dlpack:0 2025-07-17T07:36:52.7112779Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0, line 718 <- wrt source file 2025-07-17T07:36:52.9897909Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0 2025-07-17T07:36:52.9900423Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::IterableDataset:0, line 94 <- wrt source file 2025-07-17T07:36:52.9902965Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::IterableDataset:0 2025-07-17T07:36:52.9905145Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::StackDataset:0, line 219 <- wrt source file 2025-07-17T07:36:52.9907184Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::StackDataset:0 2025-07-17T07:36:52.9909226Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::random_split:0, line 441 <- wrt source file 2025-07-17T07:36:52.9911128Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::random_split:0 2025-07-17T07:36:52.9913148Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py::Sampler:0, line 40 <- wrt source file 2025-07-17T07:36:52.9915632Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py::Sampler:0 2025-07-17T07:36:52.9917983Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py::WeightedRandomSampler:0, line 238 <- wrt source file 2025-07-17T07:36:52.9920659Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py::WeightedRandomSampler:0 2025-07-17T07:36:52.9923101Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py::BatchSampler:0, line 301 <- wrt source file 2025-07-17T07:36:52.9925723Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py::BatchSampler:0 2025-07-17T07:36:52.9928026Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_convert:0, line 39 <- wrt source file 2025-07-17T07:36:52.9930714Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_convert:0 2025-07-17T07:36:52.9933371Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::collate:0, line 137 <- wrt source file 2025-07-17T07:36:52.9935805Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::collate:0 2025-07-17T07:36:52.9938212Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_collate:0, line 364 <- wrt source file 2025-07-17T07:36:52.9940834Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_collate:0 2025-07-17T07:36:52.9943158Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py::IterDataPipe:0, line 97 <- wrt source file 2025-07-17T07:36:52.9945747Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py::IterDataPipe:0 2025-07-17T07:36:52.9948317Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0, line 264 <- wrt source file 2025-07-17T07:36:52.9951053Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0 2025-07-17T07:36:52.9953810Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0, line 52 <- wrt source file 2025-07-17T07:36:52.9956795Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0 2025-07-17T07:36:52.9959837Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0, line 198 <- wrt source file 2025-07-17T07:36:52.9962924Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0 2025-07-17T07:36:52.9966024Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combinatorics.py::ShufflerIterDataPipe:0, line 88 <- wrt source file 2025-07-17T07:36:52.9969267Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combinatorics.py::ShufflerIterDataPipe:0 2025-07-17T07:36:52.9972690Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0, line 38 <- wrt source file 2025-07-17T07:36:52.9980387Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0 2025-07-17T07:36:52.9983481Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ForkerIterDataPipe:0, line 88 <- wrt source file 2025-07-17T07:36:52.9986447Z * SKIPPED: 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603 <- wrt source file 2025-07-17T07:36:53.0004763Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::MultiplexerIterDataPipe:0 2025-07-17T07:36:53.0007722Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ZipperIterDataPipe:0, line 671 <- wrt source file 2025-07-17T07:36:53.0010491Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ZipperIterDataPipe:0 2025-07-17T07:36:53.0013415Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/filelister.py::FileListerIterDataPipe:0, line 30 <- wrt source file 2025-07-17T07:36:53.0016457Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/filelister.py::FileListerIterDataPipe:0 2025-07-17T07:36:53.0019511Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/fileopener.py::FileOpenerIterDataPipe:0, line 35 <- wrt source file 2025-07-17T07:36:53.0022623Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/fileopener.py::FileOpenerIterDataPipe:0 2025-07-17T07:36:53.0025665Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py::BatcherIterDataPipe:0, line 53 <- wrt source file 2025-07-17T07:36:53.0028667Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py::BatcherIterDataPipe:0 2025-07-17T07:36:53.0031603Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py::UnBatcherIterDataPipe:0, line 113 <- wrt source file 2025-07-17T07:36:53.0034763Z * SKIPPED: 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<- wrt source file 2025-07-17T07:36:53.0048057Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/streamreader.py::StreamReaderIterDataPipe:0 2025-07-17T07:36:53.0050466Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/utils.py::IterableWrapperIterDataPipe:0, line 29 <- wrt source file 2025-07-17T07:36:53.0052170Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/utils.py::IterableWrapperIterDataPipe:0 2025-07-17T07:36:53.0053738Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/callable.py::MapperMapDataPipe:0, line 35 <- wrt source file 2025-07-17T07:36:53.0055489Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/callable.py::MapperMapDataPipe:0 2025-07-17T07:36:53.0058184Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combinatorics.py::ShufflerIterDataPipe:0, line 34 <- wrt source file 2025-07-17T07:36:53.0061001Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combinatorics.py::ShufflerIterDataPipe:0 2025-07-17T07:36:53.0063745Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combining.py::ConcaterMapDataPipe:0, line 29 <- wrt source file 2025-07-17T07:36:53.0066475Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combining.py::ConcaterMapDataPipe:0 2025-07-17T07:36:53.0069103Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combining.py::ZipperMapDataPipe:0, line 73 <- wrt source file 2025-07-17T07:36:53.0072033Z * SKIPPED: 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file 2025-07-17T07:36:53.0088123Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/utils/common.py::validate_input_col:0 2025-07-17T07:36:53.0090647Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0, line 47 <- wrt source file 2025-07-17T07:36:53.0093204Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0 2025-07-17T07:36:53.0095804Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0, line 439 <- wrt source file 2025-07-17T07:36:53.0098116Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0 2025-07-17T07:36:53.0100514Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0, line 535 <- wrt source file 2025-07-17T07:36:53.0103069Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0 2025-07-17T07:36:53.0105612Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.__init__:0, line 216 <- wrt source file 2025-07-17T07:36:53.0108132Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.__init__:0 2025-07-17T07:36:53.0110650Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0, line 314 <- wrt source file 2025-07-17T07:36:53.0113376Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0 2025-07-17T07:36:53.0115930Z * DOCTEST : 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2025-07-17T07:36:53.0131451Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0, line 480 <- wrt source file 2025-07-17T07:36:53.0134089Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0 2025-07-17T07:36:53.0136669Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0, line 533 <- wrt source file 2025-07-17T07:36:53.0139383Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0 2025-07-17T07:36:53.0141908Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_image:0, line 599 <- wrt source file 2025-07-17T07:36:53.0144476Z * SKIPPED: 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2025-07-17T07:36:53.0159819Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_embedding:0 2025-07-17T07:36:53.0162529Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0, line 989 <- wrt source file 2025-07-17T07:36:53.0165026Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0 2025-07-17T07:36:53.0167844Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0, line 1063 <- wrt source file 2025-07-17T07:36:53.0171307Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0 2025-07-17T07:36:53.0174228Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0, line 1084 <- wrt source file 2025-07-17T07:36:53.0177215Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0 2025-07-17T07:36:53.0179986Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0, line 1108 <- wrt source file 2025-07-17T07:36:53.0182846Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0 2025-07-17T07:36:53.0185600Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0, line 1154 <- wrt source file 2025-07-17T07:36:53.0188281Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0 2025-07-17T07:36:53.0189621Z ============ 2025-07-17T07:36:53.0190089Z Finished doctests 2025-07-17T07:36:53.0190462Z 342 / 719 passed 2025-07-17T07:36:53.0190861Z  2025-07-17T07:36:53.0191329Z === Found 136 parse-time warnings === 2025-07-17T07:36:53.0192005Z --- Parse Warning: 1 / 136 --- 2025-07-17T07:36:53.0203929Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Tensor.dim_order in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py line=1493. 2025-07-17T07:36:53.0206365Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0206961Z 2025-07-17T07:36:53.0207304Z dim_order(ambiguity_check=False) -> tuple 2025-07-17T07:36:53.0207675Z 2025-07-17T07:36:53.0208147Z Returns the uniquely determined tuple of int describing the dim order or 2025-07-17T07:36:53.0208921Z physical layout of :attr:`self`. 2025-07-17T07:36:53.0209411Z 2025-07-17T07:36:53.0209816Z The dim order represents how dimensions are laid out in memory of dense tensors, 2025-07-17T07:36:53.0210612Z starting from the outermost to the innermost dimension. 2025-07-17T07:36:53.0211155Z 2025-07-17T07:36:53.0211466Z Note that the dim order may not always be uniquely determined. 2025-07-17T07:36:53.0212326Z If `ambiguity_check` is True, this function raises a RuntimeError when the dim order cannot be uniquely determined; 2025-07-17T07:36:53.0213324Z If `ambiguity_check` is a list of memory formats, this function raises a RuntimeError when tensor can not be interpreted 2025-07-17T07:36:53.0214124Z into exactly one of the given memory formats, or it cannot be uniquely determined. 2025-07-17T07:36:53.0214843Z If `ambiguity_check` is False, it will return one of legal dim order(s) without checking its uniqueness. 2025-07-17T07:36:53.0215402Z Otherwise, it will raise TypeError. 2025-07-17T07:36:53.0215711Z 2025-07-17T07:36:53.0215979Z Args: 2025-07-17T07:36:53.0216417Z ambiguity_check (bool or List[torch.memory_format]): The check method for ambiguity of dim order. 2025-07-17T07:36:53.0216949Z 2025-07-17T07:36:53.0217168Z Examples:: 2025-07-17T07:36:53.0217383Z 2025-07-17T07:36:53.0217613Z >>> torch.empty((2, 3, 5, 7)).dim_order() 2025-07-17T07:36:53.0217938Z (0, 1, 2, 3) 2025-07-17T07:36:53.0218239Z >>> torch.empty((2, 3, 5, 7)).transpose(1, 2).dim_order() 2025-07-17T07:36:53.0218605Z (0, 2, 1, 3) 2025-07-17T07:36:53.0218964Z >>> torch.empty((2, 3, 5, 7), memory_format=torch.channels_last).dim_order() 2025-07-17T07:36:53.0219383Z (0, 2, 3, 1) 2025-07-17T07:36:53.0219724Z >>> torch.empty((1, 2, 3, 4)).dim_order() 2025-07-17T07:36:53.0220044Z (0, 1, 2, 3) 2025-07-17T07:36:53.0220285Z >>> try: 2025-07-17T07:36:53.0220594Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check=True) 2025-07-17T07:36:53.0221015Z ... except RuntimeError as e: 2025-07-17T07:36:53.0221328Z ... print(e) 2025-07-17T07:36:53.0221855Z The tensor does not have unique dim order, or cannot map to exact one of the given memory formats. 2025-07-17T07:36:53.0222429Z >>> torch.empty((1, 2, 3, 4)).dim_order( 2025-07-17T07:36:53.0222881Z ... ambiguity_check=[torch.contiguous_format, torch.channels_last] 2025-07-17T07:36:53.0223355Z ... ) # It can be mapped to contiguous format 2025-07-17T07:36:53.0223676Z (0, 1, 2, 3) 2025-07-17T07:36:53.0223915Z >>> try: 2025-07-17T07:36:53.0224280Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check="ILLEGAL") 2025-07-17T07:36:53.0224767Z ... except TypeError as e: 2025-07-17T07:36:53.0225083Z ... print(e) 2025-07-17T07:36:53.0235709Z The ambiguity_check argument must be a bool or a list of memory formats. 2025-07-17T07:36:53.0236231Z 2025-07-17T07:36:53.0236439Z .. warning:: 2025-07-17T07:36:53.0257470Z The dim_order tensor API is experimental and subject to change. 2025-07-17T07:36:53.0257954Z 2025-07-17T07:36:53.0258328Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0258783Z 2025-07-17T07:36:53.0259049Z warnings.warn(msg) 2025-07-17T07:36:53.0259392Z 2025-07-17T07:36:53.0259911Z --- Parse Warning: 2 / 136 --- 2025-07-17T07:36:53.0261062Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=meshgrid in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=446. 2025-07-17T07:36:53.0262327Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0262960Z Creates grids of coordinates specified by the 1D inputs in `attr`:tensors. 2025-07-17T07:36:53.0263400Z 2025-07-17T07:36:53.0263686Z This is helpful when you want to visualize data over some 2025-07-17T07:36:53.0264143Z range of inputs. See below for a plotting example. 2025-07-17T07:36:53.0264493Z 2025-07-17T07:36:53.0264768Z Given :math:`N` 1D tensors :math:`T_0 \ldots T_{N-1}` as 2025-07-17T07:36:53.0265243Z inputs with corresponding sizes :math:`S_0 \ldots S_{N-1}`, 2025-07-17T07:36:53.0265723Z this creates :math:`N` N-dimensional tensors :math:`G_0 \ldots 2025-07-17T07:36:53.0266310Z G_{N-1}`, each with shape :math:`(S_0, ..., S_{N-1})` where 2025-07-17T07:36:53.0266774Z the output :math:`G_i` is constructed by expanding :math:`T_i` 2025-07-17T07:36:53.0267188Z to the result shape. 2025-07-17T07:36:53.0267464Z 2025-07-17T07:36:53.0267676Z .. note:: 2025-07-17T07:36:53.0267994Z 0D inputs are treated equivalently to 1D inputs of a 2025-07-17T07:36:53.0268373Z single element. 2025-07-17T07:36:53.0268642Z 2025-07-17T07:36:53.0268847Z .. warning:: 2025-07-17T07:36:53.0269235Z `torch.meshgrid(*tensors)` currently has the same behavior 2025-07-17T07:36:53.0269692Z as calling `numpy.meshgrid(*arrays, indexing='ij')`. 2025-07-17T07:36:53.0270287Z 2025-07-17T07:36:53.0270560Z In the future `torch.meshgrid` will transition to 2025-07-17T07:36:53.0270944Z `indexing='xy'` as the default. 2025-07-17T07:36:53.0271282Z 2025-07-17T07:36:53.0271584Z https://github.com/pytorch/pytorch/issues/50276 tracks 2025-07-17T07:36:53.0272059Z this issue with the goal of migrating to NumPy's behavior. 2025-07-17T07:36:53.0272437Z 2025-07-17T07:36:53.0272778Z .. seealso:: 2025-07-17T07:36:53.0273025Z 2025-07-17T07:36:53.0273310Z :func:`torch.cartesian_prod` has the same effect but it 2025-07-17T07:36:53.0273732Z collects the data in a tensor of vectors. 2025-07-17T07:36:53.0274059Z 2025-07-17T07:36:53.0274244Z Args: 2025-07-17T07:36:53.0274646Z tensors (list of Tensor): list of scalars or 1 dimensional tensors. Scalars will be 2025-07-17T07:36:53.0275200Z treated as tensors of size :math:`(1,)` automatically 2025-07-17T07:36:53.0275561Z 2025-07-17T07:36:53.0275852Z indexing: (str, optional): the indexing mode, either "xy" 2025-07-17T07:36:53.0276322Z or "ij", defaults to "ij". See warning for future changes. 2025-07-17T07:36:53.0276692Z 2025-07-17T07:36:53.0276956Z If "xy" is selected, the first dimension corresponds 2025-07-17T07:36:53.0277401Z to the cardinality of the second input and the second 2025-07-17T07:36:53.0277854Z dimension corresponds to the cardinality of the first 2025-07-17T07:36:53.0278237Z input. 2025-07-17T07:36:53.0278489Z 2025-07-17T07:36:53.0278752Z If "ij" is selected, the dimensions are in the same 2025-07-17T07:36:53.0279158Z order as the cardinality of the inputs. 2025-07-17T07:36:53.0279478Z 2025-07-17T07:36:53.0279682Z Returns: 2025-07-17T07:36:53.0279995Z seq (sequence of Tensors): If the input has :math:`N` 2025-07-17T07:36:53.0280428Z tensors of size :math:`S_0 \ldots S_{N-1}``, then the 2025-07-17T07:36:53.0280906Z output will also have :math:`N` tensors, where each tensor 2025-07-17T07:36:53.0281327Z is of shape :math:`(S_0, ..., S_{N-1})`. 2025-07-17T07:36:53.0281645Z 2025-07-17T07:36:53.0281851Z Example:: 2025-07-17T07:36:53.0282074Z 2025-07-17T07:36:53.0282331Z >>> x = torch.tensor([1, 2, 3]) 2025-07-17T07:36:53.0282668Z >>> y = torch.tensor([4, 5, 6]) 2025-07-17T07:36:53.0282969Z 2025-07-17T07:36:53.0283275Z Observe the element-wise pairings across the grid, (1, 4), 2025-07-17T07:36:53.0283719Z (1, 5), ..., (3, 6). This is the same thing as the 2025-07-17T07:36:53.0284071Z cartesian product. 2025-07-17T07:36:53.0284433Z >>> grid_x, grid_y = torch.meshgrid(x, y, indexing='ij') 2025-07-17T07:36:53.0284819Z >>> grid_x 2025-07-17T07:36:53.0285082Z tensor([[1, 1, 1], 2025-07-17T07:36:53.0285441Z [2, 2, 2], 2025-07-17T07:36:53.0285779Z [3, 3, 3]]) 2025-07-17T07:36:53.0286088Z >>> grid_y 2025-07-17T07:36:53.0286348Z tensor([[4, 5, 6], 2025-07-17T07:36:53.0286631Z [4, 5, 6], 2025-07-17T07:36:53.0286928Z [4, 5, 6]]) 2025-07-17T07:36:53.0287206Z 2025-07-17T07:36:53.0287490Z This correspondence can be seen when these grids are 2025-07-17T07:36:53.0287880Z stacked properly. 2025-07-17T07:36:53.0288274Z >>> torch.equal(torch.cat(tuple(torch.dstack([grid_x, grid_y]))), 2025-07-17T07:36:53.0288773Z ... torch.cartesian_prod(x, y)) 2025-07-17T07:36:53.0289105Z True 2025-07-17T07:36:53.0289370Z 2025-07-17T07:36:53.0289721Z `torch.meshgrid` is commonly used to produce a grid for 2025-07-17T07:36:53.0290151Z plotting. 2025-07-17T07:36:53.0290507Z >>> # xdoctest: +REQUIRES(module:matplotlib) 2025-07-17T07:36:53.0290959Z >>> # xdoctest: +REQUIRES(env:DOCTEST_SHOW) 2025-07-17T07:36:53.0291435Z >>> import matplotlib.pyplot as plt 2025-07-17T07:36:53.0291874Z >>> xs = torch.linspace(-5, 5, steps=100) 2025-07-17T07:36:53.0292477Z >>> ys = torch.linspace(-5, 5, steps=100) 2025-07-17T07:36:53.0292914Z >>> x, y = torch.meshgrid(xs, ys, indexing='xy') 2025-07-17T07:36:53.0293467Z >>> z = torch.sin(torch.sqrt(x * x + y * y)) 2025-07-17T07:36:53.0293909Z >>> ax = plt.axes(projection='3d') 2025-07-17T07:36:53.0294368Z >>> ax.plot_surface(x.numpy(), y.numpy(), z.numpy()) 2025-07-17T07:36:53.0294869Z >>> plt.show() 2025-07-17T07:36:53.0295135Z 2025-07-17T07:36:53.0295390Z .. image:: ../_static/img/meshgrid.png 2025-07-17T07:36:53.0295821Z :width: 512 2025-07-17T07:36:53.0296124Z 2025-07-17T07:36:53.0296371Z 2025-07-17T07:36:53.0296821Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0297344Z 2025-07-17T07:36:53.0297657Z warnings.warn(msg) 2025-07-17T07:36:53.0297963Z 2025-07-17T07:36:53.0298451Z --- Parse Warning: 3 / 136 --- 2025-07-17T07:36:53.0299655Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_unique_impl in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=842. 2025-07-17T07:36:53.0300997Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0301864Z unique(input, sorted=True, return_inverse=False, return_counts=False, dim=None) -> tuple[Tensor, Tensor, Tensor] 2025-07-17T07:36:53.0302484Z 2025-07-17T07:36:53.0302806Z Returns the unique elements of the input tensor. 2025-07-17T07:36:53.0303152Z 2025-07-17T07:36:53.0303554Z .. note:: This function is different from :func:`torch.unique_consecutive` in the sense that 2025-07-17T07:36:53.0304243Z this function also eliminates non-consecutive duplicate values. 2025-07-17T07:36:53.0304665Z 2025-07-17T07:36:53.0305104Z .. note:: Currently in the CUDA implementation and the CPU implementation, 2025-07-17T07:36:53.0305822Z `torch.unique` always sort the tensor at the beginning regardless of the `sort` argument. 2025-07-17T07:36:53.0306598Z Sorting could be slow, so if your input tensor is already sorted, it is recommended to use 2025-07-17T07:36:53.0307199Z :func:`torch.unique_consecutive` which avoids the sorting. 2025-07-17T07:36:53.0307729Z 2025-07-17T07:36:53.0307975Z Args: 2025-07-17T07:36:53.0308305Z input (Tensor): the input tensor 2025-07-17T07:36:53.0308807Z sorted (bool): Whether to sort the unique elements in ascending order 2025-07-17T07:36:53.0309281Z before returning as output. 2025-07-17T07:36:53.0309954Z return_inverse (bool): Whether to also return the indices for where 2025-07-17T07:36:53.0310529Z elements in the original input ended up in the returned unique list. 2025-07-17T07:36:53.0311203Z return_counts (bool): Whether to also return the counts for each unique 2025-07-17T07:36:53.0311631Z element. 2025-07-17T07:36:53.0312086Z dim (int, optional): the dimension to operate upon. If ``None``, the 2025-07-17T07:36:53.0312697Z unique of the flattened input is returned. Otherwise, each of the 2025-07-17T07:36:53.0313275Z tensors indexed by the given dimension is treated as one of the 2025-07-17T07:36:53.0313841Z elements to apply the unique operation upon. See examples for more 2025-07-17T07:36:53.0314288Z details. Default: ``None`` 2025-07-17T07:36:53.0314582Z 2025-07-17T07:36:53.0314785Z Returns: 2025-07-17T07:36:53.0315222Z (Tensor, Tensor (optional), Tensor (optional)): A tensor or a tuple of tensors containing 2025-07-17T07:36:53.0315701Z 2025-07-17T07:36:53.0316017Z - **output** (*Tensor*): the output list of unique scalar elements. 2025-07-17T07:36:53.0316545Z - **inverse_indices** (*Tensor*): (optional) if 2025-07-17T07:36:53.0316974Z :attr:`return_inverse` is True, there will be an additional 2025-07-17T07:36:53.0317486Z returned tensor (same shape as input) representing the indices 2025-07-17T07:36:53.0318018Z for where elements in the original input map to in the output; 2025-07-17T07:36:53.0318530Z otherwise, this function will only return a single tensor. 2025-07-17T07:36:53.0318958Z - **counts** (*Tensor*): (optional) if 2025-07-17T07:36:53.0319374Z :attr:`return_counts` is True, there will be an additional 2025-07-17T07:36:53.0319863Z returned tensor (same shape as output or output.size(dim), 2025-07-17T07:36:53.0320355Z if dim was specified) representing the number of occurrences 2025-07-17T07:36:53.0320783Z for each unique value or tensor. 2025-07-17T07:36:53.0321099Z 2025-07-17T07:36:53.0321306Z Example:: 2025-07-17T07:36:53.0321520Z 2025-07-17T07:36:53.0321853Z >>> output = torch.unique(torch.tensor([1, 3, 2, 3], dtype=torch.long)) 2025-07-17T07:36:53.0322283Z >>> output 2025-07-17T07:36:53.0322520Z tensor([1, 2, 3]) 2025-07-17T07:36:53.0322781Z 2025-07-17T07:36:53.0323027Z >>> output, inverse_indices = torch.unique( 2025-07-17T07:36:53.0323491Z ... torch.tensor([1, 3, 2, 3], dtype=torch.long), sorted=True, return_inverse=True) 2025-07-17T07:36:53.0323933Z >>> output 2025-07-17T07:36:53.0324183Z tensor([1, 2, 3]) 2025-07-17T07:36:53.0324448Z >>> inverse_indices 2025-07-17T07:36:53.0324731Z tensor([0, 2, 1, 2]) 2025-07-17T07:36:53.0325026Z 2025-07-17T07:36:53.0325291Z >>> output, inverse_indices = torch.unique( 2025-07-17T07:36:53.0325854Z ... torch.tensor([[1, 3], [2, 3]], dtype=torch.long), sorted=True, return_inverse=True) 2025-07-17T07:36:53.0326306Z >>> output 2025-07-17T07:36:53.0326542Z tensor([1, 2, 3]) 2025-07-17T07:36:53.0326823Z >>> inverse_indices 2025-07-17T07:36:53.0327102Z tensor([[0, 2], 2025-07-17T07:36:53.0327366Z [1, 2]]) 2025-07-17T07:36:53.0327606Z 2025-07-17T07:36:53.0327828Z >>> a = torch.tensor([ 2025-07-17T07:36:53.0328116Z ... [ 2025-07-17T07:36:53.0328349Z ... [1, 1, 0, 0], 2025-07-17T07:36:53.0328642Z ... [1, 1, 0, 0], 2025-07-17T07:36:53.0328927Z ... [0, 0, 1, 1], 2025-07-17T07:36:53.0329195Z ... ], 2025-07-17T07:36:53.0329559Z ... [ 2025-07-17T07:36:53.0329805Z ... [0, 0, 1, 1], 2025-07-17T07:36:53.0330079Z ... [0, 0, 1, 1], 2025-07-17T07:36:53.0330369Z ... [1, 1, 1, 1], 2025-07-17T07:36:53.0330652Z ... ], 2025-07-17T07:36:53.0330879Z ... [ 2025-07-17T07:36:53.0331125Z ... [1, 1, 0, 0], 2025-07-17T07:36:53.0331417Z ... [1, 1, 0, 0], 2025-07-17T07:36:53.0331714Z ... [0, 0, 1, 1], 2025-07-17T07:36:53.0331992Z ... ], 2025-07-17T07:36:53.0332226Z ... ]) 2025-07-17T07:36:53.0332544Z 2025-07-17T07:36:53.0332860Z >>> # If we call `torch.unique(a, dim=0)`, each of the tensors `a[idx, :, :]` 2025-07-17T07:36:53.0333408Z >>> # will be compared. We can see that `a[0, :, :]` and `a[2, :, :]` match 2025-07-17T07:36:53.0333874Z >>> # each other, so one of them will be removed. 2025-07-17T07:36:53.0334219Z >>> (a[0, :, :] == a[2, :, :]).all() 2025-07-17T07:36:53.0334545Z tensor(True) 2025-07-17T07:36:53.0334839Z >>> a_unique_dim0 = torch.unique(a, dim=0) 2025-07-17T07:36:53.0335161Z >>> a_unique_dim0 2025-07-17T07:36:53.0335439Z tensor([[[0, 0, 1, 1], 2025-07-17T07:36:53.0335786Z [0, 0, 1, 1], 2025-07-17T07:36:53.0336070Z [1, 1, 1, 1]], 2025-07-17T07:36:53.0336370Z [[1, 1, 0, 0], 2025-07-17T07:36:53.0336651Z [1, 1, 0, 0], 2025-07-17T07:36:53.0336932Z [0, 0, 1, 1]]]) 2025-07-17T07:36:53.0337202Z 2025-07-17T07:36:53.0337535Z >>> # Notice which sub-tensors from `a` match with the sub-tensors from 2025-07-17T07:36:53.0337968Z >>> # `a_unique_dim0`: 2025-07-17T07:36:53.0338273Z >>> (a_unique_dim0[0, :, :] == a[1, :, :]).all() 2025-07-17T07:36:53.0338605Z tensor(True) 2025-07-17T07:36:53.0338890Z >>> (a_unique_dim0[1, :, :] == a[0, :, :]).all() 2025-07-17T07:36:53.0339212Z tensor(True) 2025-07-17T07:36:53.0339478Z 2025-07-17T07:36:53.0339797Z >>> # For `torch.unique(a, dim=1)`, each of the tensors `a[:, idx, :]` are 2025-07-17T07:36:53.0340303Z >>> # compared. `a[:, 0, :]` and `a[:, 1, :]` match each other, so one of 2025-07-17T07:36:53.0340713Z >>> # them will be removed. 2025-07-17T07:36:53.0341034Z >>> (a[:, 0, :] == a[:, 1, :]).all() 2025-07-17T07:36:53.0341343Z tensor(True) 2025-07-17T07:36:53.0341601Z >>> torch.unique(a, dim=1) 2025-07-17T07:36:53.0341909Z tensor([[[0, 0, 1, 1], 2025-07-17T07:36:53.0342194Z [1, 1, 0, 0]], 2025-07-17T07:36:53.0342467Z [[1, 1, 1, 1], 2025-07-17T07:36:53.0342750Z [0, 0, 1, 1]], 2025-07-17T07:36:53.0343032Z [[0, 0, 1, 1], 2025-07-17T07:36:53.0343298Z [1, 1, 0, 0]]]) 2025-07-17T07:36:53.0343600Z 2025-07-17T07:36:53.0343925Z >>> # For `torch.unique(a, dim=2)`, the tensors `a[:, :, idx]` are compared. 2025-07-17T07:36:53.0344458Z >>> # `a[:, :, 0]` and `a[:, :, 1]` match each other. Also, `a[:, :, 2]` and 2025-07-17T07:36:53.0344909Z >>> # `a[:, :, 3]` match each other as well. So in this case, two of the 2025-07-17T07:36:53.0345323Z >>> # sub-tensors will be removed. 2025-07-17T07:36:53.0345654Z >>> (a[:, :, 0] == a[:, :, 1]).all() 2025-07-17T07:36:53.0345950Z tensor(True) 2025-07-17T07:36:53.0346216Z >>> (a[:, :, 2] == a[:, :, 3]).all() 2025-07-17T07:36:53.0346527Z tensor(True) 2025-07-17T07:36:53.0346786Z >>> torch.unique(a, dim=2) 2025-07-17T07:36:53.0347097Z tensor([[[0, 1], 2025-07-17T07:36:53.0347367Z [0, 1], 2025-07-17T07:36:53.0347618Z [1, 0]], 2025-07-17T07:36:53.0347886Z [[1, 0], 2025-07-17T07:36:53.0348199Z [1, 0], 2025-07-17T07:36:53.0348448Z [1, 1]], 2025-07-17T07:36:53.0348726Z [[0, 1], 2025-07-17T07:36:53.0348992Z [0, 1], 2025-07-17T07:36:53.0349240Z [1, 0]]]) 2025-07-17T07:36:53.0349500Z 2025-07-17T07:36:53.0349876Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0350342Z 2025-07-17T07:36:53.0350553Z warnings.warn(msg) 2025-07-17T07:36:53.0350804Z 2025-07-17T07:36:53.0351172Z --- Parse Warning: 4 / 136 --- 2025-07-17T07:36:53.0352255Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=560. 2025-07-17T07:36:53.0353436Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0353904Z 2025-07-17T07:36:53.0354168Z Load a model from a github repo or a local directory. 2025-07-17T07:36:53.0354524Z 2025-07-17T07:36:53.0354866Z Note: Loading a model is the typical use case, but this can also be used to 2025-07-17T07:36:53.0355432Z for loading other objects such as tokenizers, loss functions, etc. 2025-07-17T07:36:53.0355904Z 2025-07-17T07:36:53.0356184Z If ``source`` is 'github', ``repo_or_dir`` is expected to be 2025-07-17T07:36:53.0356636Z of the form ``repo_owner/repo_name[:ref]`` with an optional 2025-07-17T07:36:53.0357019Z ref (a tag or a branch). 2025-07-17T07:36:53.0357284Z 2025-07-17T07:36:53.0357568Z If ``source`` is 'local', ``repo_or_dir`` is expected to be a 2025-07-17T07:36:53.0357956Z path to a local directory. 2025-07-17T07:36:53.0358217Z 2025-07-17T07:36:53.0358412Z Args: 2025-07-17T07:36:53.0358662Z repo_or_dir (str): If ``source`` is 'github', 2025-07-17T07:36:53.0359199Z this should correspond to a github repo with format ``repo_owner/repo_name[:ref]`` with 2025-07-17T07:36:53.0359911Z an optional ref (tag or branch), for example 'pytorch/vision:0.10'. If ``ref`` is not specified, 2025-07-17T07:36:53.0360603Z the default branch is assumed to be ``main`` if it exists, and otherwise ``master``. 2025-07-17T07:36:53.0361261Z If ``source`` is 'local' then it should be a path to a local directory. 2025-07-17T07:36:53.0361877Z model (str): the name of a callable (entrypoint) defined in the 2025-07-17T07:36:53.0362563Z repo/dir's ``hubconf.py``. 2025-07-17T07:36:53.0363015Z *args (optional): the corresponding args for callable ``model``. 2025-07-17T07:36:53.0363631Z source (str, optional): 'github' or 'local'. Specifies how 2025-07-17T07:36:53.0364289Z ``repo_or_dir`` is to be interpreted. Default is 'github'. 2025-07-17T07:36:53.0364884Z trust_repo (bool, str or None): ``"check"``, ``True``, ``False`` or ``None``. 2025-07-17T07:36:53.0365626Z This parameter was introduced in v1.12 and helps ensuring that users 2025-07-17T07:36:53.0366197Z only run code from repos that they trust. 2025-07-17T07:36:53.0366733Z 2025-07-17T07:36:53.0367040Z - If ``False``, a prompt will ask the user whether the repo should 2025-07-17T07:36:53.0367651Z be trusted. 2025-07-17T07:36:53.0368069Z - If ``True``, the repo will be added to the trusted list and loaded 2025-07-17T07:36:53.0368509Z without requiring explicit confirmation. 2025-07-17T07:36:53.0368947Z - If ``"check"``, the repo will be checked against the list of 2025-07-17T07:36:53.0369467Z trusted repos in the cache. If it is not present in that list, the 2025-07-17T07:36:53.0370270Z behaviour will fall back onto the ``trust_repo=False`` option. 2025-07-17T07:36:53.0370803Z - If ``None``: this will raise a warning, inviting the user to set 2025-07-17T07:36:53.0371431Z ``trust_repo`` to either ``False``, ``True`` or ``"check"``. This 2025-07-17T07:36:53.0371952Z is only present for backward compatibility and will be removed in 2025-07-17T07:36:53.0372375Z v2.0. 2025-07-17T07:36:53.0372786Z 2025-07-17T07:36:53.0373164Z Default is ``None`` and will eventually change to ``"check"`` in v2.0. 2025-07-17T07:36:53.0373704Z force_reload (bool, optional): whether to force a fresh download of 2025-07-17T07:36:53.0374229Z the github repo unconditionally. Does not have any effect if 2025-07-17T07:36:53.0374662Z ``source = 'local'``. Default is ``False``. 2025-07-17T07:36:53.0375163Z verbose (bool, optional): If ``False``, mute messages about hitting 2025-07-17T07:36:53.0375687Z local caches. Note that the message about first download cannot be 2025-07-17T07:36:53.0376192Z muted. Does not have any effect if ``source = 'local'``. 2025-07-17T07:36:53.0376580Z Default is ``True``. 2025-07-17T07:36:53.0377061Z skip_validation (bool, optional): if ``False``, torchhub will check that the branch or commit 2025-07-17T07:36:53.0377764Z specified by the ``github`` argument properly belongs to the repo owner. This will make 2025-07-17T07:36:53.0378542Z requests to the GitHub API; you can specify a non-default GitHub token by setting the 2025-07-17T07:36:53.0379118Z ``GITHUB_TOKEN`` environment variable. Default is ``False``. 2025-07-17T07:36:53.0379630Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-07-17T07:36:53.0380052Z 2025-07-17T07:36:53.0380249Z Returns: 2025-07-17T07:36:53.0380568Z The output of the ``model`` callable when called with the given 2025-07-17T07:36:53.0380975Z ``*args`` and ``**kwargs``. 2025-07-17T07:36:53.0381254Z 2025-07-17T07:36:53.0381452Z Example: 2025-07-17T07:36:53.0381717Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-07-17T07:36:53.0382062Z >>> # from a github repo 2025-07-17T07:36:53.0382355Z >>> repo = "pytorch/vision" 2025-07-17T07:36:53.0382666Z >>> model = torch.hub.load( 2025-07-17T07:36:53.0383055Z ... repo, "resnet50", weights="ResNet50_Weights.IMAGENET1K_V1" 2025-07-17T07:36:53.0383437Z ... ) 2025-07-17T07:36:53.0383669Z >>> # from a local directory 2025-07-17T07:36:53.0384001Z >>> path = "/some/local/path/pytorch/vision" 2025-07-17T07:36:53.0384349Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0384771Z >>> model = torch.hub.load(path, "resnet50", weights="ResNet50_Weights.DEFAULT") 2025-07-17T07:36:53.0385223Z 2025-07-17T07:36:53.0385593Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0386047Z 2025-07-17T07:36:53.0386254Z warnings.warn(msg) 2025-07-17T07:36:53.0386506Z 2025-07-17T07:36:53.0386884Z --- Parse Warning: 5 / 136 --- 2025-07-17T07:36:53.0387947Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_load_local in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=652. 2025-07-17T07:36:53.0389151Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0389617Z 2025-07-17T07:36:53.0389908Z Load a model from a local directory with a ``hubconf.py``. 2025-07-17T07:36:53.0390277Z 2025-07-17T07:36:53.0390474Z Args: 2025-07-17T07:36:53.0390784Z hubconf_dir (str): path to a local directory that contains a 2025-07-17T07:36:53.0391182Z ``hubconf.py``. 2025-07-17T07:36:53.0391549Z model (str): name of an entrypoint defined in the directory's 2025-07-17T07:36:53.0391946Z ``hubconf.py``. 2025-07-17T07:36:53.0392318Z *args (optional): the corresponding args for callable ``model``. 2025-07-17T07:36:53.0392848Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-07-17T07:36:53.0393296Z 2025-07-17T07:36:53.0393491Z Returns: 2025-07-17T07:36:53.0393788Z a single model with corresponding pretrained weights. 2025-07-17T07:36:53.0394141Z 2025-07-17T07:36:53.0394343Z Example: 2025-07-17T07:36:53.0394601Z >>> # xdoctest: +SKIP("stub local path") 2025-07-17T07:36:53.0394951Z >>> path = "/some/local/path/pytorch/vision" 2025-07-17T07:36:53.0395292Z >>> model = _load_local( 2025-07-17T07:36:53.0395568Z ... path, 2025-07-17T07:36:53.0395798Z ... "resnet50", 2025-07-17T07:36:53.0396109Z ... weights="ResNet50_Weights.IMAGENET1K_V1", 2025-07-17T07:36:53.0396486Z ... ) 2025-07-17T07:36:53.0396689Z 2025-07-17T07:36:53.0397055Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0397508Z 2025-07-17T07:36:53.0397716Z warnings.warn(msg) 2025-07-17T07:36:53.0397952Z 2025-07-17T07:36:53.0398261Z --- Parse Warning: 6 / 136 --- 2025-07-17T07:36:53.0399352Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=download_url_to_file in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=691. 2025-07-17T07:36:53.0400640Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0401177Z Download object at the given URL to a local path. 2025-07-17T07:36:53.0401521Z 2025-07-17T07:36:53.0401705Z Args: 2025-07-17T07:36:53.0401959Z url (str): URL of the object to download 2025-07-17T07:36:53.0402433Z dst (str): Full path where object will be saved, e.g. ``/tmp/temporary_file`` 2025-07-17T07:36:53.0403122Z hash_prefix (str, optional): If not None, the SHA256 downloaded file should start with ``hash_prefix``. 2025-07-17T07:36:53.0403659Z Default: None 2025-07-17T07:36:53.0404090Z progress (bool, optional): whether or not to display a progress bar to stderr 2025-07-17T07:36:53.0404559Z Default: True 2025-07-17T07:36:53.0404806Z 2025-07-17T07:36:53.0405002Z Example: 2025-07-17T07:36:53.0405277Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-07-17T07:36:53.0405711Z >>> # xdoctest: +REQUIRES(POSIX) 2025-07-17T07:36:53.0406061Z >>> torch.hub.download_url_to_file( 2025-07-17T07:36:53.0406526Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth", 2025-07-17T07:36:53.0406977Z ... "/tmp/temporary_file", 2025-07-17T07:36:53.0407266Z ... ) 2025-07-17T07:36:53.0407486Z 2025-07-17T07:36:53.0407680Z 2025-07-17T07:36:53.0408040Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0408495Z 2025-07-17T07:36:53.0408703Z warnings.warn(msg) 2025-07-17T07:36:53.0408941Z 2025-07-17T07:36:53.0409249Z --- Parse Warning: 7 / 136 --- 2025-07-17T07:36:53.0410361Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_state_dict_from_url in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=816. 2025-07-17T07:36:53.0411747Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0412269Z Loads the Torch serialized object at the given URL. 2025-07-17T07:36:53.0412619Z 2025-07-17T07:36:53.0412914Z If downloaded file is a zip file, it will be automatically 2025-07-17T07:36:53.0413309Z decompressed. 2025-07-17T07:36:53.0413536Z 2025-07-17T07:36:53.0413865Z If the object is already present in `model_dir`, it's deserialized and 2025-07-17T07:36:53.0414291Z returned. 2025-07-17T07:36:53.0414630Z The default value of ``model_dir`` is ``/checkpoints`` where 2025-07-17T07:36:53.0415159Z ``hub_dir`` is the directory returned by :func:`~torch.hub.get_dir`. 2025-07-17T07:36:53.0415621Z 2025-07-17T07:36:53.0415807Z Args: 2025-07-17T07:36:53.0416070Z url (str): URL of the object to download 2025-07-17T07:36:53.0416509Z model_dir (str, optional): directory in which to save the object 2025-07-17T07:36:53.0417175Z map_location (optional): a function or a dict specifying how to remap storage locations (see torch.load) 2025-07-17T07:36:53.0417905Z progress (bool, optional): whether or not to display a progress bar to stderr. 2025-07-17T07:36:53.0418380Z Default: True 2025-07-17T07:36:53.0418923Z check_hash(bool, optional): If True, the filename part of the URL should follow the naming convention 2025-07-17T07:36:53.0419569Z ``filename-.ext`` where ```` is the first eight or more 2025-07-17T07:36:53.0420130Z digits of the SHA256 hash of the contents of the file. The hash is used to 2025-07-17T07:36:53.0420670Z ensure unique names and to verify the contents of the file. 2025-07-17T07:36:53.0421079Z Default: False 2025-07-17T07:36:53.0421583Z file_name (str, optional): name for the downloaded file. Filename from ``url`` will be used if not set. 2025-07-17T07:36:53.0422432Z weights_only(bool, optional): If True, only weights will be loaded and no complex pickled objects. 2025-07-17T07:36:53.0423137Z Recommended for untrusted sources. See :func:`~torch.load` for more details. 2025-07-17T07:36:53.0423590Z 2025-07-17T07:36:53.0423789Z Example: 2025-07-17T07:36:53.0424067Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-07-17T07:36:53.0424470Z >>> state_dict = torch.hub.load_state_dict_from_url( 2025-07-17T07:36:53.0424956Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth" 2025-07-17T07:36:53.0425377Z ... ) 2025-07-17T07:36:53.0425595Z 2025-07-17T07:36:53.0425775Z 2025-07-17T07:36:53.0452868Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0453483Z 2025-07-17T07:36:53.0453679Z warnings.warn(msg) 2025-07-17T07:36:53.0453936Z 2025-07-17T07:36:53.0454337Z --- Parse Warning: 8 / 136 --- 2025-07-17T07:36:53.0455450Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Library.fallback in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=374. 2025-07-17T07:36:53.0456686Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:53.0457306Z Registers the function implementation as the fallback for the given key. 2025-07-17T07:36:53.0457752Z 2025-07-17T07:36:53.0458072Z This function only works for a library with global namespace ("_"). 2025-07-17T07:36:53.0458493Z 2025-07-17T07:36:53.0458692Z Args: 2025-07-17T07:36:53.0459102Z fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel` 2025-07-17T07:36:53.0459620Z to register a fallthrough. 2025-07-17T07:36:53.0460180Z dispatch_key: dispatch key that the input function should be registered for. By default, it uses 2025-07-17T07:36:53.0460789Z the dispatch key that the library was created with. 2025-07-17T07:36:53.0461441Z with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument 2025-07-17T07:36:53.0462259Z to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls. 2025-07-17T07:36:53.0462785Z 2025-07-17T07:36:53.0462999Z Example:: 2025-07-17T07:36:53.0463231Z 2025-07-17T07:36:53.0463454Z >>> my_lib = Library("_", "IMPL") 2025-07-17T07:36:53.0463923Z >>> def fallback_kernel(op, *args, **kwargs): 2025-07-17T07:36:53.0464303Z >>> # Handle all autocast ops generically 2025-07-17T07:36:53.0464639Z >>> # ... 2025-07-17T07:36:53.0464954Z >>> my_lib.fallback(fallback_kernel, "Autocast") 2025-07-17T07:36:53.0465292Z 2025-07-17T07:36:53.0466057Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7)) 2025-07-17T07:36:53.0466885Z 2025-07-17T07:36:53.0467115Z my_lib.fallback(fallback_kernel, "Autocast") 2025-07-17T07:36:53.0467480Z ^ 2025-07-17T07:36:53.0467694Z warnings.warn(msg) 2025-07-17T07:36:53.0467928Z 2025-07-17T07:36:53.0468231Z --- Parse Warning: 9 / 136 --- 2025-07-17T07:36:53.0469320Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=933. 2025-07-17T07:36:53.0470777Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:53.0471365Z Register a FakeTensor implementation ("fake impl") for this operator. 2025-07-17T07:36:53.0471797Z 2025-07-17T07:36:53.0472240Z Also sometimes known as a "meta kernel", "abstract impl". 2025-07-17T07:36:53.0472605Z 2025-07-17T07:36:53.0472963Z An "FakeTensor implementation" specifies the behavior of this operator on 2025-07-17T07:36:53.0473551Z Tensors that carry no data ("FakeTensor"). Given some input Tensors with 2025-07-17T07:36:53.0474141Z certain properties (sizes/strides/storage_offset/device), it specifies 2025-07-17T07:36:53.0474629Z what the properties of the output Tensors are. 2025-07-17T07:36:53.0474969Z 2025-07-17T07:36:53.0475307Z The FakeTensor implementation has the same signature as the operator. 2025-07-17T07:36:53.0475856Z It is run for both FakeTensors and meta tensors. To write a FakeTensor 2025-07-17T07:36:53.0476403Z implementation, assume that all Tensor inputs to the operator are 2025-07-17T07:36:53.0476944Z regular CPU/CUDA/Meta tensors, but they do not have storage, and 2025-07-17T07:36:53.0477473Z you are trying to return regular CPU/CUDA/Meta tensor(s) as output. 2025-07-17T07:36:53.0478018Z The FakeTensor implementation must consist of only PyTorch operations 2025-07-17T07:36:53.0478566Z (and may not directly access the storage or data of any input or 2025-07-17T07:36:53.0478987Z intermediate Tensors). 2025-07-17T07:36:53.0479249Z 2025-07-17T07:36:53.0479519Z This API may be used as a decorator (see examples). 2025-07-17T07:36:53.0479868Z 2025-07-17T07:36:53.0480102Z For a detailed guide on custom ops, please see 2025-07-17T07:36:53.0480595Z https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html 2025-07-17T07:36:53.0481028Z 2025-07-17T07:36:53.0481208Z Args: 2025-07-17T07:36:53.0481564Z op_name: Operator name (along with the overload) or OpOverload object. 2025-07-17T07:36:53.0482024Z func: Fake tensor implementation. 2025-07-17T07:36:53.0482457Z lib (Optional[Library]): Library to register the fake tensor to. 2025-07-17T07:36:53.0482945Z allow_override: Flag controlling if we want to override an 2025-07-17T07:36:53.0483425Z existing registered fake impl. This is by default off, 2025-07-17T07:36:53.0483894Z and will error you're trying to register a fake impl to 2025-07-17T07:36:53.0484354Z an operator that already has a fake impl. This also only 2025-07-17T07:36:53.0484815Z applies if the custom operator was not created via 2025-07-17T07:36:53.0485288Z torch.library.custom_op, as overriding and existing fake 2025-07-17T07:36:53.0485878Z impl is already allowed. 2025-07-17T07:36:53.0486174Z 2025-07-17T07:36:53.0486377Z Examples: 2025-07-17T07:36:53.0486614Z >>> import torch 2025-07-17T07:36:53.0486876Z >>> import numpy as np 2025-07-17T07:36:53.0487186Z >>> from torch import Tensor 2025-07-17T07:36:53.0487482Z >>> 2025-07-17T07:36:53.0487790Z >>> # Example 1: an operator without data-dependent output shape 2025-07-17T07:36:53.0488322Z >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=()) 2025-07-17T07:36:53.0488918Z >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-07-17T07:36:53.0489440Z >>> raise NotImplementedError("Implementation goes here") 2025-07-17T07:36:53.0489813Z >>> 2025-07-17T07:36:53.0490113Z >>> @torch.library.register_fake("mylib::custom_linear") 2025-07-17T07:36:53.0490500Z >>> def _(x, weight, bias): 2025-07-17T07:36:53.0490798Z >>> assert x.dim() == 2 2025-07-17T07:36:53.0491118Z >>> assert weight.dim() == 2 2025-07-17T07:36:53.0491449Z >>> assert bias.dim() == 1 2025-07-17T07:36:53.0491777Z >>> assert x.shape[1] == weight.shape[1] 2025-07-17T07:36:53.0492201Z >>> assert weight.shape[0] == bias.shape[0] 2025-07-17T07:36:53.0492572Z >>> assert x.device == weight.device 2025-07-17T07:36:53.0492885Z >>> 2025-07-17T07:36:53.0493122Z >>> return (x @ weight.t()) + bias 2025-07-17T07:36:53.0493438Z >>> 2025-07-17T07:36:53.0493742Z >>> with torch._subclasses.fake_tensor.FakeTensorMode(): 2025-07-17T07:36:53.0494126Z >>> x = torch.randn(2, 3) 2025-07-17T07:36:53.0494437Z >>> w = torch.randn(3, 3) 2025-07-17T07:36:53.0494746Z >>> b = torch.randn(3) 2025-07-17T07:36:53.0495071Z >>> y = torch.ops.mylib.custom_linear(x, w, b) 2025-07-17T07:36:53.0495407Z >>> 2025-07-17T07:36:53.0495642Z >>> assert y.shape == (2, 3) 2025-07-17T07:36:53.0495938Z >>> 2025-07-17T07:36:53.0496229Z >>> # Example 2: an operator with data-dependent output shape 2025-07-17T07:36:53.0496744Z >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=()) 2025-07-17T07:36:53.0497211Z >>> def custom_nonzero(x: Tensor) -> Tensor: 2025-07-17T07:36:53.0497552Z >>> x_np = x.numpy(force=True) 2025-07-17T07:36:53.0497908Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-07-17T07:36:53.0498290Z >>> return torch.tensor(res, device=x.device) 2025-07-17T07:36:53.0498609Z >>> 2025-07-17T07:36:53.0498917Z >>> @torch.library.register_fake("mylib::custom_nonzero") 2025-07-17T07:36:53.0499296Z >>> def _(x): 2025-07-17T07:36:53.0499606Z >>> # Number of nonzero-elements is data-dependent. 2025-07-17T07:36:53.0500012Z >>> # Since we cannot peek at the data in an fake impl, 2025-07-17T07:36:53.0500439Z >>> # we use the ctx object to construct a new symint that 2025-07-17T07:36:53.0500845Z >>> # represents the data-dependent size. 2025-07-17T07:36:53.0501197Z >>> ctx = torch.library.get_ctx() 2025-07-17T07:36:53.0501538Z >>> nnz = ctx.new_dynamic_size() 2025-07-17T07:36:53.0501869Z >>> shape = [nnz, x.dim()] 2025-07-17T07:36:53.0502221Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-07-17T07:36:53.0502582Z >>> return result 2025-07-17T07:36:53.0502851Z >>> 2025-07-17T07:36:53.0503156Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-07-17T07:36:53.0503518Z >>> 2025-07-17T07:36:53.0503761Z >>> x = torch.tensor([0, 1, 2, 3, 4, 0]) 2025-07-17T07:36:53.0504263Z >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x) 2025-07-17T07:36:53.0504724Z >>> trace.print_readable() 2025-07-17T07:36:53.0505010Z >>> 2025-07-17T07:36:53.0505364Z >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x)) 2025-07-17T07:36:53.0505888Z 2025-07-17T07:36:53.0506167Z 2025-07-17T07:36:53.0507183Z Original Error: IndentationError('expected an indented block after function definition on line 37', ('', 38, 1, '_._ = None\n', 38, 2)) 2025-07-17T07:36:53.0508345Z 2025-07-17T07:36:53.0508619Z _._ = None 2025-07-17T07:36:53.0509030Z ^ 2025-07-17T07:36:53.0509330Z warnings.warn(msg) 2025-07-17T07:36:53.0509696Z 2025-07-17T07:36:53.0510137Z --- Parse Warning: 10 / 136 --- 2025-07-17T07:36:53.0511268Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_autograd in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1068. 2025-07-17T07:36:53.0512517Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0513052Z Register a backward formula for this custom op. 2025-07-17T07:36:53.0513393Z 2025-07-17T07:36:53.0513785Z In order for an operator to work with autograd, you need to register 2025-07-17T07:36:53.0514207Z a backward formula: 2025-07-17T07:36:53.0514594Z 1. You must tell us how to compute gradients during the backward pass 2025-07-17T07:36:53.0515040Z by providing us a "backward" function. 2025-07-17T07:36:53.0515760Z 2. If you need any values from the forward to compute gradients, you can 2025-07-17T07:36:53.0516241Z use `setup_context` to save values for backward. 2025-07-17T07:36:53.0516576Z 2025-07-17T07:36:53.0516902Z ``backward`` runs during the backward pass. It accepts ``(ctx, *grads)``: 2025-07-17T07:36:53.0517452Z - ``grads`` is one or more gradients. The number of gradients matches 2025-07-17T07:36:53.0517888Z the number of outputs of the operator. 2025-07-17T07:36:53.0518341Z The ``ctx`` object is `the same ctx object `_ used by 2025-07-17T07:36:53.0518918Z :class:`torch.autograd.Function`. The semantics of ``backward_fn`` are the 2025-07-17T07:36:53.0519441Z same as :meth:`torch.autograd.Function.backward`. 2025-07-17T07:36:53.0519798Z 2025-07-17T07:36:53.0520111Z ``setup_context(ctx, inputs, output)`` runs during the forward pass. 2025-07-17T07:36:53.0520671Z Please save quantities needed for backward onto the ``ctx`` object via 2025-07-17T07:36:53.0521261Z either :meth:`torch.autograd.function.FunctionCtx.save_for_backward` 2025-07-17T07:36:53.0521801Z or assigning them as attributes of ``ctx``. If your custom op has 2025-07-17T07:36:53.0522330Z kwarg-only arguments, we expect the signature of ``setup_context`` 2025-07-17T07:36:53.0522857Z to be ``setup_context(ctx, inputs, keyword_only_inputs, output)``. 2025-07-17T07:36:53.0523246Z 2025-07-17T07:36:53.0523566Z Both ``setup_context_fn`` and ``backward_fn`` must be traceable. That is, 2025-07-17T07:36:53.0524133Z they may not directly access :meth:`torch.Tensor.data_ptr` and they must 2025-07-17T07:36:53.0524711Z not depend on or mutate global state. If you need a non-traceable backward, 2025-07-17T07:36:53.0525277Z you can make it a separate custom_op that you call inside ``backward_fn``. 2025-07-17T07:36:53.0525764Z 2025-07-17T07:36:53.0526096Z If you need different autograd behavior on different devices, then we 2025-07-17T07:36:53.0526665Z recommend creating two different custom operators, one for each device 2025-07-17T07:36:53.0527228Z that needs different behavior, and switching between them at runtime. 2025-07-17T07:36:53.0527654Z 2025-07-17T07:36:53.0527856Z Examples: 2025-07-17T07:36:53.0528142Z >>> import torch 2025-07-17T07:36:53.0528424Z >>> import numpy as np 2025-07-17T07:36:53.0528725Z >>> from torch import Tensor 2025-07-17T07:36:53.0529052Z >>> 2025-07-17T07:36:53.0529408Z >>> @torch.library.custom_op("mylib::numpy_sin", mutates_args=()) 2025-07-17T07:36:53.0529853Z >>> def numpy_sin(x: Tensor) -> Tensor: 2025-07-17T07:36:53.0530192Z >>> x_np = x.cpu().numpy() 2025-07-17T07:36:53.0530528Z >>> y_np = np.sin(x_np) 2025-07-17T07:36:53.0530891Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-07-17T07:36:53.0531287Z >>> 2025-07-17T07:36:53.0531566Z >>> def setup_context(ctx, inputs, output) -> Tensor: 2025-07-17T07:36:53.0531925Z >>> x, = inputs 2025-07-17T07:36:53.0532215Z >>> ctx.save_for_backward(x) 2025-07-17T07:36:53.0532504Z >>> 2025-07-17T07:36:53.0532752Z >>> def backward(ctx, grad): 2025-07-17T07:36:53.0533075Z >>> x, = ctx.saved_tensors 2025-07-17T07:36:53.0533374Z >>> return grad * x.cos() 2025-07-17T07:36:53.0533670Z >>> 2025-07-17T07:36:53.0533928Z >>> torch.library.register_autograd( 2025-07-17T07:36:53.0534398Z ... "mylib::numpy_sin", backward, setup_context=setup_context 2025-07-17T07:36:53.0534772Z ... ) 2025-07-17T07:36:53.0534990Z >>> 2025-07-17T07:36:53.0535242Z >>> x = torch.randn(3, requires_grad=True) 2025-07-17T07:36:53.0535565Z >>> y = numpy_sin(x) 2025-07-17T07:36:53.0535925Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-07-17T07:36:53.0536347Z >>> assert torch.allclose(grad_x, x.cos()) 2025-07-17T07:36:53.0536650Z >>> 2025-07-17T07:36:53.0536898Z >>> # Example with a keyword-only arg 2025-07-17T07:36:53.0537332Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-07-17T07:36:53.0537854Z >>> def numpy_mul(x: Tensor, *, val: float) -> Tensor: 2025-07-17T07:36:53.0538216Z >>> x_np = x.cpu().numpy() 2025-07-17T07:36:53.0538533Z >>> y_np = x_np * val 2025-07-17T07:36:53.0538894Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-07-17T07:36:53.0539237Z >>> 2025-07-17T07:36:53.0539592Z >>> def setup_context(ctx, inputs, keyword_only_inputs, output) -> Tensor: 2025-07-17T07:36:53.0540060Z >>> ctx.val = keyword_only_inputs["val"] 2025-07-17T07:36:53.0540369Z >>> 2025-07-17T07:36:53.0540608Z >>> def backward(ctx, grad): 2025-07-17T07:36:53.0540921Z >>> return grad * ctx.val 2025-07-17T07:36:53.0541202Z >>> 2025-07-17T07:36:53.0541455Z >>> torch.library.register_autograd( 2025-07-17T07:36:53.0541869Z ... "mylib::numpy_mul", backward, setup_context=setup_context 2025-07-17T07:36:53.0542247Z ... ) 2025-07-17T07:36:53.0542454Z >>> 2025-07-17T07:36:53.0542715Z >>> x = torch.randn(3, requires_grad=True) 2025-07-17T07:36:53.0543064Z >>> y = numpy_mul(x, val=3.14) 2025-07-17T07:36:53.0543440Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-07-17T07:36:53.0543902Z >>> assert torch.allclose(grad_x, torch.full_like(x, 3.14)) 2025-07-17T07:36:53.0544276Z 2025-07-17T07:36:53.0544458Z 2025-07-17T07:36:53.0544830Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0545284Z 2025-07-17T07:36:53.0545493Z warnings.warn(msg) 2025-07-17T07:36:53.0545731Z 2025-07-17T07:36:53.0546086Z --- Parse Warning: 11 / 136 --- 2025-07-17T07:36:53.0547168Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=opcheck in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1482. 2025-07-17T07:36:53.0548410Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0549019Z Given an operator and some sample arguments, tests if the operator is 2025-07-17T07:36:53.0549459Z registered correctly. 2025-07-17T07:36:53.0549708Z 2025-07-17T07:36:53.0550038Z That is, when you use the torch.library/TORCH_LIBRARY APIs to create a 2025-07-17T07:36:53.0550598Z custom op, you specified metadata (e.g. mutability info) about the custom op 2025-07-17T07:36:53.0551185Z and these APIs require that the functions you pass them satisfy certain 2025-07-17T07:36:53.0551773Z properties (e.g. no data pointer access in the fake/meta/abstract kernel) 2025-07-17T07:36:53.0552253Z ``opcheck`` tests these metadata and properties. 2025-07-17T07:36:53.0552589Z 2025-07-17T07:36:53.0552799Z Concretely, we test the following: 2025-07-17T07:36:53.0553097Z 2025-07-17T07:36:53.0553390Z - test_schema: If the schema matches the implementation of 2025-07-17T07:36:53.0553889Z the operator. For example: if the schema specifies a Tensor is mutated, 2025-07-17T07:36:53.0554424Z then we check the implementation mutates the Tensor. If the schema 2025-07-17T07:36:53.0555002Z specifies that we return a new Tensor, then we check that the 2025-07-17T07:36:53.0555514Z implementation returns a new Tensor (instead of an existing one or 2025-07-17T07:36:53.0555947Z a view of an existing one). 2025-07-17T07:36:53.0556346Z - test_autograd_registration: If the operator supports training 2025-07-17T07:36:53.0556852Z (autograd): we check that its autograd formula is registered via 2025-07-17T07:36:53.0557369Z torch.library.register_autograd or a manual registration to one 2025-07-17T07:36:53.0557885Z or more DispatchKey::Autograd keys. Any other DispatchKey-based 2025-07-17T07:36:53.0558339Z registrations may lead to undefined behavior. 2025-07-17T07:36:53.0558767Z - test_faketensor: If the operator has a FakeTensor kernel 2025-07-17T07:36:53.0559218Z (and if it is correct). The FakeTensor kernel is necessary ( 2025-07-17T07:36:53.0559715Z but not sufficient) for the operator to work with PyTorch compilation 2025-07-17T07:36:53.0560261Z APIs (torch.compile/export/FX). We check that a FakeTensor kernel 2025-07-17T07:36:53.0560763Z (also sometimes known as a meta kernel) was registered for the 2025-07-17T07:36:53.0561245Z operator and that it is correct. This test takes the result of 2025-07-17T07:36:53.0561740Z running the operator on real tensors and the result of running 2025-07-17T07:36:53.0562243Z the operator on FakeTensors and checks that they have the same 2025-07-17T07:36:53.0562689Z Tensor metadata (sizes/strides/dtype/device/etc). 2025-07-17T07:36:53.0563147Z - test_aot_dispatch_dynamic: If the operator has correct behavior 2025-07-17T07:36:53.0563631Z with PyTorch compilation APIs (torch.compile/export/FX). 2025-07-17T07:36:53.0564120Z This checks that the outputs (and gradients, if applicable) are the 2025-07-17T07:36:53.0564579Z same under eager-mode PyTorch and torch.compile. 2025-07-17T07:36:53.0565027Z This test is a superset of ``test_faketensor`` and is an e2e test; 2025-07-17T07:36:53.0565583Z other things it tests are that the operator supports 2025-07-17T07:36:53.0566066Z functionalization and that the backward pass (if it exists) also 2025-07-17T07:36:53.0566534Z supports FakeTensor and functionalization. 2025-07-17T07:36:53.0566858Z 2025-07-17T07:36:53.0567152Z For best results, please call ``opcheck`` multiple times with a 2025-07-17T07:36:53.0567641Z representative set of inputs. If your operator supports 2025-07-17T07:36:53.0568167Z autograd, please use ``opcheck`` with inputs with ``requires_grad = True``; 2025-07-17T07:36:53.0568767Z if your operator supports multiple devices (e.g. CPU and CUDA), please 2025-07-17T07:36:53.0569247Z use ``opcheck`` with inputs on all supported devices. 2025-07-17T07:36:53.0569586Z 2025-07-17T07:36:53.0569779Z Args: 2025-07-17T07:36:53.0570261Z op: The operator. Must either be a function decorated with 2025-07-17T07:36:53.0570769Z :func:`torch.library.custom_op` or an OpOverload/OpOverloadPacket 2025-07-17T07:36:53.0571312Z found in torch.ops.* (e.g. torch.ops.aten.sin, torch.ops.mylib.foo) 2025-07-17T07:36:53.0571827Z args: The args to the operator 2025-07-17T07:36:53.0572146Z kwargs: The kwargs to the operator 2025-07-17T07:36:53.0572545Z test_utils: Tests that we should run. Default: all of them. 2025-07-17T07:36:53.0572971Z Example: ("test_schema", "test_faketensor") 2025-07-17T07:36:53.0573398Z raise_exception: If we should raise an exception on the first 2025-07-17T07:36:53.0573867Z error. If False, we will return a dict with information 2025-07-17T07:36:53.0574253Z on if each test passed or not. 2025-07-17T07:36:53.0574779Z rtol (Optional[float]): Relative tolerance for floating point comparisons. 2025-07-17T07:36:53.0575266Z If specified ``atol`` must also be specified. 2025-07-17T07:36:53.0575708Z If omitted, default values based on the ``dtype`` are selected 2025-07-17T07:36:53.0576177Z (see the table in :func:`torch.testing.assert_close`). 2025-07-17T07:36:53.0576688Z atol (Optional[float]): Absolute tolerance for floating point comparisons. 2025-07-17T07:36:53.0577190Z If specified ``rtol`` must also be specified. 2025-07-17T07:36:53.0577633Z If omitted, default values based on the ``dtype`` are selected 2025-07-17T07:36:53.0578099Z (see the table in :func:`torch.testing.assert_close`). 2025-07-17T07:36:53.0578450Z 2025-07-17T07:36:53.0578648Z .. warning:: 2025-07-17T07:36:53.0578862Z 2025-07-17T07:36:53.0579175Z opcheck and :func:`torch.autograd.gradcheck` test different things; 2025-07-17T07:36:53.0579723Z opcheck tests if your usage of torch.library APIs is correct while 2025-07-17T07:36:53.0580243Z :func:`torch.autograd.gradcheck` tests if your autograd formula is 2025-07-17T07:36:53.0580784Z mathematically correct. Use both to test custom ops that support 2025-07-17T07:36:53.0581210Z gradient computation. 2025-07-17T07:36:53.0581476Z 2025-07-17T07:36:53.0581659Z Example: 2025-07-17T07:36:53.0581862Z 2025-07-17T07:36:53.0582087Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:53.0582527Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-07-17T07:36:53.0582967Z >>> def numpy_mul(x: Tensor, y: float) -> Tensor: 2025-07-17T07:36:53.0583327Z >>> x_np = x.numpy(force=True) 2025-07-17T07:36:53.0583634Z >>> z_np = x_np * y 2025-07-17T07:36:53.0583952Z >>> return torch.from_numpy(z_np).to(x.device) 2025-07-17T07:36:53.0584277Z >>> 2025-07-17T07:36:53.0584519Z >>> @numpy_mul.register_fake 2025-07-17T07:36:53.0584802Z >>> def _(x, y): 2025-07-17T07:36:53.0585080Z >>> return torch.empty_like(x) 2025-07-17T07:36:53.0585387Z >>> 2025-07-17T07:36:53.0585627Z >>> def setup_context(ctx, inputs, output): 2025-07-17T07:36:53.0585949Z >>> y, = inputs 2025-07-17T07:36:53.0586207Z >>> ctx.y = y 2025-07-17T07:36:53.0586442Z >>> 2025-07-17T07:36:53.0586658Z >>> def backward(ctx, grad): 2025-07-17T07:36:53.0586973Z >>> return grad * ctx.y, None 2025-07-17T07:36:53.0587256Z >>> 2025-07-17T07:36:53.0587647Z >>> numpy_mul.register_autograd(backward, setup_context=setup_context) 2025-07-17T07:36:53.0588062Z >>> 2025-07-17T07:36:53.0588301Z >>> sample_inputs = [ 2025-07-17T07:36:53.0588584Z >>> (torch.randn(3), 3.14), 2025-07-17T07:36:53.0588926Z >>> (torch.randn(2, 3, device='cuda'), 2.718), 2025-07-17T07:36:53.0589314Z >>> (torch.randn(1, 10, requires_grad=True), 1.234), 2025-07-17T07:36:53.0589750Z >>> (torch.randn(64, 64, device='cuda', requires_grad=True), 90.18), 2025-07-17T07:36:53.0590127Z >>> ] 2025-07-17T07:36:53.0590365Z >>> 2025-07-17T07:36:53.0590603Z >>> for args in sample_inputs: 2025-07-17T07:36:53.0590944Z >>> torch.library.opcheck(numpy_mul, args) 2025-07-17T07:36:53.0591255Z 2025-07-17T07:36:53.0591442Z 2025-07-17T07:36:53.0591791Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0592231Z 2025-07-17T07:36:53.0592420Z warnings.warn(msg) 2025-07-17T07:36:53.0592649Z 2025-07-17T07:36:53.0592982Z --- Parse Warning: 12 / 136 --- 2025-07-17T07:36:53.0594113Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py line=1285. 2025-07-17T07:36:53.0595330Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0596022Z load(f, map_location=None, pickle_module=pickle, *, weights_only=True, mmap=None, **pickle_load_args) 2025-07-17T07:36:53.0596544Z 2025-07-17T07:36:53.0596821Z Loads an object saved with :func:`torch.save` from a file. 2025-07-17T07:36:53.0597173Z 2025-07-17T07:36:53.0597505Z :func:`torch.load` uses Python's unpickling facilities but treats storages, 2025-07-17T07:36:53.0598071Z which underlie tensors, specially. They are first deserialized on the 2025-07-17T07:36:53.0598621Z CPU and are then moved to the device they were saved from. If this fails 2025-07-17T07:36:53.0599164Z (e.g. because the run time system doesn't have certain devices), an exception 2025-07-17T07:36:53.0599751Z is raised. However, storages can be dynamically remapped to an alternative 2025-07-17T07:36:53.0600264Z set of devices using the :attr:`map_location` argument. 2025-07-17T07:36:53.0600605Z 2025-07-17T07:36:53.0600950Z If :attr:`map_location` is a callable, it will be called once for each serialized 2025-07-17T07:36:53.0601523Z storage with two arguments: storage and location. The storage argument 2025-07-17T07:36:53.0602079Z will be the initial deserialization of the storage, residing on the CPU. 2025-07-17T07:36:53.0602623Z Each serialized storage has a location tag associated with it which 2025-07-17T07:36:53.0603162Z identifies the device it was saved from, and this tag is the second 2025-07-17T07:36:53.0603739Z argument passed to :attr:`map_location`. The builtin location tags are ``'cpu'`` 2025-07-17T07:36:53.0604316Z for CPU tensors and ``'cuda:device_id'`` (e.g. ``'cuda:2'``) for CUDA tensors. 2025-07-17T07:36:53.0604847Z :attr:`map_location` should return either ``None`` or a storage. If 2025-07-17T07:36:53.0605497Z :attr:`map_location` returns a storage, it will be used as the final deserialized 2025-07-17T07:36:53.0606114Z object, already moved to the right device. Otherwise, :func:`torch.load` will 2025-07-17T07:36:53.0606703Z fall back to the default behavior, as if :attr:`map_location` wasn't specified. 2025-07-17T07:36:53.0607153Z 2025-07-17T07:36:53.0607502Z If :attr:`map_location` is a :class:`torch.device` object or a string containing 2025-07-17T07:36:53.0608077Z a device tag, it indicates the location where all tensors should be loaded. 2025-07-17T07:36:53.0608509Z 2025-07-17T07:36:53.0608922Z Otherwise, if :attr:`map_location` is a dict, it will be used to remap location tags 2025-07-17T07:36:53.0609506Z appearing in the file (keys), to ones that specify where to put the 2025-07-17T07:36:53.0609913Z storages (values). 2025-07-17T07:36:53.0610169Z 2025-07-17T07:36:53.0610513Z User extensions can register their own location tags and tagging and 2025-07-17T07:36:53.0611111Z deserialization methods using :func:`torch.serialization.register_package`. 2025-07-17T07:36:53.0611576Z 2025-07-17T07:36:53.0611931Z See :ref:`layout-control` for more advanced tools to manipulate a checkpoint. 2025-07-17T07:36:53.0612400Z 2025-07-17T07:36:53.0612597Z Args: 2025-07-17T07:36:53.0613060Z f: a file-like object (has to implement :meth:`read`, :meth:`readline`, :meth:`tell`, and :meth:`seek`), 2025-07-17T07:36:53.0613672Z or a string or os.PathLike object containing a file name 2025-07-17T07:36:53.0614277Z map_location: a function, :class:`torch.device`, string or a dict specifying how to remap storage 2025-07-17T07:36:53.0614818Z locations 2025-07-17T07:36:53.0615210Z pickle_module: module used for unpickling metadata and objects (has to 2025-07-17T07:36:53.0615784Z match the :attr:`pickle_module` used to serialize file) 2025-07-17T07:36:53.0616269Z weights_only: Indicates whether unpickler should be restricted to 2025-07-17T07:36:53.0616753Z loading only tensors, primitive types, dictionaries 2025-07-17T07:36:53.0617276Z and any types added via :func:`torch.serialization.add_safe_globals`. 2025-07-17T07:36:53.0617755Z See :ref:`weights-only` for more details. 2025-07-17T07:36:53.0618326Z mmap: Indicates whether the file should be mapped rather than loading all the storages into memory. 2025-07-17T07:36:53.0619122Z Typically, tensor storages in the file will first be moved from disk to CPU memory, after which they 2025-07-17T07:36:53.0619922Z are moved to the location that they were tagged with when saving, or specified by ``map_location``. This 2025-07-17T07:36:53.0620702Z second step is a no-op if the final location is CPU. When the ``mmap`` flag is set, instead of copying the 2025-07-17T07:36:53.0621476Z tensor storages from disk to CPU memory in the first step, ``f`` is mapped, which means tensor storages 2025-07-17T07:36:53.0622084Z will be lazily loaded when their data is accessed. 2025-07-17T07:36:53.0622591Z pickle_load_args: (Python 3 only) optional keyword arguments passed over to 2025-07-17T07:36:53.0623170Z :func:`pickle_module.load` and :func:`pickle_module.Unpickler`, e.g., 2025-07-17T07:36:53.0623621Z :attr:`errors=...`. 2025-07-17T07:36:53.0623901Z 2025-07-17T07:36:53.0624099Z .. warning:: 2025-07-17T07:36:53.0624465Z :func:`torch.load()` unless `weights_only` parameter is set to `True`, 2025-07-17T07:36:53.0625000Z uses ``pickle`` module implicitly, which is known to be insecure. 2025-07-17T07:36:53.0625593Z It is possible to construct malicious pickle data which will execute arbitrary code 2025-07-17T07:36:53.0626214Z during unpickling. Never load data that could have come from an untrusted 2025-07-17T07:36:53.0626863Z source in an unsafe mode, or that could have been tampered with. **Only load data you trust**. 2025-07-17T07:36:53.0627354Z 2025-07-17T07:36:53.0627439Z .. note:: 2025-07-17T07:36:53.0627706Z When you call :func:`torch.load()` on a file which contains GPU tensors, those tensors 2025-07-17T07:36:53.0627962Z will be loaded to GPU by default. You can call ``torch.load(.., map_location='cpu')`` 2025-07-17T07:36:53.0628228Z and then :meth:`load_state_dict` to avoid GPU RAM surge when loading a model checkpoint. 2025-07-17T07:36:53.0628367Z 2025-07-17T07:36:53.0628452Z .. note:: 2025-07-17T07:36:53.0628700Z By default, we decode byte strings as ``utf-8``. This is to avoid a common error 2025-07-17T07:36:53.0628922Z case ``UnicodeDecodeError: 'ascii' codec can't decode byte 0x...`` 2025-07-17T07:36:53.0629132Z when loading files saved by Python 2 in Python 3. If this default 2025-07-17T07:36:53.0629396Z is incorrect, you may use an extra :attr:`encoding` keyword argument to specify how 2025-07-17T07:36:53.0629630Z these objects should be loaded, e.g., :attr:`encoding='latin1'` decodes them 2025-07-17T07:36:53.0629892Z to strings using ``latin1`` encoding, and :attr:`encoding='bytes'` keeps them 2025-07-17T07:36:53.0630129Z as byte arrays which can be decoded later with ``byte_array.decode(...)``. 2025-07-17T07:36:53.0630205Z 2025-07-17T07:36:53.0630289Z Example: 2025-07-17T07:36:53.0630432Z >>> # xdoctest: +SKIP("undefined filepaths") 2025-07-17T07:36:53.0630570Z >>> torch.load("tensors.pt", weights_only=True) 2025-07-17T07:36:53.0630681Z # Load all tensors onto the CPU 2025-07-17T07:36:53.0630785Z >>> torch.load( 2025-07-17T07:36:53.0630879Z ... "tensors.pt", 2025-07-17T07:36:53.0631077Z ... map_location=torch.device("cpu"), 2025-07-17T07:36:53.0631178Z ... weights_only=True, 2025-07-17T07:36:53.0631257Z ... ) 2025-07-17T07:36:53.0631413Z # Load all tensors onto the CPU, using a function 2025-07-17T07:36:53.0631503Z >>> torch.load( 2025-07-17T07:36:53.0631602Z ... "tensors.pt", 2025-07-17T07:36:53.0631750Z ... map_location=lambda storage, loc: storage, 2025-07-17T07:36:53.0631847Z ... weights_only=True, 2025-07-17T07:36:53.0631925Z ... ) 2025-07-17T07:36:53.0632042Z # Load all tensors onto GPU 1 2025-07-17T07:36:53.0632132Z >>> torch.load( 2025-07-17T07:36:53.0632235Z ... "tensors.pt", 2025-07-17T07:36:53.0632395Z ... map_location=lambda storage, loc: storage.cuda(1), 2025-07-17T07:36:53.0632492Z ... weights_only=True, 2025-07-17T07:36:53.0632614Z ... ) # type: ignore[attr-defined] 2025-07-17T07:36:53.0632727Z # Map tensors from GPU 1 to GPU 0 2025-07-17T07:36:53.0632814Z >>> torch.load( 2025-07-17T07:36:53.0632919Z ... "tensors.pt", 2025-07-17T07:36:53.0633057Z ... map_location={"cuda:1": "cuda:0"}, 2025-07-17T07:36:53.0633155Z ... weights_only=True, 2025-07-17T07:36:53.0633247Z ... ) 2025-07-17T07:36:53.0633362Z # Load tensor from io.BytesIO object 2025-07-17T07:36:53.0633623Z # Loading from a buffer setting weights_only=False, warning this can be unsafe 2025-07-17T07:36:53.0633737Z >>> with open("tensor.pt", "rb") as f: 2025-07-17T07:36:53.0633851Z ... buffer = io.BytesIO(f.read()) 2025-07-17T07:36:53.0633983Z >>> torch.load(buffer, weights_only=False) 2025-07-17T07:36:53.0634131Z # Load a module with 'ascii' encoding for unpickling 2025-07-17T07:36:53.0634379Z # Loading from a module setting weights_only=False, warning this can be unsafe 2025-07-17T07:36:53.0634581Z >>> torch.load("module.pt", encoding="ascii", weights_only=False) 2025-07-17T07:36:53.0634663Z 2025-07-17T07:36:53.0634928Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0635007Z 2025-07-17T07:36:53.0635101Z warnings.warn(msg) 2025-07-17T07:36:53.0635192Z 2025-07-17T07:36:53.0635410Z --- Parse Warning: 13 / 136 --- 2025-07-17T07:36:53.0636420Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=compute_required_storage_length in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims_common/__init__.py line=1848. 2025-07-17T07:36:53.0636725Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0636941Z Computes the minimum storage size to hold the given tensor geometry. 2025-07-17T07:36:53.0637021Z 2025-07-17T07:36:53.0637127Z Example 2025-07-17T07:36:53.0637204Z ======= 2025-07-17T07:36:53.0637293Z 2025-07-17T07:36:53.0637514Z This is the size of a newly allocated tensor's storage, in units of elements 2025-07-17T07:36:53.0637590Z 2025-07-17T07:36:53.0637710Z >>> t = torch.empty((10, 20)) 2025-07-17T07:36:53.0638007Z >>> compute_required_storage_length(t.shape, t.stride(), t.storage_offset()) 2025-07-17T07:36:53.0638086Z 200 2025-07-17T07:36:53.0638176Z 2025-07-17T07:36:53.0638277Z >>> # xdoctest: +SKIP(failing) 2025-07-17T07:36:53.0638405Z >>> t2 = torch.empty_strided((1, 2, 3), (5, 7, 11)) 2025-07-17T07:36:53.0638539Z >>> size = compute_required_storage_length( 2025-07-17T07:36:53.0638669Z ... t2.shape, t2.stride(), t2.storage_offset() 2025-07-17T07:36:53.0638759Z ... ) 2025-07-17T07:36:53.0638858Z >>> size == t.storage().size() 2025-07-17T07:36:53.0638939Z True 2025-07-17T07:36:53.0639028Z 2025-07-17T07:36:53.0639270Z A valid tensor may have a larger storage size, but never smaller 2025-07-17T07:36:53.0639346Z 2025-07-17T07:36:53.0639464Z >>> slice = torch.empty(100)[20:40] 2025-07-17T07:36:53.0639563Z >>> slice.storage().size() 2025-07-17T07:36:53.0639644Z 100 2025-07-17T07:36:53.0639731Z 2025-07-17T07:36:53.0639842Z >>> compute_required_storage_length( 2025-07-17T07:36:53.0640004Z ... slice.shape, slice.stride(), slice.storage_offset() 2025-07-17T07:36:53.0640094Z ... ) 2025-07-17T07:36:53.0640171Z 40 2025-07-17T07:36:53.0640247Z 2025-07-17T07:36:53.0640335Z 2025-07-17T07:36:53.0640586Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0640672Z 2025-07-17T07:36:53.0640764Z warnings.warn(msg) 2025-07-17T07:36:53.0640839Z 2025-07-17T07:36:53.0641035Z --- Parse Warning: 14 / 136 --- 2025-07-17T07:36:53.0641938Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=is_available in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=66. 2025-07-17T07:36:53.0642182Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:53.0642444Z Check if the current accelerator is available at runtime: it was build, all the 2025-07-17T07:36:53.0642655Z required drivers are available and at least one device is visible. 2025-07-17T07:36:53.0642809Z See :ref:`accelerator` for details. 2025-07-17T07:36:53.0642887Z 2025-07-17T07:36:53.0642970Z Returns: 2025-07-17T07:36:53.0643249Z bool: A boolean indicating if there is an available :ref:`accelerator`. 2025-07-17T07:36:53.0643327Z 2025-07-17T07:36:53.0643566Z .. note:: This API delegates to the device-specific version of `is_available`. 2025-07-17T07:36:53.0643837Z On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set, 2025-07-17T07:36:53.0644081Z this function will NOT poison fork. Otherwise, it will. For more details, see 2025-07-17T07:36:53.0644239Z :ref:`multiprocessing-poison-fork-note`. 2025-07-17T07:36:53.0644318Z 2025-07-17T07:36:53.0644404Z Example:: 2025-07-17T07:36:53.0644492Z 2025-07-17T07:36:53.0644759Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-07-17T07:36:53.0644839Z 2025-07-17T07:36:53.0645495Z Original Error: SyntaxError('invalid syntax', ('', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78)) 2025-07-17T07:36:53.0645612Z 2025-07-17T07:36:53.0645873Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-07-17T07:36:53.0645983Z ^ 2025-07-17T07:36:53.0646082Z warnings.warn(msg) 2025-07-17T07:36:53.0646171Z 2025-07-17T07:36:53.0646362Z --- Parse Warning: 15 / 136 --- 2025-07-17T07:36:53.0647269Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=synchronize in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=212. 2025-07-17T07:36:53.0647557Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:53.0647760Z Wait for all kernels in all streams on the given device to complete. 2025-07-17T07:36:53.0647836Z 2025-07-17T07:36:53.0647925Z Args: 2025-07-17T07:36:53.0648245Z device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match 2025-07-17T07:36:53.0648480Z the current :ref:`accelerator` device type. If not given, 2025-07-17T07:36:53.0648723Z use :func:`torch.accelerator.current_device_index` by default. 2025-07-17T07:36:53.0648802Z 2025-07-17T07:36:53.0649124Z .. note:: This function is a no-op if the current :ref:`accelerator` is not initialized. 2025-07-17T07:36:53.0649200Z 2025-07-17T07:36:53.0649285Z Example:: 2025-07-17T07:36:53.0649372Z 2025-07-17T07:36:53.0649511Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:53.0649786Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-07-17T07:36:53.0649925Z >>> start_event = torch.Event(enable_timing=True) 2025-07-17T07:36:53.0650058Z >>> end_event = torch.Event(enable_timing=True) 2025-07-17T07:36:53.0650172Z >>> start_event.record() 2025-07-17T07:36:53.0650410Z >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator()) 2025-07-17T07:36:53.0650511Z >>> sum = torch.sum(tensor) 2025-07-17T07:36:53.0650622Z >>> end_event.record() 2025-07-17T07:36:53.0650752Z >>> torch.accelerator.synchronize() 2025-07-17T07:36:53.0650920Z >>> elapsed_time_ms = start_event.elapsed_time(end_event) 2025-07-17T07:36:53.0651014Z 2025-07-17T07:36:53.0651578Z Original Error: SyntaxError('invalid syntax', ('', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78)) 2025-07-17T07:36:53.0651672Z 2025-07-17T07:36:53.0651934Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-07-17T07:36:53.0652032Z ^ 2025-07-17T07:36:53.0652142Z warnings.warn(msg) 2025-07-17T07:36:53.0652222Z 2025-07-17T07:36:53.0652404Z --- Parse Warning: 16 / 136 --- 2025-07-17T07:36:53.0653272Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=cudart in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/__init__.py line=434. 2025-07-17T07:36:53.0653519Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:53.0653650Z Retrieves the CUDA runtime API module. 2025-07-17T07:36:53.0653731Z 2025-07-17T07:36:53.0653809Z 2025-07-17T07:36:53.0654078Z This function initializes the CUDA runtime environment if it is not already 2025-07-17T07:36:53.0654308Z initialized and returns the CUDA runtime API module (_cudart). The CUDA 2025-07-17T07:36:53.0654528Z runtime API module provides access to various CUDA runtime functions. 2025-07-17T07:36:53.0654622Z 2025-07-17T07:36:53.0654704Z Args: 2025-07-17T07:36:53.0654817Z ``None`` 2025-07-17T07:36:53.0654908Z 2025-07-17T07:36:53.0654991Z Returns: 2025-07-17T07:36:53.0655146Z module: The CUDA runtime API module (_cudart). 2025-07-17T07:36:53.0655227Z 2025-07-17T07:36:53.0655310Z Raises: 2025-07-17T07:36:53.0655557Z RuntimeError: If CUDA cannot be re-initialized in a forked subprocess. 2025-07-17T07:36:53.0655918Z AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable. 2025-07-17T07:36:53.0655993Z 2025-07-17T07:36:53.0656137Z Example of CUDA operations with profiling: 2025-07-17T07:36:53.0656255Z >>> import torch 2025-07-17T07:36:53.0656386Z >>> from torch.cuda import cudart, check_error 2025-07-17T07:36:53.0656490Z >>> import os 2025-07-17T07:36:53.0656571Z >>> 2025-07-17T07:36:53.0656695Z >>> os.environ["CUDA_PROFILE"] = "1" 2025-07-17T07:36:53.0656819Z >>> 2025-07-17T07:36:53.0656956Z >>> def perform_cuda_operations_with_streams(): 2025-07-17T07:36:53.0657080Z >>> stream = torch.cuda.Stream() 2025-07-17T07:36:53.0657194Z >>> with torch.cuda.stream(stream): 2025-07-17T07:36:53.0657319Z >>> x = torch.randn(100, 100, device='cuda') 2025-07-17T07:36:53.0657499Z >>> y = torch.randn(100, 100, device='cuda') 2025-07-17T07:36:53.0657600Z >>> z = torch.mul(x, y) 2025-07-17T07:36:53.0657686Z >>> return z 2025-07-17T07:36:53.0657775Z >>> 2025-07-17T07:36:53.0657883Z >>> torch.cuda.synchronize() 2025-07-17T07:36:53.0658025Z >>> print("====== Start nsys profiling ======") 2025-07-17T07:36:53.0658176Z >>> check_error(cudart().cudaProfilerStart()) 2025-07-17T07:36:53.0658313Z >>> with torch.autograd.profiler.emit_nvtx(): 2025-07-17T07:36:53.0658471Z >>> result = perform_cuda_operations_with_streams() 2025-07-17T07:36:53.0658596Z >>> print("CUDA operations completed.") 2025-07-17T07:36:53.0658755Z >>> check_error(torch.cuda.cudart().cudaProfilerStop()) 2025-07-17T07:36:53.0658887Z >>> print("====== End nsys profiling ======") 2025-07-17T07:36:53.0658965Z 2025-07-17T07:36:53.0659164Z To run this example and save the profiling information, execute: 2025-07-17T07:36:53.0659534Z >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-07-17T07:36:53.0659611Z 2025-07-17T07:36:53.0659866Z This command profiles the CUDA operations in the provided script and saves 2025-07-17T07:36:53.0660058Z the profiling information to a file named `trace_name.prof`. 2025-07-17T07:36:53.0660289Z The `--profile-from-start off` option ensures that profiling starts only 2025-07-17T07:36:53.0660448Z after the `cudaProfilerStart` call in the script. 2025-07-17T07:36:53.0660670Z The `--csv` and `--print-summary` options format the profiling output as a 2025-07-17T07:36:53.0660796Z CSV file and print a summary, respectively. 2025-07-17T07:36:53.0661046Z The `-o` option specifies the output file name, and the `-f` option forces the 2025-07-17T07:36:53.0661200Z overwrite of the output file if it already exists. 2025-07-17T07:36:53.0661294Z 2025-07-17T07:36:53.0661946Z Original Error: SyntaxError('invalid syntax', ('', 1, 1, '$ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py\n', 1, 2)) 2025-07-17T07:36:53.0662027Z 2025-07-17T07:36:53.0662389Z $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-07-17T07:36:53.0662468Z ^ 2025-07-17T07:36:53.0662564Z warnings.warn(msg) 2025-07-17T07:36:53.0662650Z 2025-07-17T07:36:53.0662834Z --- Parse Warning: 17 / 136 --- 2025-07-17T07:36:53.0663755Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Future.then in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=101. 2025-07-17T07:36:53.0664017Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0664094Z 2025-07-17T07:36:53.0664329Z Append the given callback function to this ``Future``, which will be run 2025-07-17T07:36:53.0664531Z when the ``Future`` is completed. Multiple callbacks can be added to 2025-07-17T07:36:53.0664735Z the same ``Future``, but the order in which they will be executed cannot 2025-07-17T07:36:53.0664966Z be guaranteed (to enforce a certain order consider chaining: 2025-07-17T07:36:53.0665160Z ``fut.then(cb1).then(cb2)``). The callback must take one argument, which 2025-07-17T07:36:53.0665374Z is the reference to this ``Future``. The callback function can use the 2025-07-17T07:36:53.0665575Z :meth:`value` method to get the value. Note that if this ``Future`` is 2025-07-17T07:36:53.0665799Z already completed, the given callback will be run immediately inline. 2025-07-17T07:36:53.0665888Z 2025-07-17T07:36:53.0666077Z If the ``Future``'s value contains tensors that reside on GPUs, the 2025-07-17T07:36:53.0666341Z callback might be invoked while the async kernels that are populating 2025-07-17T07:36:53.0666581Z those tensors haven't yet finished executing on the device. However, the 2025-07-17T07:36:53.0666785Z callback will be invoked with some dedicated streams set as current 2025-07-17T07:36:53.0667001Z (fetched from a global pool) which will be synchronized with those 2025-07-17T07:36:53.0667226Z kernels. Hence any operation performed by the callback on these tensors 2025-07-17T07:36:53.0667432Z will be scheduled on the device after the kernels complete. In other 2025-07-17T07:36:53.0667638Z words, as long as the callback doesn't switch streams, it can safely 2025-07-17T07:36:53.0667868Z manipulate the result without any additional synchronization. This is 2025-07-17T07:36:53.0668026Z similar to the non-blocking behavior of :meth:`wait`. 2025-07-17T07:36:53.0668118Z 2025-07-17T07:36:53.0668327Z Similarly, if the callback returns a value that contains tensors that 2025-07-17T07:36:53.0668533Z reside on a GPU, it can do so even if the kernels that are producing 2025-07-17T07:36:53.0668747Z these tensors are still running on the device, as long as the callback 2025-07-17T07:36:53.0668948Z didn't change streams during its execution. If one wants to change 2025-07-17T07:36:53.0669170Z streams, one must be careful to re-synchronize them with the original 2025-07-17T07:36:53.0669380Z streams, that is, those that were current when the callback was invoked. 2025-07-17T07:36:53.0669459Z 2025-07-17T07:36:53.0669552Z Args: 2025-07-17T07:36:53.0669753Z callback(``Callable``): a ``Callable`` that takes this ``Future`` as 2025-07-17T07:36:53.0669863Z the only argument. 2025-07-17T07:36:53.0670140Z 2025-07-17T07:36:53.0670261Z Returns: 2025-07-17T07:36:53.0670470Z A new ``Future`` object that holds the return value of the 2025-07-17T07:36:53.0670652Z ``callback`` and will be marked as completed when the given 2025-07-17T07:36:53.0670751Z ``callback`` finishes. 2025-07-17T07:36:53.0670843Z 2025-07-17T07:36:53.0671017Z .. note:: Note that if the callback function throws, either 2025-07-17T07:36:53.0671228Z through the original future being completed with an exception and 2025-07-17T07:36:53.0671429Z calling ``fut.wait()``, or through other code in the callback, the 2025-07-17T07:36:53.0671630Z future returned by ``then`` will be marked appropriately with the 2025-07-17T07:36:53.0671835Z encountered error. However, if this callback later completes 2025-07-17T07:36:53.0672045Z additional futures, those futures are not marked as completed with 2025-07-17T07:36:53.0672323Z an error and the user is responsible for handling completion/waiting 2025-07-17T07:36:53.0672447Z on those futures independently. 2025-07-17T07:36:53.0672523Z 2025-07-17T07:36:53.0672613Z Example:: 2025-07-17T07:36:53.0672705Z 2025-07-17T07:36:53.0672852Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-07-17T07:36:53.0672950Z >>> def callback(fut): 2025-07-17T07:36:53.0673100Z ... print(f"RPC return value is {fut.wait()}.") 2025-07-17T07:36:53.0673212Z >>> fut = torch.futures.Future() 2025-07-17T07:36:53.0673423Z >>> # The inserted callback will print the return value when 2025-07-17T07:36:53.0673542Z >>> # receiving the response from "worker1" 2025-07-17T07:36:53.0673644Z >>> cb_fut = fut.then(callback) 2025-07-17T07:36:53.0673758Z >>> chain_cb_fut = cb_fut.then( 2025-07-17T07:36:53.0673903Z ... lambda x : print(f"Chained cb done. {x.wait()}") 2025-07-17T07:36:53.0673984Z ... ) 2025-07-17T07:36:53.0674089Z >>> fut.set_result(5) 2025-07-17T07:36:53.0674187Z RPC return value is 5. 2025-07-17T07:36:53.0674283Z Chained cb done. None 2025-07-17T07:36:53.0674372Z 2025-07-17T07:36:53.0674692Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0674771Z 2025-07-17T07:36:53.0674878Z warnings.warn(msg) 2025-07-17T07:36:53.0674955Z 2025-07-17T07:36:53.0675178Z --- Parse Warning: 18 / 136 --- 2025-07-17T07:36:53.0676087Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Future.set_result in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=211. 2025-07-17T07:36:53.0676351Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0676440Z 2025-07-17T07:36:53.0676645Z Set the result for this ``Future``, which will mark this ``Future`` as 2025-07-17T07:36:53.0676859Z completed and trigger all attached callbacks. Note that a ``Future`` 2025-07-17T07:36:53.0676981Z cannot be marked completed twice. 2025-07-17T07:36:53.0677058Z 2025-07-17T07:36:53.0677288Z If the result contains tensors that reside on GPUs, this method can be 2025-07-17T07:36:53.0677491Z called even if the asynchronous kernels that are populating those 2025-07-17T07:36:53.0677709Z tensors haven't yet completed running on the device, provided that the 2025-07-17T07:36:53.0677942Z streams on which those kernels were enqueued are set as the current ones 2025-07-17T07:36:53.0678152Z when this method is called. Put simply, it's safe to call this method 2025-07-17T07:36:53.0678364Z immediately after launching those kernels, without any additional 2025-07-17T07:36:53.0678601Z synchronization, as long as one doesn't change streams in between. This 2025-07-17T07:36:53.0678816Z method will record events on all the relevant current streams and will 2025-07-17T07:36:53.0679026Z use them to ensure proper scheduling for all the consumers of this 2025-07-17T07:36:53.0679113Z ``Future``. 2025-07-17T07:36:53.0679191Z 2025-07-17T07:36:53.0679287Z Args: 2025-07-17T07:36:53.0679454Z result (object): the result object of this ``Future``. 2025-07-17T07:36:53.0679532Z 2025-07-17T07:36:53.0679633Z Example:: 2025-07-17T07:36:53.0679711Z 2025-07-17T07:36:53.0679856Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-07-17T07:36:53.0679965Z >>> import threading 2025-07-17T07:36:53.0680059Z >>> import time 2025-07-17T07:36:53.0680170Z >>> def slow_set_future(fut, value): 2025-07-17T07:36:53.0680276Z ... time.sleep(0.5) 2025-07-17T07:36:53.0680376Z ... fut.set_result(value) 2025-07-17T07:36:53.0680498Z >>> fut = torch.futures.Future() 2025-07-17T07:36:53.0680597Z >>> t = threading.Thread( 2025-07-17T07:36:53.0680728Z ... target=slow_set_future, 2025-07-17T07:36:53.0680849Z ... args=(fut, torch.ones(2) * 3) 2025-07-17T07:36:53.0680928Z ... ) 2025-07-17T07:36:53.0681011Z >>> t.start() 2025-07-17T07:36:53.0681117Z >>> print(fut.wait()) 2025-07-17T07:36:53.0681210Z tensor([3., 3.]) 2025-07-17T07:36:53.0681292Z >>> t.join() 2025-07-17T07:36:53.0681382Z 2025-07-17T07:36:53.0681634Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0681710Z 2025-07-17T07:36:53.0681826Z warnings.warn(msg) 2025-07-17T07:36:53.0681930Z 2025-07-17T07:36:53.0682129Z --- Parse Warning: 19 / 136 --- 2025-07-17T07:36:53.0683011Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=compile_shader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/mps/__init__.py line=145. 2025-07-17T07:36:53.0683279Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0683512Z Compiles compute shader from source and allows one to invoke kernels 2025-07-17T07:36:53.0683659Z defined there from the comfort of Python runtime 2025-07-17T07:36:53.0683751Z Example:: 2025-07-17T07:36:53.0683893Z 2025-07-17T07:36:53.0684027Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_MPS) 2025-07-17T07:36:53.0684158Z >>> lib = torch.mps.compile_shader( 2025-07-17T07:36:53.0684540Z ... "kernel void full(device float* out, constant float& val, uint idx [[thread_position_in_grid]]) { out[idx] = val; }" 2025-07-17T07:36:53.0684627Z ... ) 2025-07-17T07:36:53.0684757Z >>> x = torch.zeros(16, device="mps") 2025-07-17T07:36:53.0684857Z >>> lib.full(x, 3.14) 2025-07-17T07:36:53.0684954Z 2025-07-17T07:36:53.0685220Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0685361Z 2025-07-17T07:36:53.0685462Z warnings.warn(msg) 2025-07-17T07:36:53.0685556Z 2025-07-17T07:36:53.0685743Z --- Parse Warning: 20 / 136 --- 2025-07-17T07:36:53.0686600Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=sum in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py line=202. 2025-07-17T07:36:53.0686859Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0687022Z Return the sum of each row of the given sparse tensor. 2025-07-17T07:36:53.0687118Z 2025-07-17T07:36:53.0687343Z Returns the sum of each row of the sparse tensor :attr:`input` in the given 2025-07-17T07:36:53.0687538Z dimensions :attr:`dim`. If :attr:`dim` is a list of dimensions, 2025-07-17T07:36:53.0687761Z reduce over all of them. When sum over all ``sparse_dim``, this method 2025-07-17T07:36:53.0687910Z returns a dense tensor instead of a sparse tensor. 2025-07-17T07:36:53.0688005Z 2025-07-17T07:36:53.0688263Z All summed :attr:`dim` are squeezed (see :func:`torch.squeeze`), resulting an output 2025-07-17T07:36:53.0688457Z tensor having :attr:`dim` fewer dimensions than :attr:`input`. 2025-07-17T07:36:53.0688554Z 2025-07-17T07:36:53.0688771Z During backward, only gradients at ``nnz`` locations of :attr:`input` 2025-07-17T07:36:53.0689008Z will propagate back. Note that the gradients of :attr:`input` is coalesced. 2025-07-17T07:36:53.0689101Z 2025-07-17T07:36:53.0689187Z Args: 2025-07-17T07:36:53.0689311Z input (Tensor): the input sparse tensor 2025-07-17T07:36:53.0689595Z dim (int or tuple of ints): a dimension or a list of dimensions to reduce. Default: reduce 2025-07-17T07:36:53.0689691Z over all dims. 2025-07-17T07:36:53.0689958Z dtype (:class:`torch.dtype`, optional): the desired data type of returned Tensor. 2025-07-17T07:36:53.0690105Z Default: dtype of :attr:`input`. 2025-07-17T07:36:53.0690181Z 2025-07-17T07:36:53.0690281Z Example:: 2025-07-17T07:36:53.0690355Z 2025-07-17T07:36:53.0690438Z >>> nnz = 3 2025-07-17T07:36:53.0690540Z >>> dims = [5, 5, 2, 3] 2025-07-17T07:36:53.0690698Z >>> I = torch.cat([torch.randint(0, dims[0], size=(nnz,)), 2025-07-17T07:36:53.0690890Z torch.randint(0, dims[1], size=(nnz,))], 0).reshape(2, nnz) 2025-07-17T07:36:53.0691008Z >>> V = torch.randn(nnz, dims[2], dims[3]) 2025-07-17T07:36:53.0691134Z >>> size = torch.Size(dims) 2025-07-17T07:36:53.0691286Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-07-17T07:36:53.0691411Z >>> S = torch.sparse_coo_tensor(I, V, size) 2025-07-17T07:36:53.0691490Z >>> S 2025-07-17T07:36:53.0691611Z tensor(indices=tensor([[2, 0, 3], 2025-07-17T07:36:53.0691712Z [2, 4, 1]]), 2025-07-17T07:36:53.0691837Z values=tensor([[[-0.6438, -1.6467, 1.4004], 2025-07-17T07:36:53.0691953Z [ 0.3411, 0.0918, -0.2312]], 2025-07-17T07:36:53.0692031Z 2025-07-17T07:36:53.0692197Z [[ 0.5348, 0.0634, -2.0494], 2025-07-17T07:36:53.0692304Z [-0.7125, -1.0646, 2.1844]], 2025-07-17T07:36:53.0692381Z 2025-07-17T07:36:53.0692494Z [[ 0.1276, 0.1874, -0.6334], 2025-07-17T07:36:53.0692602Z [-1.9682, -0.5340, 0.7483]]]), 2025-07-17T07:36:53.0692747Z size=(5, 5, 2, 3), nnz=3, layout=torch.sparse_coo) 2025-07-17T07:36:53.0692835Z 2025-07-17T07:36:53.0693024Z # when sum over only part of sparse_dims, return a sparse tensor 2025-07-17T07:36:53.0693134Z >>> torch.sparse.sum(S, [1, 3]) 2025-07-17T07:36:53.0693257Z tensor(indices=tensor([[0, 2, 3]]), 2025-07-17T07:36:53.0693368Z values=tensor([[-1.4512, 0.4073], 2025-07-17T07:36:53.0693484Z [-0.8901, 0.2017], 2025-07-17T07:36:53.0693588Z [-0.3183, -1.7539]]), 2025-07-17T07:36:53.0693726Z size=(5, 2), nnz=3, layout=torch.sparse_coo) 2025-07-17T07:36:53.0693817Z 2025-07-17T07:36:53.0693964Z # when sum over all sparse dim, return a dense tensor 2025-07-17T07:36:53.0694065Z # with summed dims squeezed 2025-07-17T07:36:53.0694188Z >>> torch.sparse.sum(S, [0, 1, 3]) 2025-07-17T07:36:53.0694287Z tensor([-2.6596, -1.1450]) 2025-07-17T07:36:53.0694368Z 2025-07-17T07:36:53.0694632Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0694708Z 2025-07-17T07:36:53.0694817Z warnings.warn(msg) 2025-07-17T07:36:53.0694896Z 2025-07-17T07:36:53.0695080Z --- Parse Warning: 21 / 136 --- 2025-07-17T07:36:53.0695933Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=vmap in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=39. 2025-07-17T07:36:53.0696197Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0696274Z 2025-07-17T07:36:53.0696502Z vmap is the vectorizing map; ``vmap(func)`` returns a new function that 2025-07-17T07:36:53.0696698Z maps ``func`` over some dimension of the inputs. Semantically, vmap 2025-07-17T07:36:53.0696926Z pushes the map into PyTorch operations called by ``func``, effectively 2025-07-17T07:36:53.0697032Z vectorizing those operations. 2025-07-17T07:36:53.0697109Z 2025-07-17T07:36:53.0697328Z vmap is useful for handling batch dimensions: one can write a function 2025-07-17T07:36:53.0697525Z ``func`` that runs on examples and then lift it to a function that can 2025-07-17T07:36:53.0697775Z take batches of examples with ``vmap(func)``. vmap can also be used to 2025-07-17T07:36:53.0697956Z compute batched gradients when composed with autograd. 2025-07-17T07:36:53.0698034Z 2025-07-17T07:36:53.0698117Z .. note:: 2025-07-17T07:36:53.0698314Z :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for 2025-07-17T07:36:53.0698442Z convenience. Use whichever one you'd like. 2025-07-17T07:36:53.0698534Z 2025-07-17T07:36:53.0698615Z Args: 2025-07-17T07:36:53.0698824Z func (function): A Python function that takes one or more arguments. 2025-07-17T07:36:53.0698976Z Must return one or more Tensors. 2025-07-17T07:36:53.0699172Z in_dims (int or nested structure): Specifies which dimension of the 2025-07-17T07:36:53.0699342Z inputs should be mapped over. ``in_dims`` should have a 2025-07-17T07:36:53.0699547Z structure like the inputs. If the ``in_dim`` for a particular 2025-07-17T07:36:53.0699734Z input is None, then that indicates there is no map dimension. 2025-07-17T07:36:53.0699821Z Default: 0. 2025-07-17T07:36:53.0700021Z out_dims (int or Tuple[int]): Specifies where the mapped dimension 2025-07-17T07:36:53.0700276Z should appear in the outputs. If ``out_dims`` is a Tuple, then 2025-07-17T07:36:53.0700443Z it should have one element per output. Default: 0. 2025-07-17T07:36:53.0700625Z randomness (str): Specifies whether the randomness in this 2025-07-17T07:36:53.0700830Z vmap should be the same or different across batches. If 'different', 2025-07-17T07:36:53.0701039Z the randomness for each batch will be different. If 'same', the 2025-07-17T07:36:53.0701250Z randomness will be the same across batches. If 'error', any calls to 2025-07-17T07:36:53.0701468Z random functions will error. Default: 'error'. WARNING: this flag 2025-07-17T07:36:53.0701670Z only applies to random PyTorch operations and does not apply to 2025-07-17T07:36:53.0701802Z Python's random module or numpy randomness. 2025-07-17T07:36:53.0702073Z chunk_size (None or int): If None (default), apply a single vmap over inputs. 2025-07-17T07:36:53.0702289Z If not None, then compute the vmap :attr:`chunk_size` samples at a time. 2025-07-17T07:36:53.0702542Z Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop. 2025-07-17T07:36:53.0702817Z If you run into memory issues computing the vmap, please try a non-None chunk_size. 2025-07-17T07:36:53.0702897Z 2025-07-17T07:36:53.0702992Z Returns: 2025-07-17T07:36:53.0703178Z Returns a new "batched" function. It takes the same inputs as 2025-07-17T07:36:53.0703414Z ``func``, except each input has an extra dimension at the index 2025-07-17T07:36:53.0703615Z specified by ``in_dims``. It takes returns the same outputs as 2025-07-17T07:36:53.0703795Z ``func``, except each output has an extra dimension at the index 2025-07-17T07:36:53.0703898Z specified by ``out_dims``. 2025-07-17T07:36:53.0703987Z 2025-07-17T07:36:53.0704068Z .. warning: 2025-07-17T07:36:53.0704267Z :func:`vmap` works best with functional-style code. Please do not 2025-07-17T07:36:53.0704461Z perform any side-effects in ``func``, with the exception of 2025-07-17T07:36:53.0704692Z in-place PyTorch operations. Examples of side-effects include mutating 2025-07-17T07:36:53.0704926Z Python data structures and assigning values to variables not captured 2025-07-17T07:36:53.0705011Z in ``func``. 2025-07-17T07:36:53.0705089Z 2025-07-17T07:36:53.0705331Z One example of using :func:`vmap` is to compute batched dot products. PyTorch 2025-07-17T07:36:53.0705542Z doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully 2025-07-17T07:36:53.0705757Z rummaging through docs, use :func:`vmap` to construct a new function. 2025-07-17T07:36:53.0705871Z 2025-07-17T07:36:53.0705972Z >>> torch.dot # [D], [D] -> [] 2025-07-17T07:36:53.0706169Z >>> batched_dot = torch.func.vmap(torch.dot) # [N, D], [N, D] -> [N] 2025-07-17T07:36:53.0706306Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-07-17T07:36:53.0706400Z >>> batched_dot(x, y) 2025-07-17T07:36:53.0706489Z 2025-07-17T07:36:53.0706711Z :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler 2025-07-17T07:36:53.0706814Z model authoring experience. 2025-07-17T07:36:53.0706927Z 2025-07-17T07:36:53.0707035Z >>> batch_size, feature_size = 3, 5 2025-07-17T07:36:53.0707206Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-07-17T07:36:53.0707298Z >>> 2025-07-17T07:36:53.0707399Z >>> def model(feature_vec): 2025-07-17T07:36:53.0707527Z >>> # Very simple linear model with activation 2025-07-17T07:36:53.0707662Z >>> return feature_vec.dot(weights).relu() 2025-07-17T07:36:53.0707741Z >>> 2025-07-17T07:36:53.0707898Z >>> examples = torch.randn(batch_size, feature_size) 2025-07-17T07:36:53.0708016Z >>> result = torch.vmap(model)(examples) 2025-07-17T07:36:53.0708095Z 2025-07-17T07:36:53.0708402Z :func:`vmap` can also help vectorize computations that were previously difficult 2025-07-17T07:36:53.0708638Z or impossible to batch. One example is higher-order gradient computation. 2025-07-17T07:36:53.0708868Z The PyTorch autograd engine computes vjps (vector-Jacobian products). 2025-07-17T07:36:53.0709110Z Computing a full Jacobian matrix for some function f: R^N -> R^N usually 2025-07-17T07:36:53.0709357Z requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`, 2025-07-17T07:36:53.0709605Z we can vectorize the whole computation, computing the Jacobian in a single 2025-07-17T07:36:53.0709706Z call to ``autograd.grad``. 2025-07-17T07:36:53.0709789Z 2025-07-17T07:36:53.0709886Z >>> # Setup 2025-07-17T07:36:53.0709967Z >>> N = 5 2025-07-17T07:36:53.0710059Z >>> f = lambda x: x**2 2025-07-17T07:36:53.0710191Z >>> x = torch.randn(N, requires_grad=True) 2025-07-17T07:36:53.0710273Z >>> y = f(x) 2025-07-17T07:36:53.0710369Z >>> I_N = torch.eye(N) 2025-07-17T07:36:53.0710460Z >>> 2025-07-17T07:36:53.0710559Z >>> # Sequential approach 2025-07-17T07:36:53.0710771Z >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0] 2025-07-17T07:36:53.0710892Z >>> for v in I_N.unbind()] 2025-07-17T07:36:53.0711013Z >>> jacobian = torch.stack(jacobian_rows) 2025-07-17T07:36:53.0711103Z >>> 2025-07-17T07:36:53.0711219Z >>> # vectorized gradient computation 2025-07-17T07:36:53.0711310Z >>> def get_vjp(v): 2025-07-17T07:36:53.0711441Z >>> return torch.autograd.grad(y, x, v) 2025-07-17T07:36:53.0711558Z >>> jacobian = torch.vmap(get_vjp)(I_N) 2025-07-17T07:36:53.0711634Z 2025-07-17T07:36:53.0711903Z :func:`vmap` can also be nested, producing an output with multiple batched dimensions 2025-07-17T07:36:53.0711982Z 2025-07-17T07:36:53.0712083Z >>> torch.dot # [D], [D] -> [] 2025-07-17T07:36:53.0712203Z >>> batched_dot = torch.vmap( 2025-07-17T07:36:53.0712306Z ... torch.vmap(torch.dot) 2025-07-17T07:36:53.0712434Z ... ) # [N1, N0, D], [N1, N0, D] -> [N1, N0] 2025-07-17T07:36:53.0712568Z >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5) 2025-07-17T07:36:53.0712695Z >>> batched_dot(x, y) # tensor of size [2, 3] 2025-07-17T07:36:53.0712787Z 2025-07-17T07:36:53.0713026Z If the inputs are not batched along the first dimension, ``in_dims`` specifies 2025-07-17T07:36:53.0713178Z the dimension that each inputs are batched along as 2025-07-17T07:36:53.0713272Z 2025-07-17T07:36:53.0713377Z >>> torch.dot # [N], [N] -> [] 2025-07-17T07:36:53.0714159Z >>> batched_dot = torch.vmap(torch.dot, in_dims=1) # [N, D], [N, D] -> [D] 2025-07-17T07:36:53.0714299Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-07-17T07:36:53.0714389Z >>> batched_dot( 2025-07-17T07:36:53.0714487Z ... x, y 2025-07-17T07:36:53.0714681Z ... ) # output is [5] instead of [2] if batched along the 0th dimension 2025-07-17T07:36:53.0714760Z 2025-07-17T07:36:53.0715031Z If there are multiple inputs each of which is batched along different dimensions, 2025-07-17T07:36:53.0715224Z ``in_dims`` must be a tuple with the batch dimension for each input as 2025-07-17T07:36:53.0715330Z 2025-07-17T07:36:53.0715448Z >>> torch.dot # [D], [D] -> [] 2025-07-17T07:36:53.0715684Z >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None)) # [N, D], [D] -> [N] 2025-07-17T07:36:53.0715806Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-07-17T07:36:53.0715913Z >>> batched_dot( 2025-07-17T07:36:53.0715999Z ... x, y 2025-07-17T07:36:53.0716204Z ... ) # second arg doesn't have a batch dim because in_dim[1] was None 2025-07-17T07:36:53.0716285Z 2025-07-17T07:36:53.0716518Z If the input is a Python struct, ``in_dims`` must be a tuple containing a struct 2025-07-17T07:36:53.0716690Z matching the shape of the input: 2025-07-17T07:36:53.0716769Z 2025-07-17T07:36:53.0716905Z >>> f = lambda dict: torch.dot(dict["x"], dict["y"]) 2025-07-17T07:36:53.0717040Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-07-17T07:36:53.0717135Z >>> input = {"x": x, "y": y} 2025-07-17T07:36:53.0717314Z >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},)) 2025-07-17T07:36:53.0717424Z >>> batched_dot(input) 2025-07-17T07:36:53.0717504Z 2025-07-17T07:36:53.0717792Z By default, the output is batched along the first dimension. However, it can be batched 2025-07-17T07:36:53.0717913Z along any dimension by using ``out_dims`` 2025-07-17T07:36:53.0717992Z 2025-07-17T07:36:53.0718096Z >>> f = lambda x: x**2 2025-07-17T07:36:53.0718193Z >>> x = torch.randn(2, 5) 2025-07-17T07:36:53.0718340Z >>> batched_pow = torch.vmap(f, out_dims=1) 2025-07-17T07:36:53.0718453Z >>> batched_pow(x) # [5, 2] 2025-07-17T07:36:53.0718533Z 2025-07-17T07:36:53.0718824Z For any function that uses kwargs, the returned function will not batch the kwargs but will 2025-07-17T07:36:53.0718922Z accept kwargs 2025-07-17T07:36:53.0719003Z 2025-07-17T07:36:53.0719102Z >>> x = torch.randn([2, 5]) 2025-07-17T07:36:53.0719208Z >>> def fn(x, scale=4.): 2025-07-17T07:36:53.0719302Z >>> return x * scale 2025-07-17T07:36:53.0719392Z >>> 2025-07-17T07:36:53.0719497Z >>> batched_pow = torch.vmap(fn) 2025-07-17T07:36:53.0719634Z >>> assert torch.allclose(batched_pow(x), x * 4) 2025-07-17T07:36:53.0719865Z >>> batched_pow(x, scale=x) # scale is not batched, output has shape [2, 2, 5] 2025-07-17T07:36:53.0719944Z 2025-07-17T07:36:53.0720031Z .. note:: 2025-07-17T07:36:53.0720261Z vmap does not provide general autobatching or handle variable-length 2025-07-17T07:36:53.0720361Z sequences out of the box. 2025-07-17T07:36:53.0720438Z 2025-07-17T07:36:53.0720702Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0720779Z 2025-07-17T07:36:53.0720874Z warnings.warn(msg) 2025-07-17T07:36:53.0720963Z 2025-07-17T07:36:53.0721165Z --- Parse Warning: 22 / 136 --- 2025-07-17T07:36:53.0722026Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=grad in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=306. 2025-07-17T07:36:53.0722289Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0722552Z ``grad`` operator helps computing gradients of ``func`` with respect to the 2025-07-17T07:36:53.0722760Z input(s) specified by ``argnums``. This operator can be nested to 2025-07-17T07:36:53.0722872Z compute higher-order gradients. 2025-07-17T07:36:53.0722948Z 2025-07-17T07:36:53.0723045Z Args: 2025-07-17T07:36:53.0723258Z func (Callable): A Python function that takes one or more arguments. 2025-07-17T07:36:53.0723526Z Must return a single-element Tensor. If specified ``has_aux`` equals ``True``, 2025-07-17T07:36:53.0723789Z function can return a tuple of single-element Tensor and other auxiliary objects: 2025-07-17T07:36:53.0723917Z ``(output, aux)``. 2025-07-17T07:36:53.0724202Z argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to. 2025-07-17T07:36:53.0724402Z ``argnums`` can be single integer or tuple of integers. Default: 0. 2025-07-17T07:36:53.0724631Z has_aux (bool): Flag indicating that ``func`` returns a tensor and other 2025-07-17T07:36:53.0724792Z auxiliary objects: ``(output, aux)``. Default: False. 2025-07-17T07:36:53.0724871Z 2025-07-17T07:36:53.0724965Z Returns: 2025-07-17T07:36:53.0725400Z Function to compute gradients with respect to its inputs. By default, the output of 2025-07-17T07:36:53.0725640Z the function is the gradient tensor(s) with respect to the first argument. 2025-07-17T07:36:53.0725920Z If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects 2025-07-17T07:36:53.0726168Z is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with 2025-07-17T07:36:53.0726310Z respect to each ``argnums`` value is returned. 2025-07-17T07:36:53.0726419Z 2025-07-17T07:36:53.0726520Z Example of using ``grad``: 2025-07-17T07:36:53.0726612Z 2025-07-17T07:36:53.0726709Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0726820Z >>> from torch.func import grad 2025-07-17T07:36:53.0726931Z >>> x = torch.randn([]) 2025-07-17T07:36:53.0727055Z >>> cos_x = grad(lambda x: torch.sin(x))(x) 2025-07-17T07:36:53.0727179Z >>> assert torch.allclose(cos_x, x.cos()) 2025-07-17T07:36:53.0727278Z >>> 2025-07-17T07:36:53.0727381Z >>> # Second-order gradients 2025-07-17T07:36:53.0727524Z >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x) 2025-07-17T07:36:53.0727671Z >>> assert torch.allclose(neg_sin_x, -x.sin()) 2025-07-17T07:36:53.0727752Z 2025-07-17T07:36:53.0728010Z When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients: 2025-07-17T07:36:53.0728090Z 2025-07-17T07:36:53.0728186Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0728317Z >>> from torch.func import grad, vmap 2025-07-17T07:36:53.0728429Z >>> batch_size, feature_size = 3, 5 2025-07-17T07:36:53.0728512Z >>> 2025-07-17T07:36:53.0728638Z >>> def model(weights, feature_vec): 2025-07-17T07:36:53.0728767Z >>> # Very simple linear model with activation 2025-07-17T07:36:53.0728878Z >>> assert feature_vec.dim() == 1 2025-07-17T07:36:53.0729016Z >>> return feature_vec.dot(weights).relu() 2025-07-17T07:36:53.0729096Z >>> 2025-07-17T07:36:53.0729242Z >>> def compute_loss(weights, example, target): 2025-07-17T07:36:53.0729350Z >>> y = model(weights, example) 2025-07-17T07:36:53.0729477Z >>> return ((y - target) ** 2).mean() # MSELoss 2025-07-17T07:36:53.0729573Z >>> 2025-07-17T07:36:53.0729745Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-07-17T07:36:53.0729890Z >>> examples = torch.randn(batch_size, feature_size) 2025-07-17T07:36:53.0730016Z >>> targets = torch.randn(batch_size) 2025-07-17T07:36:53.0730168Z >>> inputs = (weights, examples, targets) 2025-07-17T07:36:53.0730396Z >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))( 2025-07-17T07:36:53.0730495Z ... *inputs 2025-07-17T07:36:53.0730576Z ... ) 2025-07-17T07:36:53.0730716Z 2025-07-17T07:36:53.0730891Z Example of using ``grad`` with ``has_aux`` and ``argnums``: 2025-07-17T07:36:53.0730969Z 2025-07-17T07:36:53.0731078Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0731187Z >>> from torch.func import grad 2025-07-17T07:36:53.0731294Z >>> def my_loss_func(y, y_pred): 2025-07-17T07:36:53.0731459Z >>> loss_per_sample = (0.5 * y_pred - y) ** 2 2025-07-17T07:36:53.0731575Z >>> loss = loss_per_sample.mean() 2025-07-17T07:36:53.0731696Z >>> return loss, (y_pred, loss_per_sample) 2025-07-17T07:36:53.0731786Z >>> 2025-07-17T07:36:53.0731931Z >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True) 2025-07-17T07:36:53.0732048Z >>> y_true = torch.rand(4) 2025-07-17T07:36:53.0732178Z >>> y_preds = torch.rand(4, requires_grad=True) 2025-07-17T07:36:53.0732283Z >>> out = fn(y_true, y_preds) 2025-07-17T07:36:53.0732585Z >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample)) 2025-07-17T07:36:53.0732663Z 2025-07-17T07:36:53.0732752Z .. note:: 2025-07-17T07:36:53.0732928Z Using PyTorch ``torch.no_grad`` together with ``grad``. 2025-07-17T07:36:53.0733005Z 2025-07-17T07:36:53.0733150Z Case 1: Using ``torch.no_grad`` inside a function: 2025-07-17T07:36:53.0733237Z 2025-07-17T07:36:53.0733335Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0733433Z >>> def f(x): 2025-07-17T07:36:53.0733536Z >>> with torch.no_grad(): 2025-07-17T07:36:53.0733627Z >>> c = x ** 2 2025-07-17T07:36:53.0733731Z >>> return x - c 2025-07-17T07:36:53.0733808Z 2025-07-17T07:36:53.0734002Z In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``. 2025-07-17T07:36:53.0734091Z 2025-07-17T07:36:53.0734269Z Case 2: Using ``grad`` inside ``torch.no_grad`` context manager: 2025-07-17T07:36:53.0734350Z 2025-07-17T07:36:53.0734460Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0734561Z >>> with torch.no_grad(): 2025-07-17T07:36:53.0734652Z >>> grad(f)(x) 2025-07-17T07:36:53.0734740Z 2025-07-17T07:36:53.0734958Z In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the 2025-07-17T07:36:53.0735188Z outer one. This is because ``grad`` is a "function transform": its result 2025-07-17T07:36:53.0735407Z should not depend on the result of a context manager outside of ``f``. 2025-07-17T07:36:53.0735485Z 2025-07-17T07:36:53.0735580Z 2025-07-17T07:36:53.0735833Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0735912Z 2025-07-17T07:36:53.0736026Z warnings.warn(msg) 2025-07-17T07:36:53.0736107Z 2025-07-17T07:36:53.0736317Z --- Parse Warning: 23 / 136 --- 2025-07-17T07:36:53.0737311Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CustomOpDef.register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py line=396. 2025-07-17T07:36:53.0737558Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:53.0737757Z Register a FakeTensor implementation for this custom op. 2025-07-17T07:36:53.0737835Z 2025-07-17T07:36:53.0738079Z This is necessary to get the operator to work efficiently with torch.compile. 2025-07-17T07:36:53.0738170Z 2025-07-17T07:36:53.0738384Z The Fake impl (sometimes also known as a meta kernel or abstract impl) 2025-07-17T07:36:53.0738640Z specifies the behavior of this operator on Tensors that carry no data. 2025-07-17T07:36:53.0738804Z Given some input Tensors with certain properties 2025-07-17T07:36:53.0739064Z (sizes/strides/storage_offset/device), it specifies what the properties of 2025-07-17T07:36:53.0739177Z the output Tensors are. 2025-07-17T07:36:53.0739255Z 2025-07-17T07:36:53.0739476Z Please see :func:`torch.library.impl_abstract` for more details. 2025-07-17T07:36:53.0739564Z 2025-07-17T07:36:53.0739680Z Args: 2025-07-17T07:36:53.0739851Z fn (Callable): The function to register as the FakeTensor 2025-07-17T07:36:53.0739962Z implementation. 2025-07-17T07:36:53.0740039Z 2025-07-17T07:36:53.0740125Z Examples: 2025-07-17T07:36:53.0740229Z >>> import torch 2025-07-17T07:36:53.0740342Z >>> import numpy as np 2025-07-17T07:36:53.0740464Z >>> from torch import Tensor 2025-07-17T07:36:53.0740547Z >>> 2025-07-17T07:36:53.0740735Z >>> # Example 1: an operator without data-dependent output shape 2025-07-17T07:36:53.0740986Z >>> @torch.library.custom_op("mylib::linear", mutates_args=()) 2025-07-17T07:36:53.0741178Z >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-07-17T07:36:53.0741294Z >>> return (x @ weight.t()) + bias 2025-07-17T07:36:53.0741389Z >>> 2025-07-17T07:36:53.0741494Z >>> @linear.register_fake 2025-07-17T07:36:53.0741599Z >>> def _(x, weight, bias): 2025-07-17T07:36:53.0741712Z >>> assert x.dim() == 2 2025-07-17T07:36:53.0741824Z >>> assert weight.dim() == 2 2025-07-17T07:36:53.0741943Z >>> assert bias.dim() == 1 2025-07-17T07:36:53.0742067Z >>> assert x.shape[1] == weight.shape[1] 2025-07-17T07:36:53.0742200Z >>> assert weight.shape[0] == bias.shape[0] 2025-07-17T07:36:53.0742335Z >>> assert x.device == weight.device 2025-07-17T07:36:53.0742479Z >>> return x.new_empty(x.size(0), weight.size(0)) 2025-07-17T07:36:53.0742565Z >>> 2025-07-17T07:36:53.0742685Z >>> x = torch.randn(2, 2) 2025-07-17T07:36:53.0742798Z >>> weight = torch.randn(2, 2) 2025-07-17T07:36:53.0742914Z >>> bias = torch.randn(2) 2025-07-17T07:36:53.0743050Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-07-17T07:36:53.0743240Z >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias) 2025-07-17T07:36:53.0743387Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-07-17T07:36:53.0743635Z >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias)) 2025-07-17T07:36:53.0743720Z >>> 2025-07-17T07:36:53.0743909Z >>> # Example 2: an operator with data-dependent output shape 2025-07-17T07:36:53.0744108Z >>> @torch.library.custom_op("mylib::nonzero", mutates_args=()) 2025-07-17T07:36:53.0744241Z >>> def nonzero(x: Tensor) -> Tensor: 2025-07-17T07:36:53.0744351Z >>> x_np = x.cpu().numpy() 2025-07-17T07:36:53.0744482Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-07-17T07:36:53.0744625Z >>> return torch.tensor(res, device=x.device) 2025-07-17T07:36:53.0744708Z >>> 2025-07-17T07:36:53.0744816Z >>> @nonzero.register_fake 2025-07-17T07:36:53.0744920Z >>> def _(x): 2025-07-17T07:36:53.0745069Z >>> # Number of nonzero-elements is data-dependent. 2025-07-17T07:36:53.0745233Z >>> # Since we cannot peek at the data in an abstract impl, 2025-07-17T07:36:53.0745401Z >>> # we use the ctx object to construct a new symint that 2025-07-17T07:36:53.0745561Z >>> # represents the data-dependent size. 2025-07-17T07:36:53.0745692Z >>> ctx = torch.library.get_ctx() 2025-07-17T07:36:53.0745807Z >>> nnz = ctx.new_dynamic_size() 2025-07-17T07:36:53.0745916Z >>> shape = [nnz, x.dim()] 2025-07-17T07:36:53.0746072Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-07-17T07:36:53.0746167Z >>> return result 2025-07-17T07:36:53.0746245Z >>> 2025-07-17T07:36:53.0746368Z >>> x = torch.tensor([0, 1, 2, 0, 0, 1]) 2025-07-17T07:36:53.0746526Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-07-17T07:36:53.0746680Z >>> out = torch.compile(nonzero, fullgraph=True)(x) 2025-07-17T07:36:53.0746809Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-07-17T07:36:53.0746936Z >>> assert torch.allclose(out, x.nonzero()) 2025-07-17T07:36:53.0747028Z 2025-07-17T07:36:53.0747106Z 2025-07-17T07:36:53.0747638Z Original Error: IndentationError('expected an indented block after function definition on line 36', ('', 37, 1, '_._ = None\n', 37, 2)) 2025-07-17T07:36:53.0747728Z 2025-07-17T07:36:53.0747860Z _._ = None 2025-07-17T07:36:53.0747940Z ^ 2025-07-17T07:36:53.0748046Z warnings.warn(msg) 2025-07-17T07:36:53.0748123Z 2025-07-17T07:36:53.0748321Z --- Parse Warning: 24 / 136 --- 2025-07-17T07:36:53.0749314Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_profile.py line=94. 2025-07-17T07:36:53.0749577Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0749668Z 2025-07-17T07:36:53.0749895Z Registers a fake kernel based on the given operator profiles. This fake 2025-07-17T07:36:53.0750139Z kernel registration will override any existing fake kernel registrations. 2025-07-17T07:36:53.0750228Z 2025-07-17T07:36:53.0750436Z The input is a dictionary mapping operator names to a set of operator 2025-07-17T07:36:53.0750684Z profiles, which we will use to generate fake kernels. The operator profiles 2025-07-17T07:36:53.0750879Z are a record of the input and output tensor metadata. Based on this 2025-07-17T07:36:53.0751116Z information we will match a given input to the recorded profile, and return 2025-07-17T07:36:53.0751353Z an output with the same metadata as in the recorded profile. If a profile 2025-07-17T07:36:53.0751490Z doesn't exist then an exception will be thrown. 2025-07-17T07:36:53.0751568Z 2025-07-17T07:36:53.0751810Z The fake kernel generation is considered unsafe because it relies on the 2025-07-17T07:36:53.0752035Z rigid, pre-defined operator profiles that do not account for potential 2025-07-17T07:36:53.0752299Z variations in output behavior. Specifically, the generated kernels assume a 2025-07-17T07:36:53.0752549Z fixed relationship between input and output ranks. However, in reality, it's 2025-07-17T07:36:53.0752789Z possible that data-dependent operations may produce outputs of different 2025-07-17T07:36:53.0753022Z ranks even when given inputs of the same rank. The generated fake kernels 2025-07-17T07:36:53.0753237Z are inflexible and unable to accommodate these nuances, making them 2025-07-17T07:36:53.0753336Z potentially unsafe. 2025-07-17T07:36:53.0753424Z 2025-07-17T07:36:53.0753506Z Args: 2025-07-17T07:36:53.0753720Z op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator 2025-07-17T07:36:53.0753927Z name to a set of operator profiles from which we will generate fake 2025-07-17T07:36:53.0754011Z kernels. 2025-07-17T07:36:53.0754101Z 2025-07-17T07:36:53.0754213Z Examples: 2025-07-17T07:36:53.0754292Z 2025-07-17T07:36:53.0754470Z >>> # Example: Registering an op-profile from draft-export 2025-07-17T07:36:53.0754559Z >>> import torch 2025-07-17T07:36:53.0754719Z >>> from torch.export._draft_export import draft_export 2025-07-17T07:36:53.0754808Z >>> 2025-07-17T07:36:53.0754988Z >>> @torch.library.custom_op("mylib::foo", mutates_args=()) 2025-07-17T07:36:53.0755112Z >>> def foo(x: Tensor, y: Tensor) -> Tensor: 2025-07-17T07:36:53.0755217Z >>> return x + y 2025-07-17T07:36:53.0755296Z >>> 2025-07-17T07:36:53.0755432Z >>> class M(torch.nn.Module): 2025-07-17T07:36:53.0755547Z >>> def forward(self, a, b): 2025-07-17T07:36:53.0755689Z >>> res = torch.ops.mylib.foo(a, b) # no fake impl 2025-07-17T07:36:53.0755795Z >>> return res 2025-07-17T07:36:53.0755875Z >>> 2025-07-17T07:36:53.0756043Z >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4)) 2025-07-17T07:36:53.0756136Z >>> 2025-07-17T07:36:53.0756433Z >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles): 2025-07-17T07:36:53.0756554Z >>> decomp = ep.run_decompositions() 2025-07-17T07:36:53.0756644Z 2025-07-17T07:36:53.0756782Z 2025-07-17T07:36:53.0757038Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0757157Z 2025-07-17T07:36:53.0757277Z warnings.warn(msg) 2025-07-17T07:36:53.0757389Z 2025-07-17T07:36:53.0757686Z --- Parse Warning: 25 / 136 --- 2025-07-17T07:36:53.0758574Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=triton_op in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=21. 2025-07-17T07:36:53.0758850Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0759103Z Create a custom operator whose implementation is backed by 1+ triton kernels. 2025-07-17T07:36:53.0759180Z 2025-07-17T07:36:53.0759398Z This is a more structured way of using triton kernels with PyTorch. 2025-07-17T07:36:53.0759654Z Prefer using triton kernels with no ``torch.library`` custom operator wrappers 2025-07-17T07:36:53.0759916Z (like :func:`torch.library.custom_op`, :func:`torch.library.triton_op`) because 2025-07-17T07:36:53.0760008Z that is simpler; 2025-07-17T07:36:53.0760258Z only use :func:`torch.library.custom_op`/:func:`torch.library.triton_op` if you 2025-07-17T07:36:53.0760496Z want to create an operator that behaves like PyTorch built-in operators. 2025-07-17T07:36:53.0760704Z For example, you may use a ``torch.library`` wrapper API to define the 2025-07-17T07:36:53.0760918Z behavior of the triton kernel when passed a tensor subclass or under 2025-07-17T07:36:53.0761028Z a TorchDispatchMode. 2025-07-17T07:36:53.0761109Z 2025-07-17T07:36:53.0761366Z Use :func:`torch.library.triton_op` instead of :func:`torch.library.custom_op` 2025-07-17T07:36:53.0761466Z when the implementation 2025-07-17T07:36:53.0761680Z consists of 1+ triton kernels. :func:`torch.library.custom_op` treats 2025-07-17T07:36:53.0761862Z custom operators as opaque (:func:`torch.compile` and 2025-07-17T07:36:53.0762094Z :func:`torch.export.export` will never trace into them), but ``triton_op`` 2025-07-17T07:36:53.0762311Z makes the implementation visible to these subsystems, allowing them 2025-07-17T07:36:53.0762435Z to optimize the triton kernel(s). 2025-07-17T07:36:53.0762514Z 2025-07-17T07:36:53.0762701Z Note that ``fn`` must only consist of calls to PyTorch-understood 2025-07-17T07:36:53.0762964Z operators and triton kernels. Any triton kernels called inside ``fn`` 2025-07-17T07:36:53.0763156Z must be wrapped in a call to :func:`torch.library.wrap_triton`. 2025-07-17T07:36:53.0763298Z 2025-07-17T07:36:53.0763404Z Args: 2025-07-17T07:36:53.0763628Z name (str): A name for the custom op that looks like "{namespace}::{name}", 2025-07-17T07:36:53.0763849Z e.g. "mylib::my_linear". The name is used as the op's stable identifier 2025-07-17T07:36:53.0764019Z in PyTorch subsystems (e.g. torch.export, FX graphs). 2025-07-17T07:36:53.0764267Z To avoid name collisions, please use your project name as the namespace; 2025-07-17T07:36:53.0764467Z e.g. all custom ops in pytorch/fbgemm use "fbgemm" as the namespace. 2025-07-17T07:36:53.0764766Z mutates_args (Iterable[str] or "unknown"): The names of args that the function mutates. 2025-07-17T07:36:53.0765010Z This MUST be accurate, otherwise, the behavior is undefined. If "unknown", 2025-07-17T07:36:53.0765270Z it pessimistically assumes that all inputs to the operator are being mutated. 2025-07-17T07:36:53.0765533Z schema (None | str): A schema string for the operator. If None 2025-07-17T07:36:53.0765750Z (recommended) we'll infer a schema for the operator from its type 2025-07-17T07:36:53.0765951Z annotations. We recommend letting us infer a schema unless you 2025-07-17T07:36:53.0766133Z have a specific reason not to. 2025-07-17T07:36:53.0766281Z Example: "(Tensor x, int y) -> (Tensor, Tensor)". 2025-07-17T07:36:53.0766357Z 2025-07-17T07:36:53.0766458Z Example:: 2025-07-17T07:36:53.0766535Z 2025-07-17T07:36:53.0766672Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:53.0766777Z >>> import torch 2025-07-17T07:36:53.0766928Z >>> from torch.library import triton_op, wrap_triton 2025-07-17T07:36:53.0767008Z >>> 2025-07-17T07:36:53.0767112Z >>> import triton 2025-07-17T07:36:53.0767234Z >>> from triton import language as tl 2025-07-17T07:36:53.0767331Z >>> 2025-07-17T07:36:53.0767421Z >>> @triton.jit 2025-07-17T07:36:53.0767516Z >>> def add_kernel( 2025-07-17T07:36:53.0767617Z >>> in_ptr0, 2025-07-17T07:36:53.0767702Z >>> in_ptr1, 2025-07-17T07:36:53.0767794Z >>> out_ptr, 2025-07-17T07:36:53.0767898Z >>> n_elements, 2025-07-17T07:36:53.0768010Z >>> BLOCK_SIZE: "tl.constexpr", 2025-07-17T07:36:53.0768094Z >>> ): 2025-07-17T07:36:53.0768218Z >>> pid = tl.program_id(axis=0) 2025-07-17T07:36:53.0768333Z >>> block_start = pid * BLOCK_SIZE 2025-07-17T07:36:53.0768480Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-07-17T07:36:53.0768597Z >>> mask = offsets < n_elements 2025-07-17T07:36:53.0768724Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-07-17T07:36:53.0768850Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-07-17T07:36:53.0779954Z >>> output = x + y 2025-07-17T07:36:53.0780154Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-07-17T07:36:53.0780237Z >>> 2025-07-17T07:36:53.0780418Z >>> @triton_op("mylib::add", mutates_args={}) 2025-07-17T07:36:53.0780620Z >>> def add(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor: 2025-07-17T07:36:53.0780752Z >>> output = torch.empty_like(x) 2025-07-17T07:36:53.0780870Z >>> n_elements = output.numel() 2025-07-17T07:36:53.0780954Z >>> 2025-07-17T07:36:53.0781072Z >>> def grid(meta): 2025-07-17T07:36:53.0781241Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-07-17T07:36:53.0781323Z >>> 2025-07-17T07:36:53.0781518Z >>> # NB: we need to wrap the triton kernel in a call to wrap_triton 2025-07-17T07:36:53.0781705Z >>> wrap_triton(add_kernel)[grid](x, y, output, n_elements, 16) 2025-07-17T07:36:53.0781996Z >>> return output 2025-07-17T07:36:53.0782078Z >>> 2025-07-17T07:36:53.0782174Z >>> @torch.compile 2025-07-17T07:36:53.0782281Z >>> def f(x, y): 2025-07-17T07:36:53.0782378Z >>> return add(x, y) 2025-07-17T07:36:53.0782464Z >>> 2025-07-17T07:36:53.0782592Z >>> x = torch.randn(3, device="cuda") 2025-07-17T07:36:53.0782701Z >>> y = torch.randn(3, device="cuda") 2025-07-17T07:36:53.0782781Z >>> 2025-07-17T07:36:53.0782880Z >>> z = f(x, y) 2025-07-17T07:36:53.0783035Z >>> assert torch.allclose(z, x + y) 2025-07-17T07:36:53.0783114Z 2025-07-17T07:36:53.0783207Z 2025-07-17T07:36:53.0783460Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0783550Z 2025-07-17T07:36:53.0783643Z warnings.warn(msg) 2025-07-17T07:36:53.0783722Z 2025-07-17T07:36:53.0783976Z --- Parse Warning: 26 / 136 --- 2025-07-17T07:36:53.0784860Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=wrap_triton in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=202. 2025-07-17T07:36:53.0785209Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0785411Z Allows capture of a triton kernel into a graph via make_fx or 2025-07-17T07:36:53.0785520Z non-strict ``torch.export``. 2025-07-17T07:36:53.0785614Z 2025-07-17T07:36:53.0785797Z These technologies perform Dispatcher-based tracing (via 2025-07-17T07:36:53.0785993Z ``__torch_dispatch__``) and cannot see calls to raw triton kernels. 2025-07-17T07:36:53.0786201Z The ``wrap_triton`` API wraps a triton kernel into a callable that 2025-07-17T07:36:53.0786315Z can actually be traced into a graph. 2025-07-17T07:36:53.0786397Z 2025-07-17T07:36:53.0786617Z Please use this API together with :func:`torch.library.triton_op`. 2025-07-17T07:36:53.0786694Z 2025-07-17T07:36:53.0786781Z Examples: 2025-07-17T07:36:53.0786872Z 2025-07-17T07:36:53.0786968Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0787066Z >>> import torch 2025-07-17T07:36:53.0787168Z >>> import triton 2025-07-17T07:36:53.0787285Z >>> from triton import language as tl 2025-07-17T07:36:53.0787475Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-07-17T07:36:53.0787601Z >>> from torch.library import wrap_triton 2025-07-17T07:36:53.0787681Z >>> 2025-07-17T07:36:53.0787785Z >>> @triton.jit 2025-07-17T07:36:53.0787876Z >>> def add_kernel( 2025-07-17T07:36:53.0787963Z >>> in_ptr0, 2025-07-17T07:36:53.0788063Z >>> in_ptr1, 2025-07-17T07:36:53.0788147Z >>> out_ptr, 2025-07-17T07:36:53.0788237Z >>> n_elements, 2025-07-17T07:36:53.0788359Z >>> BLOCK_SIZE: "tl.constexpr", 2025-07-17T07:36:53.0788438Z >>> ): 2025-07-17T07:36:53.0788562Z >>> pid = tl.program_id(axis=0) 2025-07-17T07:36:53.0788673Z >>> block_start = pid * BLOCK_SIZE 2025-07-17T07:36:53.0788820Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-07-17T07:36:53.0788939Z >>> mask = offsets < n_elements 2025-07-17T07:36:53.0789065Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-07-17T07:36:53.0789191Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-07-17T07:36:53.0789302Z >>> output = x + y 2025-07-17T07:36:53.0789444Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-07-17T07:36:53.0789525Z >>> 2025-07-17T07:36:53.0789631Z >>> def add(x, y): 2025-07-17T07:36:53.0789743Z >>> output = torch.empty_like(x) 2025-07-17T07:36:53.0789895Z >>> n_elements = output.numel() 2025-07-17T07:36:53.0789976Z >>> 2025-07-17T07:36:53.0790075Z >>> def grid_fn(meta): 2025-07-17T07:36:53.0790256Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-07-17T07:36:53.0790341Z >>> 2025-07-17T07:36:53.0790536Z >>> wrap_triton(add_kernel)[grid_fn](x, y, output, n_elements, 16) 2025-07-17T07:36:53.0790644Z >>> return output 2025-07-17T07:36:53.0790723Z >>> 2025-07-17T07:36:53.0790838Z >>> x = torch.randn(3, device="cuda") 2025-07-17T07:36:53.0790988Z >>> y = torch.randn(3, device="cuda") 2025-07-17T07:36:53.0791090Z >>> gm = make_fx(add)(x, y) 2025-07-17T07:36:53.0791198Z >>> print(gm.code) 2025-07-17T07:36:53.0791308Z >>> # def forward(self, x_1, y_1): 2025-07-17T07:36:53.0791586Z >>> # empty_like = torch.ops.aten.empty_like.default(x_1, pin_memory = False) 2025-07-17T07:36:53.0791844Z >>> # triton_kernel_wrapper_mutation_proxy = triton_kernel_wrapper_mutation( 2025-07-17T07:36:53.0791971Z >>> # kernel_idx = 0, constant_args_idx = 0, 2025-07-17T07:36:53.0792130Z >>> # grid = [(1, 1, 1)], kwargs = { 2025-07-17T07:36:53.0792295Z >>> # 'in_ptr0': x_1, 'in_ptr1': y_1, 'out_ptr': empty_like, 2025-07-17T07:36:53.0792415Z >>> # 'n_elements': 3, 'BLOCK_SIZE': 16 2025-07-17T07:36:53.0792514Z >>> # }) 2025-07-17T07:36:53.0792613Z >>> # return empty_like 2025-07-17T07:36:53.0792690Z 2025-07-17T07:36:53.0792782Z 2025-07-17T07:36:53.0793034Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0793111Z 2025-07-17T07:36:53.0793220Z warnings.warn(msg) 2025-07-17T07:36:53.0793298Z 2025-07-17T07:36:53.0793495Z --- Parse Warning: 27 / 136 --- 2025-07-17T07:36:53.0794446Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=print_assert_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=286. 2025-07-17T07:36:53.0794713Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0794806Z 2025-07-17T07:36:53.0795023Z Test if two objects are equal, and print an error message if test fails. 2025-07-17T07:36:53.0795101Z 2025-07-17T07:36:53.0795258Z The test is performed with ``actual == desired``. 2025-07-17T07:36:53.0795338Z 2025-07-17T07:36:53.0795425Z Parameters 2025-07-17T07:36:53.0795523Z ---------- 2025-07-17T07:36:53.0795614Z test_string : str 2025-07-17T07:36:53.0795739Z The message supplied to AssertionError. 2025-07-17T07:36:53.0795838Z actual : object 2025-07-17T07:36:53.0795986Z The object to test for equality against `desired`. 2025-07-17T07:36:53.0796075Z desired : object 2025-07-17T07:36:53.0796182Z The expected result. 2025-07-17T07:36:53.0796299Z 2025-07-17T07:36:53.0796382Z Examples 2025-07-17T07:36:53.0796478Z -------- 2025-07-17T07:36:53.0796587Z >>> np.testing.print_assert_equal( 2025-07-17T07:36:53.0796716Z ... "Test XYZ of func xyz", [0, 1], [0, 1] 2025-07-17T07:36:53.0796811Z ... ) # doctest: +SKIP 2025-07-17T07:36:53.0796920Z >>> np.testing.print_assert_equal( 2025-07-17T07:36:53.0797049Z ... "Test XYZ of func xyz", [0, 1], [0, 2] 2025-07-17T07:36:53.0797144Z ... ) # doctest: +SKIP 2025-07-17T07:36:53.0797251Z Traceback (most recent call last): 2025-07-17T07:36:53.0797346Z ... 2025-07-17T07:36:53.0797473Z AssertionError: Test XYZ of func xyz failed 2025-07-17T07:36:53.0797555Z ACTUAL: 2025-07-17T07:36:53.0797650Z [0, 1] 2025-07-17T07:36:53.0797734Z DESIRED: 2025-07-17T07:36:53.0797845Z [0, 2] 2025-07-17T07:36:53.0797935Z 2025-07-17T07:36:53.0798013Z 2025-07-17T07:36:53.0798279Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0798356Z 2025-07-17T07:36:53.0798450Z warnings.warn(msg) 2025-07-17T07:36:53.0798541Z 2025-07-17T07:36:53.0798726Z --- Parse Warning: 28 / 136 --- 2025-07-17T07:36:53.0799661Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=331. 2025-07-17T07:36:53.0799983Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0800061Z 2025-07-17T07:36:53.0800269Z Raises an AssertionError if two items are not equal up to desired 2025-07-17T07:36:53.0800364Z precision. 2025-07-17T07:36:53.0800442Z 2025-07-17T07:36:53.0800622Z .. note:: It is recommended to use one of `assert_allclose`, 2025-07-17T07:36:53.0800800Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-07-17T07:36:53.0800985Z instead of this function for more consistent floating point 2025-07-17T07:36:53.0801089Z comparisons. 2025-07-17T07:36:53.0801166Z 2025-07-17T07:36:53.0801427Z The test verifies that the elements of `actual` and `desired` satisfy. 2025-07-17T07:36:53.0801521Z 2025-07-17T07:36:53.0801679Z ``abs(desired-actual) < float64(1.5 * 10**(-decimal))`` 2025-07-17T07:36:53.0801758Z 2025-07-17T07:36:53.0801997Z That is a looser test than originally documented, but agrees with what the 2025-07-17T07:36:53.0802231Z actual implementation in `assert_array_almost_equal` did up to rounding 2025-07-17T07:36:53.0802477Z vagaries. An exception is raised at conflicting values. For ndarrays this 2025-07-17T07:36:53.0802593Z delegates to assert_array_almost_equal 2025-07-17T07:36:53.0802672Z 2025-07-17T07:36:53.0802771Z Parameters 2025-07-17T07:36:53.0802855Z ---------- 2025-07-17T07:36:53.0802946Z actual : array_like 2025-07-17T07:36:53.0803055Z The object to check. 2025-07-17T07:36:53.0803148Z desired : array_like 2025-07-17T07:36:53.0803243Z The expected object. 2025-07-17T07:36:53.0803356Z decimal : int, optional 2025-07-17T07:36:53.0803469Z Desired precision, default is 7. 2025-07-17T07:36:53.0803577Z err_msg : str, optional 2025-07-17T07:36:53.0803730Z The error message to be printed in case of failure. 2025-07-17T07:36:53.0803835Z verbose : bool, optional 2025-07-17T07:36:53.0804051Z If True, the conflicting values are appended to the error message. 2025-07-17T07:36:53.0804129Z 2025-07-17T07:36:53.0804210Z Raises 2025-07-17T07:36:53.0804307Z ------ 2025-07-17T07:36:53.0804396Z AssertionError 2025-07-17T07:36:53.0804591Z If actual and desired are not equal up to specified precision. 2025-07-17T07:36:53.0804684Z 2025-07-17T07:36:53.0804765Z See Also 2025-07-17T07:36:53.0804847Z -------- 2025-07-17T07:36:53.0805094Z assert_allclose: Compare two array_like objects for equality with desired 2025-07-17T07:36:53.0805219Z relative and/or absolute precision. 2025-07-17T07:36:53.0805530Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-07-17T07:36:53.0805611Z 2025-07-17T07:36:53.0805695Z Examples 2025-07-17T07:36:53.0805791Z -------- 2025-07-17T07:36:53.0805952Z >>> from torch._numpy.testing import assert_almost_equal 2025-07-17T07:36:53.0806082Z >>> assert_almost_equal(2.3333333333333, 2.33333334) 2025-07-17T07:36:53.0806271Z >>> assert_almost_equal(2.3333333333333, 2.33333334, decimal=10) 2025-07-17T07:36:53.0806380Z Traceback (most recent call last): 2025-07-17T07:36:53.0806460Z ... 2025-07-17T07:36:53.0806563Z AssertionError: 2025-07-17T07:36:53.0806687Z Arrays are not almost equal to 10 decimals 2025-07-17T07:36:53.0806813Z ACTUAL: 2.3333333333333 2025-07-17T07:36:53.0806913Z DESIRED: 2.33333334 2025-07-17T07:36:53.0806995Z 2025-07-17T07:36:53.0807104Z >>> assert_almost_equal( 2025-07-17T07:36:53.0807302Z ... np.array([1.0, 2.3333333333333]), np.array([1.0, 2.33333334]), decimal=9 2025-07-17T07:36:53.0807387Z ... ) 2025-07-17T07:36:53.0807512Z Traceback (most recent call last): 2025-07-17T07:36:53.0807593Z ... 2025-07-17T07:36:53.0807683Z AssertionError: 2025-07-17T07:36:53.0807817Z Arrays are not almost equal to 9 decimals 2025-07-17T07:36:53.0807903Z 2025-07-17T07:36:53.0808034Z Mismatched elements: 1 / 2 (50%) 2025-07-17T07:36:53.0808178Z Max absolute difference: 6.666699636781459e-09 2025-07-17T07:36:53.0808306Z Max relative difference: 2.8571569790287484e-09 2025-07-17T07:36:53.0808439Z x: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-07-17T07:36:53.0808583Z y: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-07-17T07:36:53.0808662Z 2025-07-17T07:36:53.0808754Z 2025-07-17T07:36:53.0809006Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0809084Z 2025-07-17T07:36:53.0809192Z warnings.warn(msg) 2025-07-17T07:36:53.0809269Z 2025-07-17T07:36:53.0809525Z --- Parse Warning: 29 / 136 --- 2025-07-17T07:36:53.0810476Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_approx_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=457. 2025-07-17T07:36:53.0810741Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0810834Z 2025-07-17T07:36:53.0811057Z Raises an AssertionError if two items are not equal up to significant 2025-07-17T07:36:53.0811136Z digits. 2025-07-17T07:36:53.0811228Z 2025-07-17T07:36:53.0811400Z .. note:: It is recommended to use one of `assert_allclose`, 2025-07-17T07:36:53.0811582Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-07-17T07:36:53.0811779Z instead of this function for more consistent floating point 2025-07-17T07:36:53.0811873Z comparisons. 2025-07-17T07:36:53.0811950Z 2025-07-17T07:36:53.0812151Z Given two numbers, check that they are approximately equal. 2025-07-17T07:36:53.0812371Z Approximately equal is defined as the number of significant digits 2025-07-17T07:36:53.0812468Z that agree. 2025-07-17T07:36:53.0812546Z 2025-07-17T07:36:53.0812634Z Parameters 2025-07-17T07:36:53.0812732Z ---------- 2025-07-17T07:36:53.0812817Z actual : scalar 2025-07-17T07:36:53.0812963Z The object to check. 2025-07-17T07:36:53.0813064Z desired : scalar 2025-07-17T07:36:53.0813158Z The expected object. 2025-07-17T07:36:53.0813261Z significant : int, optional 2025-07-17T07:36:53.0813388Z Desired precision, default is 7. 2025-07-17T07:36:53.0813501Z err_msg : str, optional 2025-07-17T07:36:53.0813651Z The error message to be printed in case of failure. 2025-07-17T07:36:53.0813761Z verbose : bool, optional 2025-07-17T07:36:53.0813959Z If True, the conflicting values are appended to the error message. 2025-07-17T07:36:53.0814049Z 2025-07-17T07:36:53.0814126Z Raises 2025-07-17T07:36:53.0814204Z ------ 2025-07-17T07:36:53.0814303Z AssertionError 2025-07-17T07:36:53.0814490Z If actual and desired are not equal up to specified precision. 2025-07-17T07:36:53.0814567Z 2025-07-17T07:36:53.0814661Z See Also 2025-07-17T07:36:53.0814741Z -------- 2025-07-17T07:36:53.0814977Z assert_allclose: Compare two array_like objects for equality with desired 2025-07-17T07:36:53.0815114Z relative and/or absolute precision. 2025-07-17T07:36:53.0815320Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-07-17T07:36:53.0815425Z 2025-07-17T07:36:53.0815520Z Examples 2025-07-17T07:36:53.0815601Z -------- 2025-07-17T07:36:53.0815717Z >>> np.testing.assert_approx_equal( 2025-07-17T07:36:53.0815830Z ... 0.12345677777777e-20, 0.1234567e-20 2025-07-17T07:36:53.0815922Z ... ) # doctest: +SKIP 2025-07-17T07:36:53.0816050Z >>> np.testing.assert_approx_equal( 2025-07-17T07:36:53.0816137Z ... 0.12345670e-20, 2025-07-17T07:36:53.0816243Z ... 0.12345671e-20, # doctest: +SKIP 2025-07-17T07:36:53.0816349Z ... significant=8, 2025-07-17T07:36:53.0816428Z ... ) 2025-07-17T07:36:53.0816539Z >>> np.testing.assert_approx_equal( 2025-07-17T07:36:53.0816669Z ... 0.12345670e-20, 2025-07-17T07:36:53.0816774Z ... 0.12345672e-20, # doctest: +SKIP 2025-07-17T07:36:53.0816865Z ... significant=8, 2025-07-17T07:36:53.0816958Z ... ) 2025-07-17T07:36:53.0817068Z Traceback (most recent call last): 2025-07-17T07:36:53.0817146Z ... 2025-07-17T07:36:53.0817252Z AssertionError: 2025-07-17T07:36:53.0817382Z Items are not equal to 8 significant digits: 2025-07-17T07:36:53.0817488Z ACTUAL: 1.234567e-21 2025-07-17T07:36:53.0817580Z DESIRED: 1.2345672e-21 2025-07-17T07:36:53.0817657Z 2025-07-17T07:36:53.0817828Z the evaluated condition that raises the exception is 2025-07-17T07:36:53.0817951Z 2025-07-17T07:36:53.0818141Z >>> abs(0.12345670e-20 / 1e-21 - 0.12345672e-20 / 1e-21) >= 10 ** -(8 - 1) 2025-07-17T07:36:53.0818241Z True 2025-07-17T07:36:53.0818318Z 2025-07-17T07:36:53.0818396Z 2025-07-17T07:36:53.0818657Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0818736Z 2025-07-17T07:36:53.0818832Z warnings.warn(msg) 2025-07-17T07:36:53.0818920Z 2025-07-17T07:36:53.0819108Z --- Parse Warning: 30 / 136 --- 2025-07-17T07:36:53.0820040Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_array_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=744. 2025-07-17T07:36:53.0820314Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0820392Z 2025-07-17T07:36:53.0820611Z Raises an AssertionError if two array_like objects are not equal. 2025-07-17T07:36:53.0820690Z 2025-07-17T07:36:53.0820892Z Given two array_like objects, check that the shape is equal and all 2025-07-17T07:36:53.0821117Z elements of these objects are equal (but see the Notes for the special 2025-07-17T07:36:53.0821316Z handling of a scalar). An exception is raised at shape mismatch or 2025-07-17T07:36:53.0821536Z conflicting values. In contrast to the standard usage in numpy, NaNs 2025-07-17T07:36:53.0821763Z are compared like numbers, no assertion is raised if both objects have 2025-07-17T07:36:53.0821866Z NaNs in the same positions. 2025-07-17T07:36:53.0821954Z 2025-07-17T07:36:53.0822180Z The usual caution for verifying equality with floating point numbers is 2025-07-17T07:36:53.0822262Z advised. 2025-07-17T07:36:53.0822352Z 2025-07-17T07:36:53.0822437Z Parameters 2025-07-17T07:36:53.0822521Z ---------- 2025-07-17T07:36:53.0822619Z x : array_like 2025-07-17T07:36:53.0822726Z The actual object to check. 2025-07-17T07:36:53.0822810Z y : array_like 2025-07-17T07:36:53.0822930Z The desired, expected object. 2025-07-17T07:36:53.0823026Z err_msg : str, optional 2025-07-17T07:36:53.0823178Z The error message to be printed in case of failure. 2025-07-17T07:36:53.0823290Z verbose : bool, optional 2025-07-17T07:36:53.0823489Z If True, the conflicting values are appended to the error message. 2025-07-17T07:36:53.0823596Z strict : bool, optional 2025-07-17T07:36:53.0823791Z If True, raise an AssertionError when either the shape or the data 2025-07-17T07:36:53.0823965Z type of the array_like objects does not match. The special 2025-07-17T07:36:53.0824211Z handling for scalars mentioned in the Notes section is disabled. 2025-07-17T07:36:53.0824289Z 2025-07-17T07:36:53.0824367Z Raises 2025-07-17T07:36:53.0824465Z ------ 2025-07-17T07:36:53.0824557Z AssertionError 2025-07-17T07:36:53.0824689Z If actual and desired objects are not equal. 2025-07-17T07:36:53.0824783Z 2025-07-17T07:36:53.0824864Z See Also 2025-07-17T07:36:53.0824946Z -------- 2025-07-17T07:36:53.0825193Z assert_allclose: Compare two array_like objects for equality with desired 2025-07-17T07:36:53.0825318Z relative and/or absolute precision. 2025-07-17T07:36:53.0825563Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-07-17T07:36:53.0825640Z 2025-07-17T07:36:53.0825724Z Notes 2025-07-17T07:36:53.0825815Z ----- 2025-07-17T07:36:53.0825993Z When one of `x` and `y` is a scalar and the other is array_like, the 2025-07-17T07:36:53.0826214Z function checks that each element of the array_like object is equal to 2025-07-17T07:36:53.0826445Z the scalar. This behaviour can be disabled with the `strict` parameter. 2025-07-17T07:36:53.0826522Z 2025-07-17T07:36:53.0826603Z Examples 2025-07-17T07:36:53.0826695Z -------- 2025-07-17T07:36:53.0826878Z The first assert does not raise an exception: 2025-07-17T07:36:53.0826967Z 2025-07-17T07:36:53.0827079Z >>> np.testing.assert_array_equal( 2025-07-17T07:36:53.0827216Z ... [1.0, 2.33333, np.nan], [np.exp(0), 2.33333, np.nan] 2025-07-17T07:36:53.0827307Z ... ) 2025-07-17T07:36:53.0827385Z 2025-07-17T07:36:53.0827606Z Use `assert_allclose` or one of the nulp (number of floating point values) 2025-07-17T07:36:53.0827726Z functions for these cases instead: 2025-07-17T07:36:53.0827804Z 2025-07-17T07:36:53.0827910Z >>> np.testing.assert_allclose( 2025-07-17T07:36:53.0828113Z ... [1.0, np.pi, np.nan], [1, np.sqrt(np.pi) ** 2, np.nan], rtol=1e-10, atol=0 2025-07-17T07:36:53.0828193Z ... ) 2025-07-17T07:36:53.0828269Z 2025-07-17T07:36:53.0828484Z As mentioned in the Notes section, `assert_array_equal` has special 2025-07-17T07:36:53.0828706Z handling for scalars. Here the test checks that each value in `x` is 3: 2025-07-17T07:36:53.0828794Z 2025-07-17T07:36:53.0828900Z >>> x = np.full((2, 5), fill_value=3) 2025-07-17T07:36:53.0829014Z >>> np.testing.assert_array_equal(x, 3) 2025-07-17T07:36:53.0829102Z 2025-07-17T07:36:53.0829310Z Use `strict` to raise an AssertionError when comparing a scalar with an 2025-07-17T07:36:53.0829390Z array: 2025-07-17T07:36:53.0829479Z 2025-07-17T07:36:53.0829625Z >>> np.testing.assert_array_equal(x, 3, strict=True) 2025-07-17T07:36:53.0829734Z Traceback (most recent call last): 2025-07-17T07:36:53.0829824Z ... 2025-07-17T07:36:53.0829914Z AssertionError: 2025-07-17T07:36:53.0830006Z Arrays are not equal 2025-07-17T07:36:53.0830101Z 2025-07-17T07:36:53.0830197Z (shapes (2, 5), () mismatch) 2025-07-17T07:36:53.0830312Z x: torch.ndarray([[3, 3, 3, 3, 3], 2025-07-17T07:36:53.0830402Z [3, 3, 3, 3, 3]]) 2025-07-17T07:36:53.0830495Z y: torch.ndarray(3) 2025-07-17T07:36:53.0830584Z 2025-07-17T07:36:53.0830799Z The `strict` parameter also ensures that the array data types match: 2025-07-17T07:36:53.0830879Z 2025-07-17T07:36:53.0830989Z >>> x = np.array([2, 2, 2]) 2025-07-17T07:36:53.0831117Z >>> y = np.array([2.0, 2.0, 2.0], dtype=np.float32) 2025-07-17T07:36:53.0831264Z >>> np.testing.assert_array_equal(x, y, strict=True) 2025-07-17T07:36:53.0831388Z Traceback (most recent call last): 2025-07-17T07:36:53.0831469Z ... 2025-07-17T07:36:53.0831565Z AssertionError: 2025-07-17T07:36:53.0831670Z Arrays are not equal 2025-07-17T07:36:53.0831754Z 2025-07-17T07:36:53.0831907Z (dtypes dtype("int64"), dtype("float32") mismatch) 2025-07-17T07:36:53.0832048Z x: torch.ndarray([2, 2, 2]) 2025-07-17T07:36:53.0832147Z y: torch.ndarray([2., 2., 2.]) 2025-07-17T07:36:53.0832236Z 2025-07-17T07:36:53.0832486Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0832564Z 2025-07-17T07:36:53.0832673Z warnings.warn(msg) 2025-07-17T07:36:53.0832753Z 2025-07-17T07:36:53.0832944Z --- Parse Warning: 31 / 136 --- 2025-07-17T07:36:53.0833919Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_array_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=851. 2025-07-17T07:36:53.0834211Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0834298Z 2025-07-17T07:36:53.0834509Z Raises an AssertionError if two objects are not equal up to desired 2025-07-17T07:36:53.0834594Z precision. 2025-07-17T07:36:53.0834685Z 2025-07-17T07:36:53.0834856Z .. note:: It is recommended to use one of `assert_allclose`, 2025-07-17T07:36:53.0835032Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-07-17T07:36:53.0835228Z instead of this function for more consistent floating point 2025-07-17T07:36:53.0835378Z comparisons. 2025-07-17T07:36:53.0835468Z 2025-07-17T07:36:53.0835704Z The test verifies identical shapes and that the elements of ``actual`` and 2025-07-17T07:36:53.0835797Z ``desired`` satisfy. 2025-07-17T07:36:53.0835888Z 2025-07-17T07:36:53.0836015Z ``abs(desired-actual) < 1.5 * 10**(-decimal)`` 2025-07-17T07:36:53.0836095Z 2025-07-17T07:36:53.0836332Z That is a looser test than originally documented, but agrees with what the 2025-07-17T07:36:53.0836572Z actual implementation did up to rounding vagaries. An exception is raised 2025-07-17T07:36:53.0836805Z at shape mismatch or conflicting values. In contrast to the standard usage 2025-07-17T07:36:53.0837039Z in numpy, NaNs are compared like numbers, no assertion is raised if both 2025-07-17T07:36:53.0837161Z objects have NaNs in the same positions. 2025-07-17T07:36:53.0837253Z 2025-07-17T07:36:53.0837340Z Parameters 2025-07-17T07:36:53.0837422Z ---------- 2025-07-17T07:36:53.0837524Z x : array_like 2025-07-17T07:36:53.0837626Z The actual object to check. 2025-07-17T07:36:53.0837710Z y : array_like 2025-07-17T07:36:53.0837829Z The desired, expected object. 2025-07-17T07:36:53.0837925Z decimal : int, optional 2025-07-17T07:36:53.0838101Z Desired precision, default is 6. 2025-07-17T07:36:53.0838212Z err_msg : str, optional 2025-07-17T07:36:53.0838362Z The error message to be printed in case of failure. 2025-07-17T07:36:53.0838457Z verbose : bool, optional 2025-07-17T07:36:53.0838668Z If True, the conflicting values are appended to the error message. 2025-07-17T07:36:53.0838744Z 2025-07-17T07:36:53.0838842Z Raises 2025-07-17T07:36:53.0838923Z ------ 2025-07-17T07:36:53.0839011Z AssertionError 2025-07-17T07:36:53.0839223Z If actual and desired are not equal up to specified precision. 2025-07-17T07:36:53.0839299Z 2025-07-17T07:36:53.0839378Z See Also 2025-07-17T07:36:53.0839473Z -------- 2025-07-17T07:36:53.0839711Z assert_allclose: Compare two array_like objects for equality with desired 2025-07-17T07:36:53.0839835Z relative and/or absolute precision. 2025-07-17T07:36:53.0840054Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-07-17T07:36:53.0840133Z 2025-07-17T07:36:53.0840216Z Examples 2025-07-17T07:36:53.0840309Z -------- 2025-07-17T07:36:53.0840435Z the first assert does not raise an exception 2025-07-17T07:36:53.0840513Z 2025-07-17T07:36:53.0840770Z >>> np.testing.assert_array_almost_equal([1.0, 2.333, np.nan], [1.0, 2.333, np.nan]) 2025-07-17T07:36:53.0840849Z 2025-07-17T07:36:53.0841011Z >>> np.testing.assert_array_almost_equal( 2025-07-17T07:36:53.0841159Z ... [1.0, 2.33333, np.nan], [1.0, 2.33339, np.nan], decimal=5 2025-07-17T07:36:53.0841239Z ... ) 2025-07-17T07:36:53.0841362Z Traceback (most recent call last): 2025-07-17T07:36:53.0841439Z ... 2025-07-17T07:36:53.0841535Z AssertionError: 2025-07-17T07:36:53.0841666Z Arrays are not almost equal to 5 decimals 2025-07-17T07:36:53.0841749Z 2025-07-17T07:36:53.0841854Z Mismatched elements: 1 / 3 (33.3%) 2025-07-17T07:36:53.0841991Z Max absolute difference: 5.999999999994898e-05 2025-07-17T07:36:53.0842142Z Max relative difference: 2.5713661239633743e-05 2025-07-17T07:36:53.0842311Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-07-17T07:36:53.0842466Z y: torch.ndarray([1.0000, 2.3334, nan], dtype=float64) 2025-07-17T07:36:53.0842542Z 2025-07-17T07:36:53.0842671Z >>> np.testing.assert_array_almost_equal( 2025-07-17T07:36:53.0842802Z ... [1.0, 2.33333, np.nan], [1.0, 2.33333, 5], decimal=5 2025-07-17T07:36:53.0842881Z ... ) 2025-07-17T07:36:53.0843000Z Traceback (most recent call last): 2025-07-17T07:36:53.0843080Z ... 2025-07-17T07:36:53.0843171Z AssertionError: 2025-07-17T07:36:53.0843302Z Arrays are not almost equal to 5 decimals 2025-07-17T07:36:53.0843436Z 2025-07-17T07:36:53.0843541Z x and y nan location mismatch: 2025-07-17T07:36:53.0843706Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-07-17T07:36:53.0843858Z y: torch.ndarray([1.0000, 2.3333, 5.0000], dtype=float64) 2025-07-17T07:36:53.0843949Z 2025-07-17T07:36:53.0844026Z 2025-07-17T07:36:53.0844276Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0844364Z 2025-07-17T07:36:53.0844458Z warnings.warn(msg) 2025-07-17T07:36:53.0844535Z 2025-07-17T07:36:53.0844739Z --- Parse Warning: 32 / 136 --- 2025-07-17T07:36:53.0845782Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=clear_and_catch_warnings in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=1848. 2025-07-17T07:36:53.0846061Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0846273Z Context manager that resets warning registry for catching warnings 2025-07-17T07:36:53.0846350Z 2025-07-17T07:36:53.0846606Z Warnings can be slippery, because, whenever a warning is triggered, Python 2025-07-17T07:36:53.0846830Z adds a ``__warningregistry__`` member to the *calling* module. This makes 2025-07-17T07:36:53.0847066Z it impossible to retrigger the warning in this module, whatever you put in 2025-07-17T07:36:53.0847321Z the warnings filters. This context manager accepts a sequence of `modules` 2025-07-17T07:36:53.0847456Z as a keyword argument to its constructor and: 2025-07-17T07:36:53.0847549Z 2025-07-17T07:36:53.0847772Z * stores and removes any ``__warningregistry__`` entries in given `modules` 2025-07-17T07:36:53.0847857Z on entry; 2025-07-17T07:36:53.0848052Z * resets ``__warningregistry__`` to its previous state on exit. 2025-07-17T07:36:53.0848128Z 2025-07-17T07:36:53.0848351Z This makes it possible to trigger any warning afresh inside the context 2025-07-17T07:36:53.0848546Z manager without disturbing the state of warnings outside. 2025-07-17T07:36:53.0848624Z 2025-07-17T07:36:53.0848856Z For compatibility with Python 3.0, please consider all arguments to be 2025-07-17T07:36:53.0848960Z keyword-only. 2025-07-17T07:36:53.0849040Z 2025-07-17T07:36:53.0849125Z Parameters 2025-07-17T07:36:53.0849223Z ---------- 2025-07-17T07:36:53.0849321Z record : bool, optional 2025-07-17T07:36:53.0849519Z Specifies whether warnings should be captured by a custom 2025-07-17T07:36:53.0849787Z implementation of ``warnings.showwarning()`` and be appended to a list 2025-07-17T07:36:53.0849990Z returned by the context manager. Otherwise None is returned by the 2025-07-17T07:36:53.0850225Z context manager. The objects appended to the list are arguments whose 2025-07-17T07:36:53.0850396Z attributes mirror the arguments to ``showwarning()``. 2025-07-17T07:36:53.0850502Z modules : sequence, optional 2025-07-17T07:36:53.0850732Z Sequence of modules for which to reset warnings registry on entry and 2025-07-17T07:36:53.0850952Z restore on exit. To work correctly, all 'ignore' filters should 2025-07-17T07:36:53.0851075Z filter by one of these modules. 2025-07-17T07:36:53.0851153Z 2025-07-17T07:36:53.0851234Z Examples 2025-07-17T07:36:53.0851329Z -------- 2025-07-17T07:36:53.0851424Z >>> import warnings 2025-07-17T07:36:53.0851604Z >>> with np.testing.clear_and_catch_warnings( # doctest: +SKIP 2025-07-17T07:36:53.0851732Z ... modules=[np.core.fromnumeric] 2025-07-17T07:36:53.0851811Z ... ): 2025-07-17T07:36:53.0851930Z ... warnings.simplefilter("always") 2025-07-17T07:36:53.0852211Z ... warnings.filterwarnings("ignore", module="np.core.fromnumeric") 2025-07-17T07:36:53.0852381Z ... # do something that raises a warning but ignore those in 2025-07-17T07:36:53.0852495Z ... # np.core.fromnumeric 2025-07-17T07:36:53.0852573Z 2025-07-17T07:36:53.0852820Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0852911Z 2025-07-17T07:36:53.0853005Z warnings.warn(msg) 2025-07-17T07:36:53.0853084Z 2025-07-17T07:36:53.0853291Z --- Parse Warning: 33 / 136 --- 2025-07-17T07:36:53.0854216Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Conv1d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py line=354. 2025-07-17T07:36:53.0854477Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0854696Z Applies a 1D convolution over a quantized input signal composed of 2025-07-17T07:36:53.0854835Z several quantized input planes. 2025-07-17T07:36:53.0854923Z 2025-07-17T07:36:53.0855130Z For details on input arguments, parameters, and implementation see 2025-07-17T07:36:53.0855232Z :class:`~torch.nn.Conv1d`. 2025-07-17T07:36:53.0855325Z 2025-07-17T07:36:53.0855416Z .. note:: 2025-07-17T07:36:53.0855609Z Only `zeros` is supported for the :attr:`padding_mode` argument. 2025-07-17T07:36:53.0855697Z 2025-07-17T07:36:53.0855779Z .. note:: 2025-07-17T07:36:53.0855955Z Only `torch.quint8` is supported for the input data type. 2025-07-17T07:36:53.0856046Z 2025-07-17T07:36:53.0856127Z 2025-07-17T07:36:53.0856225Z Attributes: 2025-07-17T07:36:53.0856431Z weight (Tensor): packed tensor derived from the learnable weight 2025-07-17T07:36:53.0856529Z parameter. 2025-07-17T07:36:53.0856683Z scale (Tensor): scalar for the output scale 2025-07-17T07:36:53.0856844Z zero_point (Tensor): scalar for the output zero point 2025-07-17T07:36:53.0856919Z 2025-07-17T07:36:53.0857077Z See :class:`~torch.nn.Conv1d` for other attributes. 2025-07-17T07:36:53.0857153Z 2025-07-17T07:36:53.0857238Z Examples:: 2025-07-17T07:36:53.0857330Z 2025-07-17T07:36:53.0857509Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_QENGINE) 2025-07-17T07:36:53.0857650Z >>> m = nn.quantized.Conv1d(16, 33, 3, stride=2) 2025-07-17T07:36:53.0857759Z >>> input = torch.randn(20, 16, 100) 2025-07-17T07:36:53.0857867Z >>> # quantize input to quint8 2025-07-17T07:36:53.0858005Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0858213Z >>> q_input = torch.quantize_per_tensor(input, scale=1.0, zero_point=0, 2025-07-17T07:36:53.0858340Z ... dtype=torch.quint8) 2025-07-17T07:36:53.0858451Z >>> output = m(q_input) 2025-07-17T07:36:53.0858527Z 2025-07-17T07:36:53.0858609Z 2025-07-17T07:36:53.0858872Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0858950Z 2025-07-17T07:36:53.0859048Z warnings.warn(msg) 2025-07-17T07:36:53.0859140Z 2025-07-17T07:36:53.0859351Z --- Parse Warning: 34 / 136 --- 2025-07-17T07:36:53.0860267Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LSTM in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/rnn.py line=12. 2025-07-17T07:36:53.0860531Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0860659Z A quantized long short-term memory (LSTM). 2025-07-17T07:36:53.0860750Z 2025-07-17T07:36:53.0861027Z For the description and the argument types, please, refer to :class:`~torch.nn.LSTM` 2025-07-17T07:36:53.0861105Z 2025-07-17T07:36:53.0861269Z Attributes: 2025-07-17T07:36:53.0861391Z layers : instances of the `_LSTMLayer` 2025-07-17T07:36:53.0861505Z 2025-07-17T07:36:53.0861592Z .. note:: 2025-07-17T07:36:53.0861803Z To access the weights and biases, you need to access them per layer. 2025-07-17T07:36:53.0861988Z See examples in :class:`~torch.ao.nn.quantizable.LSTM` 2025-07-17T07:36:53.0862065Z 2025-07-17T07:36:53.0862152Z Examples:: 2025-07-17T07:36:53.0862262Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0862365Z >>> custom_module_config = { 2025-07-17T07:36:53.0862502Z ... 'float_to_observed_custom_module_class': { 2025-07-17T07:36:53.0862641Z ... nn.LSTM: nn.quantizable.LSTM, 2025-07-17T07:36:53.0862722Z ... }, 2025-07-17T07:36:53.0862880Z ... 'observed_to_quantized_custom_module_class': { 2025-07-17T07:36:53.0863018Z ... nn.quantizable.LSTM: nn.quantized.LSTM, 2025-07-17T07:36:53.0863104Z ... } 2025-07-17T07:36:53.0863199Z ... } 2025-07-17T07:36:53.0863418Z >>> tq.prepare(model, prepare_custom_module_class=custom_module_config) 2025-07-17T07:36:53.0863626Z >>> tq.convert(model, convert_custom_module_class=custom_module_config) 2025-07-17T07:36:53.0863717Z 2025-07-17T07:36:53.0863984Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0864059Z 2025-07-17T07:36:53.0864165Z warnings.warn(msg) 2025-07-17T07:36:53.0864241Z 2025-07-17T07:36:53.0864424Z --- Parse Warning: 35 / 136 --- 2025-07-17T07:36:53.0865642Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ActivationSparsifier in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16. 2025-07-17T07:36:53.0865908Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0865998Z 2025-07-17T07:36:53.0866261Z The Activation sparsifier class aims to sparsify/prune activations in a neural 2025-07-17T07:36:53.0866485Z network. The idea is to attach the sparsifier to a layer (or layers) and it 2025-07-17T07:36:53.0866744Z zeroes out the activations based on the mask_fn (or sparsification function) 2025-07-17T07:36:53.0866835Z input by the user. 2025-07-17T07:36:53.0867065Z The mask_fn is applied once all the inputs are aggregated and reduced i.e. 2025-07-17T07:36:53.0867217Z mask = mask_fn(reduce_fn(aggregate_fn(activations))) 2025-07-17T07:36:53.0867323Z 2025-07-17T07:36:53.0867419Z Note:: 2025-07-17T07:36:53.0867739Z The sparsification mask is computed on the input **before it goes through the attached layer**. 2025-07-17T07:36:53.0867816Z 2025-07-17T07:36:53.0867908Z Args: 2025-07-17T07:36:53.0868002Z model (nn.Module): 2025-07-17T07:36:53.0868223Z The model whose layers will be sparsified. The layers that needs to be 2025-07-17T07:36:53.0868476Z sparsified should be added separately using the register_layer() function 2025-07-17T07:36:53.0868590Z aggregate_fn (Optional, Callable): 2025-07-17T07:36:53.0868881Z default aggregate_fn that is used if not specified while registering the layer. 2025-07-17T07:36:53.0869041Z specifies how inputs should be aggregated over time. 2025-07-17T07:36:53.0869321Z The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor. 2025-07-17T07:36:53.0869415Z Example 2025-07-17T07:36:53.0869592Z def add_agg_fn(tensor1, tensor2): return tensor1 + tensor2 2025-07-17T07:36:53.0869705Z reduce_fn (Optional, Callable): 2025-07-17T07:36:53.0870230Z default reduce_fn that is used if not specified while registering the layer. 2025-07-17T07:36:53.0870715Z reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after 2025-07-17T07:36:53.0870847Z calling agg_fn() on all inputs. 2025-07-17T07:36:53.0870935Z Example 2025-07-17T07:36:53.0871129Z def mean_reduce_fn(agg_tensor): return agg_tensor.mean(dim=0) 2025-07-17T07:36:53.0871256Z mask_fn (Optional, Callable): 2025-07-17T07:36:53.0871562Z default mask_fn that is used to create the sparsification mask using the tensor obtained after 2025-07-17T07:36:53.0871813Z calling the reduce_fn(). This is used by default if a custom one is passed in the 2025-07-17T07:36:53.0871926Z register_layer(). 2025-07-17T07:36:53.0872271Z Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config 2025-07-17T07:36:53.0872376Z arguments. 2025-07-17T07:36:53.0872487Z features (Optional, list): 2025-07-17T07:36:53.0872616Z default selected features to sparsify. 2025-07-17T07:36:53.0872886Z If this is non-empty, then the mask_fn will be applied for each feature of the input. 2025-07-17T07:36:53.0872981Z For example, 2025-07-17T07:36:53.0873232Z mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features] 2025-07-17T07:36:53.0873352Z feature_dim (Optional, int): 2025-07-17T07:36:53.0873625Z default dimension of input features. Again, features along this dim will be chosen 2025-07-17T07:36:53.0873737Z for sparsification. 2025-07-17T07:36:53.0873838Z sparse_config (Dict): 2025-07-17T07:36:53.0874054Z Default configuration for the mask_fn. This config will be passed 2025-07-17T07:36:53.0874164Z with the mask_fn() 2025-07-17T07:36:53.0874240Z 2025-07-17T07:36:53.0874326Z Example: 2025-07-17T07:36:53.0874440Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0874535Z >>> model = SomeModel() 2025-07-17T07:36:53.0874776Z >>> act_sparsifier = ActivationSparsifier(...) # init activation sparsifier 2025-07-17T07:36:53.0874890Z >>> # Initialize aggregate_fn 2025-07-17T07:36:53.0874983Z >>> def agg_fn(x, y): 2025-07-17T07:36:53.0875086Z >>> return x + y 2025-07-17T07:36:53.0875167Z >>> 2025-07-17T07:36:53.0875267Z >>> # Initialize reduce_fn 2025-07-17T07:36:53.0875372Z >>> def reduce_fn(x): 2025-07-17T07:36:53.0875478Z >>> return torch.mean(x, dim=0) 2025-07-17T07:36:53.0875600Z >>> 2025-07-17T07:36:53.0875714Z >>> # Initialize mask_fn 2025-07-17T07:36:53.0875805Z >>> def mask_fn(data): 2025-07-17T07:36:53.0875945Z >>> return torch.eye(data.shape).to(data.device) 2025-07-17T07:36:53.0876036Z >>> 2025-07-17T07:36:53.0876151Z >>> 2025-07-17T07:36:53.0876268Z >>> act_sparsifier.register_layer( 2025-07-17T07:36:53.0876377Z ... model.some_layer, 2025-07-17T07:36:53.0876473Z ... aggregate_fn=agg_fn, 2025-07-17T07:36:53.0876569Z ... reduce_fn=reduce_fn, 2025-07-17T07:36:53.0876674Z ... mask_fn=mask_fn, 2025-07-17T07:36:53.0876793Z ... ) 2025-07-17T07:36:53.0876872Z >>> 2025-07-17T07:36:53.0876985Z >>> # start training process 2025-07-17T07:36:53.0877073Z >>> for _ in [...]: 2025-07-17T07:36:53.0877173Z >>> # epoch starts 2025-07-17T07:36:53.0877339Z >>> # model.forward(), compute_loss() and model.backwards() 2025-07-17T07:36:53.0877429Z >>> # epoch ends 2025-07-17T07:36:53.0877542Z >>> act_sparsifier.step() 2025-07-17T07:36:53.0877638Z >>> # end training process 2025-07-17T07:36:53.0877741Z >>> sparsifier.squash_mask() 2025-07-17T07:36:53.0877830Z 2025-07-17T07:36:53.0878129Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0878207Z 2025-07-17T07:36:53.0878310Z warnings.warn(msg) 2025-07-17T07:36:53.0878387Z 2025-07-17T07:36:53.0878601Z --- Parse Warning: 36 / 136 --- 2025-07-17T07:36:53.0879830Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BaseDataScheduler.get_schedule_param in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py line=91. 2025-07-17T07:36:53.0880093Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0880186Z 2025-07-17T07:36:53.0880388Z Abstract method that needs to be implemented by the child class. 2025-07-17T07:36:53.0880639Z The expected return type should is a dictionary of name to schedule_param value 2025-07-17T07:36:53.0880914Z The returned values will be updated in sparsifier when the scheduler step() function 2025-07-17T07:36:53.0881000Z is called. 2025-07-17T07:36:53.0881088Z 2025-07-17T07:36:53.0881169Z Example: 2025-07-17T07:36:53.0881276Z >>> def get_schedule_param(self): 2025-07-17T07:36:53.0881383Z ... new_param = {} 2025-07-17T07:36:53.0881534Z ... for name in self.sparsifier.data_groups.keys(): 2025-07-17T07:36:53.0881633Z ... new_param[name] = ( 2025-07-17T07:36:53.0881849Z ... self.sparsifier.data_groups[name][self.schedule_param] * 0.5 2025-07-17T07:36:53.0881939Z ... ) 2025-07-17T07:36:53.0882033Z ... return new_param 2025-07-17T07:36:53.0882124Z 2025-07-17T07:36:53.0882464Z When the step() function is called, the value in self.sparsifier.data_groups[name][self.schedule_param] 2025-07-17T07:36:53.0882562Z would be halved 2025-07-17T07:36:53.0882661Z 2025-07-17T07:36:53.0882911Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0883001Z 2025-07-17T07:36:53.0883094Z warnings.warn(msg) 2025-07-17T07:36:53.0883172Z 2025-07-17T07:36:53.0883366Z --- Parse Warning: 37 / 136 --- 2025-07-17T07:36:53.0884439Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BaseSparsifier.squash_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py line=229. 2025-07-17T07:36:53.0884698Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0884881Z Squashes the sparse masks into the appropriate tensors. 2025-07-17T07:36:53.0884992Z 2025-07-17T07:36:53.0885209Z If either the `params_to_keep` or `params_to_keep_per_layer` is set, 2025-07-17T07:36:53.0885475Z the module will have a `sparse_params` dict attached to it. 2025-07-17T07:36:53.0885554Z 2025-07-17T07:36:53.0885648Z Args: 2025-07-17T07:36:53.0885831Z params_to_keep: List of keys to save in the module or a dict 2025-07-17T07:36:53.0886028Z representing the modules and keys that will have 2025-07-17T07:36:53.0886162Z sparsity parameters saved 2025-07-17T07:36:53.0886400Z params_to_keep_per_layer: Dict to specify the params that should be 2025-07-17T07:36:53.0886560Z saved for specific layers. The keys in the dict 2025-07-17T07:36:53.0886710Z should be the module fqn, while the values should 2025-07-17T07:36:53.0886868Z be a list of strings with the names of the variables 2025-07-17T07:36:53.0887003Z to save in the `sparse_params` 2025-07-17T07:36:53.0887079Z 2025-07-17T07:36:53.0887164Z Examples: 2025-07-17T07:36:53.0887305Z >>> # xdoctest: +SKIP("locals are undefined") 2025-07-17T07:36:53.0887468Z >>> # Don't save any sparse params 2025-07-17T07:36:53.0887580Z >>> sparsifier.squash_mask() 2025-07-17T07:36:53.0887729Z >>> hasattr(model.submodule1, "sparse_params") 2025-07-17T07:36:53.0887811Z False 2025-07-17T07:36:53.0887900Z 2025-07-17T07:36:53.0888013Z >>> # Keep sparse params per layer 2025-07-17T07:36:53.0888121Z >>> sparsifier.squash_mask( 2025-07-17T07:36:53.0888244Z ... params_to_keep_per_layer={ 2025-07-17T07:36:53.0888373Z ... "submodule1.linear1": ("foo", "bar"), 2025-07-17T07:36:53.0888495Z ... "submodule2.linear42": ("baz",), 2025-07-17T07:36:53.0888593Z ... } 2025-07-17T07:36:53.0888675Z ... ) 2025-07-17T07:36:53.0888829Z >>> print(model.submodule1.linear1.sparse_params) 2025-07-17T07:36:53.0888936Z {'foo': 42, 'bar': 24} 2025-07-17T07:36:53.0889094Z >>> print(model.submodule2.linear42.sparse_params) 2025-07-17T07:36:53.0889196Z {'baz': 0.1} 2025-07-17T07:36:53.0889272Z 2025-07-17T07:36:53.0889391Z >>> # Keep sparse params for all layers 2025-07-17T07:36:53.0889573Z >>> sparsifier.squash_mask(params_to_keep=("foo", "bar")) 2025-07-17T07:36:53.0889726Z >>> print(model.submodule1.linear1.sparse_params) 2025-07-17T07:36:53.0889820Z {'foo': 42, 'bar': 24} 2025-07-17T07:36:53.0889985Z >>> print(model.submodule2.linear42.sparse_params) 2025-07-17T07:36:53.0890078Z {'foo': 42, 'bar': 24} 2025-07-17T07:36:53.0890157Z 2025-07-17T07:36:53.0890365Z >>> # Keep some sparse params for all layers, and specific ones for 2025-07-17T07:36:53.0890461Z >>> # some other layers 2025-07-17T07:36:53.0890594Z >>> sparsifier.squash_mask( 2025-07-17T07:36:53.0890714Z ... params_to_keep=("foo", "bar"), 2025-07-17T07:36:53.0890899Z ... params_to_keep_per_layer={"submodule2.linear42": ("baz",)}, 2025-07-17T07:36:53.0890993Z ... ) 2025-07-17T07:36:53.0891148Z >>> print(model.submodule1.linear1.sparse_params) 2025-07-17T07:36:53.0891256Z {'foo': 42, 'bar': 24} 2025-07-17T07:36:53.0891413Z >>> print(model.submodule2.linear42.sparse_params) 2025-07-17T07:36:53.0891518Z {'foo': 42, 'bar': 24, 'baz': 0.1} 2025-07-17T07:36:53.0891611Z 2025-07-17T07:36:53.0891864Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0891972Z 2025-07-17T07:36:53.0892076Z warnings.warn(msg) 2025-07-17T07:36:53.0892154Z 2025-07-17T07:36:53.0892344Z --- Parse Warning: 38 / 136 --- 2025-07-17T07:36:53.0893409Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DTypeConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/backend_config.py line=181. 2025-07-17T07:36:53.0893671Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0893764Z 2025-07-17T07:36:53.0894049Z Config object that specifies the supported data types passed as arguments to 2025-07-17T07:36:53.0894286Z quantize ops in the reference model spec, for input and output activations, 2025-07-17T07:36:53.0894394Z weights, and biases. 2025-07-17T07:36:53.0894473Z 2025-07-17T07:36:53.0894630Z For example, consider the following reference model: 2025-07-17T07:36:53.0894722Z 2025-07-17T07:36:53.0894877Z quant1 - [dequant1 - fp32_linear - quant2] - dequant2 2025-07-17T07:36:53.0894963Z 2025-07-17T07:36:53.0895175Z The pattern in the square brackets refers to the reference pattern of 2025-07-17T07:36:53.0895469Z statically quantized linear. Setting the input dtype as `torch.quint8` 2025-07-17T07:36:53.0895706Z in the DTypeConfig means we pass in `torch.quint8` as the dtype argument 2025-07-17T07:36:53.0895928Z to the first quantize op (quant1). Similarly, setting the output dtype as 2025-07-17T07:36:53.0896142Z `torch.quint8` means we pass in `torch.quint8` as the dtype argument to 2025-07-17T07:36:53.0896264Z the second quantize op (quant2). 2025-07-17T07:36:53.0896343Z 2025-07-17T07:36:53.0896568Z Note that the dtype here does not refer to the interface dtypes of the 2025-07-17T07:36:53.0896776Z op. For example, the "input dtype" here is not the dtype of the input 2025-07-17T07:36:53.0896988Z tensor passed to the quantized linear op. Though it can still be the 2025-07-17T07:36:53.0897195Z same as the interface dtype, this is not always the case, e.g. the 2025-07-17T07:36:53.0897411Z interface dtype is fp32 in dynamic quantization but the "input dtype" 2025-07-17T07:36:53.0897623Z specified in the DTypeConfig would still be quint8. The semantics of 2025-07-17T07:36:53.0897836Z dtypes here are the same as the semantics of the dtypes specified in 2025-07-17T07:36:53.0897924Z the observers. 2025-07-17T07:36:53.0897997Z 2025-07-17T07:36:53.0898214Z These dtypes are matched against the ones specified in the user's 2025-07-17T07:36:53.0898426Z QConfig. If there is a match, and the QConfig satisfies the constraints 2025-07-17T07:36:53.0898653Z specified in the DTypeConfig (if any), then we will quantize the given 2025-07-17T07:36:53.0898873Z pattern using this DTypeConfig. Otherwise, the QConfig is ignored and 2025-07-17T07:36:53.0898980Z the pattern will not be quantized. 2025-07-17T07:36:53.0899067Z 2025-07-17T07:36:53.0899166Z Example usage:: 2025-07-17T07:36:53.0899241Z 2025-07-17T07:36:53.0899353Z >>> # xdoctest: +SKIP(failing) 2025-07-17T07:36:53.0899460Z >>> dtype_config1 = DTypeConfig( 2025-07-17T07:36:53.0899561Z ... input_dtype=torch.quint8, 2025-07-17T07:36:53.0899682Z ... output_dtype=torch.quint8, 2025-07-17T07:36:53.0899784Z ... weight_dtype=torch.qint8, 2025-07-17T07:36:53.0899894Z ... bias_dtype=torch.float) 2025-07-17T07:36:53.0899972Z 2025-07-17T07:36:53.0900075Z >>> dtype_config2 = DTypeConfig( 2025-07-17T07:36:53.0900213Z ... input_dtype=DTypeWithConstraints( 2025-07-17T07:36:53.0900310Z ... dtype=torch.quint8, 2025-07-17T07:36:53.0900410Z ... quant_min_lower_bound=0, 2025-07-17T07:36:53.0900530Z ... quant_max_upper_bound=255, 2025-07-17T07:36:53.0900611Z ... ), 2025-07-17T07:36:53.0900764Z ... output_dtype=DTypeWithConstraints( 2025-07-17T07:36:53.0900873Z ... dtype=torch.quint8, 2025-07-17T07:36:53.0900977Z ... quant_min_lower_bound=0, 2025-07-17T07:36:53.0901095Z ... quant_max_upper_bound=255, 2025-07-17T07:36:53.0901174Z ... ), 2025-07-17T07:36:53.0901300Z ... weight_dtype=DTypeWithConstraints( 2025-07-17T07:36:53.0901407Z ... dtype=torch.qint8, 2025-07-17T07:36:53.0901517Z ... quant_min_lower_bound=-128, 2025-07-17T07:36:53.0901620Z ... quant_max_upper_bound=127, 2025-07-17T07:36:53.0901739Z ... ), 2025-07-17T07:36:53.0901838Z ... bias_dtype=torch.float) 2025-07-17T07:36:53.0901914Z 2025-07-17T07:36:53.0902032Z >>> dtype_config1.input_dtype 2025-07-17T07:36:53.0902115Z torch.quint8 2025-07-17T07:36:53.0902190Z 2025-07-17T07:36:53.0902304Z >>> dtype_config2.input_dtype 2025-07-17T07:36:53.0902390Z torch.quint8 2025-07-17T07:36:53.0902480Z 2025-07-17T07:36:53.0902611Z >>> dtype_config2.input_dtype_with_constraints 2025-07-17T07:36:53.0903148Z DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None) 2025-07-17T07:36:53.0903236Z 2025-07-17T07:36:53.0903572Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0903647Z 2025-07-17T07:36:53.0903751Z warnings.warn(msg) 2025-07-17T07:36:53.0903822Z 2025-07-17T07:36:53.0904006Z --- Parse Warning: 39 / 136 --- 2025-07-17T07:36:53.0905066Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReport in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report.py line=24. 2025-07-17T07:36:53.0905327Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0905415Z 2025-07-17T07:36:53.0905722Z The ModelReport class aims to provide users an easy way to diagnose issues that they run into 2025-07-17T07:36:53.0906016Z with their models. The class works with all traceable GraphModules to help diagnose issues, 2025-07-17T07:36:53.0906333Z though the requirements on the type of model more-so depends on the specific report the user 2025-07-17T07:36:53.0906630Z is trying to generate. With respect to the reports, the ModelReport class is initialized with 2025-07-17T07:36:53.0906914Z a set of Detector classes, each of which generate reports on quantization configuration 2025-07-17T07:36:53.0907017Z issues a use might have. 2025-07-17T07:36:53.0907095Z 2025-07-17T07:36:53.0907235Z Currently supports generating reports on: 2025-07-17T07:36:53.0907461Z - Suggestions for per-channel vs. per-tensor quantization (nn.Module) 2025-07-17T07:36:53.0907724Z - Suggestions for dynamic vs static quantization for linear layers (Graph Modules) 2025-07-17T07:36:53.0908025Z - Suggestions for input-weight equalization for linear and conv layers (Graph Modules) 2025-07-17T07:36:53.0908236Z - Suggestions for outlier detection for all layers (Graph Modules) 2025-07-17T07:36:53.0908352Z 2025-07-17T07:36:53.0908767Z The ModelReport class has the primary functionality of inserting observers (primarily the ModelReportObserver) 2025-07-17T07:36:53.0909140Z where needed for each detector to gather the information it needs, and then after calibration, the ModelReport 2025-07-17T07:36:53.0909522Z class compiles the report generated by each Detector class into a single report to return to the user. It also 2025-07-17T07:36:53.0909733Z has the capability to remove all the observers it inserted as well. 2025-07-17T07:36:53.0909808Z 2025-07-17T07:36:53.0910094Z * :attr:`_model` The model we wish to generate the report for. Must be a traceable GraphModule 2025-07-17T07:36:53.0910216Z 2025-07-17T07:36:53.0910597Z * :attr:`_desired_report_detectors` The set of Detectors representing desired reports from the ModelReport class 2025-07-17T07:36:53.0910906Z Make sure that these are all unique types of detectors [do not have more than 1 of the same class] 2025-07-17T07:36:53.0910982Z 2025-07-17T07:36:53.0911275Z * :attr:`_desired_detector_names` The set of detector names of the _desired_report_detectors. 2025-07-17T07:36:53.0911497Z This set is generated by calling the get_detector_name() of each detector 2025-07-17T07:36:53.0911571Z 2025-07-17T07:36:53.0911913Z * :attr:`_detector_name_to_observer_fqns` The mapping from each detector to fqns of observers of interest 2025-07-17T07:36:53.0912251Z The purpose of this is to keep track of what observers were inserted for each detector, so that they 2025-07-17T07:36:53.0912372Z can be removed at the end if desired 2025-07-17T07:36:53.0912447Z 2025-07-17T07:36:53.0912763Z * :attr:`_prepared_flag` A boolean flag that keeps track of whether we have prepared the model or not 2025-07-17T07:36:53.0913005Z This is to ensure we only insert observers once with the ModelReport instance 2025-07-17T07:36:53.0913082Z 2025-07-17T07:36:53.0913411Z * :attr:`_removed_observers` A boolean to track if we have removed observers already 2025-07-17T07:36:53.0913710Z The purpose is to ensure we don't attempt to remove observers twice with the same ModelReport 2025-07-17T07:36:53.0914026Z instance. This also allows the functionality where we can generate the report multiple times 2025-07-17T07:36:53.0914178Z as long as we haven't removed the observers yet. 2025-07-17T07:36:53.0914255Z 2025-07-17T07:36:53.0914337Z Note: 2025-07-17T07:36:53.0914641Z This class was initially designed to work with the Fx Graph Mode workflow in mind. However, 2025-07-17T07:36:53.0914952Z full functionality is available as long as there is a traceable GraphModule that is being used. 2025-07-17T07:36:53.0915245Z One method to get a traceable GraphModule without going through the Fx workflow is to use 2025-07-17T07:36:53.0915365Z the QuantizationTracer class. 2025-07-17T07:36:53.0915441Z 2025-07-17T07:36:53.0915541Z General Flow for Fx workflow: 2025-07-17T07:36:53.0915949Z 1.) Initialize ModelReport object with reports of interest by passing in initialized detector objects and model 2025-07-17T07:36:53.0916065Z 2.) Prepare your model with prepare_fx 2025-07-17T07:36:53.0916318Z 3.) Call model_report.prepare_detailed_calibration to add relevant observers 2025-07-17T07:36:53.0916424Z 4.) Calibrate your model with data 2025-07-17T07:36:53.0916774Z 5.) Call model_report.generate_report on your model to generate report and optionally remove added observers 2025-07-17T07:36:53.0916868Z Optional 2025-07-17T07:36:53.0917133Z 6.) Call model_report.generate_visualizer to get a ModelReportVisualizer instance 2025-07-17T07:36:53.0917372Z 7.) To help in parsing report information and debugging, view report info as a: 2025-07-17T07:36:53.0917466Z - Table 2025-07-17T07:36:53.0917556Z - Histogram 2025-07-17T07:36:53.0917654Z - Line plot 2025-07-17T07:36:53.0917973Z 8.) Call model_report.generate_qconfigs to generate the qconfigs based on the report suggestions 2025-07-17T07:36:53.0918046Z 2025-07-17T07:36:53.0918171Z Example (with QuantizationTracer): 2025-07-17T07:36:53.0918265Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0918363Z >>> # get the necessary qconfig 2025-07-17T07:36:53.0918494Z >>> config = PrepareCustomConfig() 2025-07-17T07:36:53.0918646Z >>> skipped_module_names, skipped_module_classes = ( 2025-07-17T07:36:53.0918804Z ... get_skipped_module_name_and_classes(config, False) 2025-07-17T07:36:53.0918899Z ... ) 2025-07-17T07:36:53.0918977Z 2025-07-17T07:36:53.0919121Z >>> # initialize our model and get GraphModule 2025-07-17T07:36:53.0919247Z >>> model = SomeModel() 2025-07-17T07:36:53.0919496Z >>> tracer = QuantizationTracer(skipped_module_names, skipped_module_classes) 2025-07-17T07:36:53.0919673Z >>> graph_module = GraphModule(model, tracer.trace(model)) 2025-07-17T07:36:53.0919750Z 2025-07-17T07:36:53.0919898Z >>> # get our set of detectors and ModelReport instance 2025-07-17T07:36:53.0920003Z >>> detector_set = set( 2025-07-17T07:36:53.0920083Z ... [ 2025-07-17T07:36:53.0920216Z ... DynamicStaticDetector(tolerance=0.5), 2025-07-17T07:36:53.0920436Z ... InputWeightEqualizationDetector(ratio_threshold=0.7), 2025-07-17T07:36:53.0920544Z ... ] 2025-07-17T07:36:53.0920632Z ... ) 2025-07-17T07:36:53.0920840Z >>> tracer_reporter = ModelReport(graph_module, tracer_detector_set) 2025-07-17T07:36:53.0920915Z 2025-07-17T07:36:53.0921069Z >>> # now we insert the observers and calibrate the model 2025-07-17T07:36:53.0921326Z >>> tracer_model_with_observers = tracer_reporter.prepare_detailed_calibration() 2025-07-17T07:36:53.0921451Z >>> for i in range(num_callibration_batches): 2025-07-17T07:36:53.0921588Z >>> example_input = get_callibration_input() 2025-07-17T07:36:53.0921768Z >>> tracer_model_with_observers(example_input) 2025-07-17T07:36:53.0921848Z 2025-07-17T07:36:53.0922115Z >>> # finally we generate the reports and optionally remove the observers we inserted 2025-07-17T07:36:53.0922267Z >>> reports = tracer_reporter.generate_model_report( 2025-07-17T07:36:53.0922396Z ... remove_inserted_observers=True 2025-07-17T07:36:53.0922476Z ... ) 2025-07-17T07:36:53.0922553Z 2025-07-17T07:36:53.0922785Z >>> # Optional: we can generate the qconfig mapping based on the suggestions 2025-07-17T07:36:53.0922942Z >>> qconfigs = model_report.generate_qconfig_mapping() 2025-07-17T07:36:53.0923020Z 2025-07-17T07:36:53.0923272Z >>> # Optional: we can generate the equalization mapping based on the suggestions 2025-07-17T07:36:53.0923445Z >>> qconfigs = model_report.generate_equalization_mapping() 2025-07-17T07:36:53.0923522Z 2025-07-17T07:36:53.0923819Z >>> # Optional: we get a ModelReportVisualizer instance to do any visualizations desired 2025-07-17T07:36:53.0924026Z >>> model_report_visualizer = tracer_reporter.generate_visualizer() 2025-07-17T07:36:53.0924116Z 2025-07-17T07:36:53.0924193Z 2025-07-17T07:36:53.0924445Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0924545Z 2025-07-17T07:36:53.0924643Z warnings.warn(msg) 2025-07-17T07:36:53.0924721Z 2025-07-17T07:36:53.0924930Z --- Parse Warning: 40 / 136 --- 2025-07-17T07:36:53.0926292Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_filtered_tables in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=301. 2025-07-17T07:36:53.0926573Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0926651Z 2025-07-17T07:36:53.0926920Z Takes in optional filter values and generates two tables with desired information. 2025-07-17T07:36:53.0927016Z 2025-07-17T07:36:53.0927224Z The generated tables are presented in both a list-of-lists format 2025-07-17T07:36:53.0927307Z 2025-07-17T07:36:53.0927526Z The reason for the two tables are that they handle different things: 2025-07-17T07:36:53.0927688Z 1.) the first table handles all tensor level information 2025-07-17T07:36:53.0927902Z 2.) the second table handles and displays all channel based information 2025-07-17T07:36:53.0927996Z 2025-07-17T07:36:53.0928314Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-07-17T07:36:53.0928692Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-07-17T07:36:53.0929045Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-07-17T07:36:53.0929125Z 2025-07-17T07:36:53.0929240Z Tensor table columns: 2025-07-17T07:36:53.0929430Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-07-17T07:36:53.0929583Z ---- --------- --------- --------- --------- --------- 2025-07-17T07:36:53.0929678Z 2025-07-17T07:36:53.0929824Z Per-Channel table columns: 2025-07-17T07:36:53.0930057Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-07-17T07:36:53.0930217Z ---- --------- ------- --------- --------- --------- --------- 2025-07-17T07:36:53.0930297Z 2025-07-17T07:36:53.0930391Z Args: 2025-07-17T07:36:53.0930657Z feature_filter (str, optional): Filters the features presented to only those that 2025-07-17T07:36:53.0930768Z contain this filter substring 2025-07-17T07:36:53.0930946Z Default = "", results in all the features being printed 2025-07-17T07:36:53.0931249Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-07-17T07:36:53.0931506Z Default = "", results in all the modules in the reports to be visible in the table 2025-07-17T07:36:53.0931586Z 2025-07-17T07:36:53.0931698Z Returns a dictionary with two keys: 2025-07-17T07:36:53.0931882Z (Dict[str, Tuple[List, List]]) A dict containing two keys: 2025-07-17T07:36:53.0932002Z "tensor_level_info", "channel_level_info" 2025-07-17T07:36:53.0932109Z Each key maps to a tuple with: 2025-07-17T07:36:53.0932233Z A list of the headers of each table 2025-07-17T07:36:53.0932414Z A list of lists containing the table information row by row 2025-07-17T07:36:53.0932583Z The 0th index row will contain the headers of the columns 2025-07-17T07:36:53.0932712Z The rest of the rows will contain data 2025-07-17T07:36:53.0932790Z 2025-07-17T07:36:53.0932887Z Example Use: 2025-07-17T07:36:53.0933016Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.0933162Z >>> mod_report_visualizer.generate_filtered_tables( 2025-07-17T07:36:53.0933364Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-07-17T07:36:53.0933634Z ... ) # generates table with per_channel_min info for all modules in block 1 of the model 2025-07-17T07:36:53.0933714Z 2025-07-17T07:36:53.0933975Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0934052Z 2025-07-17T07:36:53.0934149Z warnings.warn(msg) 2025-07-17T07:36:53.0934239Z 2025-07-17T07:36:53.0934438Z --- Parse Warning: 41 / 136 --- 2025-07-17T07:36:53.0935745Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_table_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=399. 2025-07-17T07:36:53.0936009Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0936088Z 2025-07-17T07:36:53.0936371Z Takes in optional filter values and prints out formatted tables of the information. 2025-07-17T07:36:53.0936451Z 2025-07-17T07:36:53.0936792Z The reason for the two tables printed out instead of one large one are that they handle different things: 2025-07-17T07:36:53.0936965Z 1.) the first table handles all tensor level information 2025-07-17T07:36:53.0937180Z 2.) the second table handles and displays all channel based information 2025-07-17T07:36:53.0937271Z 2025-07-17T07:36:53.0937624Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-07-17T07:36:53.0937951Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-07-17T07:36:53.0938321Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-07-17T07:36:53.0938398Z 2025-07-17T07:36:53.0938495Z Tensor table columns: 2025-07-17T07:36:53.0938699Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-07-17T07:36:53.0938847Z ---- --------- --------- --------- --------- --------- 2025-07-17T07:36:53.0938965Z 2025-07-17T07:36:53.0939068Z Per-Channel table columns: 2025-07-17T07:36:53.0939147Z 2025-07-17T07:36:53.0939373Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-07-17T07:36:53.0939529Z ---- --------- ------- --------- --------- --------- --------- 2025-07-17T07:36:53.0939608Z 2025-07-17T07:36:53.0939700Z Args: 2025-07-17T07:36:53.0939961Z feature_filter (str, optional): Filters the features presented to only those that 2025-07-17T07:36:53.0940070Z contain this filter substring 2025-07-17T07:36:53.0940348Z Default = "", results in all the features being printed 2025-07-17T07:36:53.0940695Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-07-17T07:36:53.0940998Z Default = "", results in all the modules in the reports to be visible in the table 2025-07-17T07:36:53.0941078Z 2025-07-17T07:36:53.0941163Z Example Use: 2025-07-17T07:36:53.0941304Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.0941469Z >>> mod_report_visualizer.generate_table_visualization( 2025-07-17T07:36:53.0941663Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-07-17T07:36:53.0941759Z ... ) 2025-07-17T07:36:53.0941952Z >>> # prints out neatly formatted table with per_channel_min info 2025-07-17T07:36:53.0942090Z >>> # for all modules in block 1 of the model 2025-07-17T07:36:53.0942180Z 2025-07-17T07:36:53.0942433Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0942531Z 2025-07-17T07:36:53.0942658Z warnings.warn(msg) 2025-07-17T07:36:53.0942737Z 2025-07-17T07:36:53.0942950Z --- Parse Warning: 42 / 136 --- 2025-07-17T07:36:53.0944238Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_plot_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=564. 2025-07-17T07:36:53.0944512Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0944591Z 2025-07-17T07:36:53.0944828Z Takes in a feature and optional module_filter and plots of the desired data. 2025-07-17T07:36:53.0944921Z 2025-07-17T07:36:53.0945195Z For per channel features, it averages the value across the channels and plots a point 2025-07-17T07:36:53.0945454Z per module. The reason for this is that for models with hundreds of channels, it can 2025-07-17T07:36:53.0945742Z be hard to differentiate one channel line from another, and so the point of generating 2025-07-17T07:36:53.0946012Z a single average point per module is to give a sense of general trends that encourage 2025-07-17T07:36:53.0946121Z further deep dives. 2025-07-17T07:36:53.0946201Z 2025-07-17T07:36:53.0946280Z Note: 2025-07-17T07:36:53.0946554Z Only features in the report that have tensor value data are plottable by this class 2025-07-17T07:36:53.0946715Z When the tensor information is plotted, it will plot: 2025-07-17T07:36:53.0946847Z idx as the x val, feature value as the y_val 2025-07-17T07:36:53.0947064Z When the channel information is plotted, it will plot: 2025-07-17T07:36:53.0947326Z the first idx of each module as the x val, feature value as the y_val [for each channel] 2025-07-17T07:36:53.0947549Z The reason for this is that we want to be able to compare values across the 2025-07-17T07:36:53.0947793Z channels for same layer, and it will be hard if values are staggered by idx 2025-07-17T07:36:53.0947958Z This means each module is represented by only 1 x value 2025-07-17T07:36:53.0948050Z Args: 2025-07-17T07:36:53.0948272Z feature_filter (str): Filters the features presented to only those that 2025-07-17T07:36:53.0948414Z contain this filter substring 2025-07-17T07:36:53.0948683Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-07-17T07:36:53.0948925Z Default = "", results in all the modules in the reports to be visible in the table 2025-07-17T07:36:53.0949004Z 2025-07-17T07:36:53.0949102Z Example Use: 2025-07-17T07:36:53.0949227Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.0949401Z >>> mod_report_visualizer.generate_plot_visualization( 2025-07-17T07:36:53.0949641Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-07-17T07:36:53.0949722Z ... ) 2025-07-17T07:36:53.0949911Z >>> # outputs line plot of per_channel_min information for all 2025-07-17T07:36:53.0950091Z >>> # modules in block1 of model each channel gets it's own line, 2025-07-17T07:36:53.0950262Z >>> # and it's plotted across the in-order modules on the x-axis 2025-07-17T07:36:53.0950354Z 2025-07-17T07:36:53.0950602Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0950679Z 2025-07-17T07:36:53.0950785Z warnings.warn(msg) 2025-07-17T07:36:53.0950862Z 2025-07-17T07:36:53.0951058Z --- Parse Warning: 43 / 136 --- 2025-07-17T07:36:53.0952574Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_histogram_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=643. 2025-07-17T07:36:53.0952837Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0952925Z 2025-07-17T07:36:53.0953202Z Takes in a feature and optional module_filter and plots the histogram of desired data. 2025-07-17T07:36:53.0953279Z 2025-07-17T07:36:53.0953370Z Note: 2025-07-17T07:36:53.0953634Z Only features in the report that have tensor value data can be viewed as a histogram 2025-07-17T07:36:53.0953904Z If you want to plot a histogram from all the channel values of a specific feature for 2025-07-17T07:36:53.0954148Z a specific model, make sure to specify both the model and the feature properly 2025-07-17T07:36:53.0954392Z in the filters and you should be able to see a distribution of the channel data 2025-07-17T07:36:53.0954481Z 2025-07-17T07:36:53.0954560Z Args: 2025-07-17T07:36:53.0954823Z feature_filter (str, optional): Filters the features presented to only those that 2025-07-17T07:36:53.0954941Z contain this filter substring 2025-07-17T07:36:53.0955113Z Default = "", results in all the features being printed 2025-07-17T07:36:53.0955381Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-07-17T07:36:53.0955623Z Default = "", results in all the modules in the reports to be visible in the table 2025-07-17T07:36:53.0955842Z num_bins (int, optional): The number of bins to create the histogram with 2025-07-17T07:36:53.0956035Z Default = 10, the values will be split into 10 equal sized bins 2025-07-17T07:36:53.0956155Z 2025-07-17T07:36:53.0956243Z Example Use: 2025-07-17T07:36:53.0956355Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.0956657Z >>> mod_report_visualizer.generategenerate_histogram_visualization_plot_visualization( 2025-07-17T07:36:53.0956858Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-07-17T07:36:53.0956944Z ... ) 2025-07-17T07:36:53.0957223Z # outputs histogram of per_channel_min information for all modules in block1 of model 2025-07-17T07:36:53.0957488Z information is gathered across all channels for all modules in block 1 for the 2025-07-17T07:36:53.0957735Z per_channel_min and is displayed in a histogram of equally sized bins 2025-07-17T07:36:53.0957813Z 2025-07-17T07:36:53.0958080Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0958160Z 2025-07-17T07:36:53.0958257Z warnings.warn(msg) 2025-07-17T07:36:53.0958350Z 2025-07-17T07:36:53.0958550Z --- Parse Warning: 44 / 136 --- 2025-07-17T07:36:53.0959473Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=record_function in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py line=734. 2025-07-17T07:36:53.0959787Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0960173Z Context manager/function decorator that adds a label to a code block/function when running autograd profiler. 2025-07-17T07:36:53.0960367Z Label will only appear if CPU activity tracing is enabled. 2025-07-17T07:36:53.0960447Z 2025-07-17T07:36:53.0960575Z It is useful when tracing the code profile. 2025-07-17T07:36:53.0960666Z 2025-07-17T07:36:53.0960746Z Args: 2025-07-17T07:36:53.0960899Z name (str): Label assigned to the block of code. 2025-07-17T07:36:53.0961081Z node_id (int): ID of node, for distributed profiling. Unset in 2025-07-17T07:36:53.0961196Z non-distributed cases. 2025-07-17T07:36:53.0961287Z 2025-07-17T07:36:53.0961370Z Example: 2025-07-17T07:36:53.0961551Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_AUTOGRAD_PROFILER) 2025-07-17T07:36:53.0961697Z >>> x = torch.randn((1, 1), requires_grad=True) 2025-07-17T07:36:53.0961856Z >>> with torch.autograd.profiler.profile() as prof: 2025-07-17T07:36:53.0961945Z ... y = x**2 2025-07-17T07:36:53.0962119Z ... with torch.autograd.profiler.record_function( 2025-07-17T07:36:53.0962240Z ... "label-z" 2025-07-17T07:36:53.0962353Z ... ): # label the block 2025-07-17T07:36:53.0962443Z ... z = y**3 2025-07-17T07:36:53.0962537Z ... y.backward() 2025-07-17T07:36:53.0962653Z >>> # xdoctest: +IGNORE_WANT 2025-07-17T07:36:53.0962787Z >>> # NOTE: some columns were removed for brevity 2025-07-17T07:36:53.0962990Z >>> print(prof.key_averages().table(sort_by="self_cpu_time_total")) 2025-07-17T07:36:53.0963196Z ----------------------------------- --------------- --------------- --------------- 2025-07-17T07:36:53.0963377Z Name Self CPU total % CPU time avg Number of Calls 2025-07-17T07:36:53.0963578Z ----------------------------------- --------------- --------------- --------------- 2025-07-17T07:36:53.0963708Z pow 60.77% 47.470us 3 2025-07-17T07:36:53.0963836Z mul 21.73% 25.465us 2 2025-07-17T07:36:53.0964020Z PowBackward0 12.03% 121.891us 1 2025-07-17T07:36:53.0964244Z torch::autograd::AccumulateGrad 2.70% 6.324us 1 2025-07-17T07:36:53.0964383Z label-z 2.13% 12.421us 1 2025-07-17T07:36:53.0964634Z torch::autograd::GraphRoot 0.64% 1.503us 1 2025-07-17T07:36:53.0964823Z ----------------------------------- --------------- --------------- --------------- 2025-07-17T07:36:53.0964951Z Self CPU time total: 234.344us 2025-07-17T07:36:53.0965052Z CUDA time total: 0.000us 2025-07-17T07:36:53.0965130Z 2025-07-17T07:36:53.0965226Z 2025-07-17T07:36:53.0965547Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0965624Z 2025-07-17T07:36:53.0965765Z warnings.warn(msg) 2025-07-17T07:36:53.0965841Z 2025-07-17T07:36:53.0966035Z --- Parse Warning: 45 / 136 --- 2025-07-17T07:36:53.0967018Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py line=685. 2025-07-17T07:36:53.0967269Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:53.0967359Z 2025-07-17T07:36:53.0967629Z Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh. 2025-07-17T07:36:53.0967948Z The submesh created consists of the dimensions and the communicators indicated by 2025-07-17T07:36:53.0968050Z ``mesh_dim_names`` 2025-07-17T07:36:53.0968126Z 2025-07-17T07:36:53.0968208Z Args: 2025-07-17T07:36:53.0968454Z mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the 2025-07-17T07:36:53.0968637Z mesh dimension of the DeviceMesh to create the submesh for. 2025-07-17T07:36:53.0968729Z Returns: 2025-07-17T07:36:53.0968830Z A :class:`DeviceMesh` object 2025-07-17T07:36:53.0968906Z 2025-07-17T07:36:53.0969198Z The following program runs on each process/rank in an SPMD manner in a world size of 8. 2025-07-17T07:36:53.0969294Z In the first example: 2025-07-17T07:36:53.0969541Z Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]). 2025-07-17T07:36:53.0969797Z Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of DeviceMesh:([4, 5, 6, 7]). 2025-07-17T07:36:53.0970281Z Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of DeviceMesh:([0, 4]). 2025-07-17T07:36:53.0970525Z Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of DeviceMesh:([1, 5]). 2025-07-17T07:36:53.0970740Z Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of DeviceMesh:([2, 6]). 2025-07-17T07:36:53.0970956Z Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of DeviceMesh:([3, 7]). 2025-07-17T07:36:53.0971044Z 2025-07-17T07:36:53.0971141Z In the second example: 2025-07-17T07:36:53.0971401Z Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]). 2025-07-17T07:36:53.0971675Z Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]). 2025-07-17T07:36:53.0971931Z Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]). 2025-07-17T07:36:53.0972201Z Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]). 2025-07-17T07:36:53.0972278Z 2025-07-17T07:36:53.0972369Z Example:: 2025-07-17T07:36:53.0972458Z 2025-07-17T07:36:53.0972564Z >>> # xdoctest: +SKIP("no rank") 2025-07-17T07:36:53.0972736Z >>> from torch.distributed.device_mesh import DeviceMesh 2025-07-17T07:36:53.0972828Z >>> 2025-07-17T07:36:53.0973026Z >>> # Initialize a 2D device mesh as (2, 4) to represent the topology 2025-07-17T07:36:53.0973164Z >>> # of cross-host(dim 0), and within-host (dim 1). 2025-07-17T07:36:53.0973424Z >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-07-17T07:36:53.0973598Z >>> tp_mesh = mesh_2d["tp"] 2025-07-17T07:36:53.0973710Z >>> dp_mesh = mesh_2d["dp"] 2025-07-17T07:36:53.0973790Z >>> 2025-07-17T07:36:53.0973886Z >>> # Initialize a 3D mesh. 2025-07-17T07:36:53.0974175Z >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp")) 2025-07-17T07:36:53.0974476Z >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh. 2025-07-17T07:36:53.0974588Z >>> dp_cp_mesh = mesh_3d["dp", "cp"] 2025-07-17T07:36:53.0974709Z >>> cp_dp_mesh = mesh_3d["cp", "dp"] 2025-07-17T07:36:53.0974824Z 2025-07-17T07:36:53.0975510Z Original Error: SyntaxError('positional argument follows keyword argument', ('', 6, 82, 'mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))\n', 6, 83)) 2025-07-17T07:36:53.0975587Z 2025-07-17T07:36:53.0975829Z mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-07-17T07:36:53.0975955Z ^ 2025-07-17T07:36:53.0976051Z warnings.warn(msg) 2025-07-17T07:36:53.0976129Z 2025-07-17T07:36:53.0976343Z --- Parse Warning: 46 / 136 --- 2025-07-17T07:36:53.0977393Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=batch_isend_irecv in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2706. 2025-07-17T07:36:53.0977670Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0977748Z 2025-07-17T07:36:53.0977996Z Send or Receive a batch of tensors asynchronously and return a list of requests. 2025-07-17T07:36:53.0978087Z 2025-07-17T07:36:53.0978330Z Process each of the operations in ``p2p_op_list`` and return the corresponding 2025-07-17T07:36:53.0978527Z requests. NCCL, Gloo, and UCC backend are currently supported. 2025-07-17T07:36:53.0978618Z 2025-07-17T07:36:53.0978702Z Args: 2025-07-17T07:36:53.0978940Z p2p_op_list: A list of point-to-point operations(type of each operator is 2025-07-17T07:36:53.0979171Z ``torch.distributed.P2POp``). The order of the isend/irecv in the list 2025-07-17T07:36:53.0979380Z matters and it needs to match with corresponding isend/irecv on the 2025-07-17T07:36:53.0979483Z remote end. 2025-07-17T07:36:53.0979561Z 2025-07-17T07:36:53.0979644Z Returns: 2025-07-17T07:36:53.0979901Z A list of distributed request objects returned by calling the corresponding 2025-07-17T07:36:53.0979995Z op in the op_list. 2025-07-17T07:36:53.0980074Z 2025-07-17T07:36:53.0980169Z Examples: 2025-07-17T07:36:53.0980274Z >>> # xdoctest: +SKIP("no rank") 2025-07-17T07:36:53.0980458Z >>> send_tensor = torch.arange(2, dtype=torch.float32) + 2 * rank 2025-07-17T07:36:53.0980616Z >>> recv_tensor = torch.randn(2, dtype=torch.float32) 2025-07-17T07:36:53.0980824Z >>> send_op = dist.P2POp(dist.isend, send_tensor, (rank + 1) % world_size) 2025-07-17T07:36:53.0980935Z >>> recv_op = dist.P2POp( 2025-07-17T07:36:53.0981122Z ... dist.irecv, recv_tensor, (rank - 1 + world_size) % world_size 2025-07-17T07:36:53.0981201Z ... ) 2025-07-17T07:36:53.0981344Z >>> reqs = batch_isend_irecv([send_op, recv_op]) 2025-07-17T07:36:53.0981436Z >>> for req in reqs: 2025-07-17T07:36:53.0981524Z >>> req.wait() 2025-07-17T07:36:53.0981623Z >>> recv_tensor 2025-07-17T07:36:53.0981717Z tensor([2, 3]) # Rank 0 2025-07-17T07:36:53.0981808Z tensor([0, 1]) # Rank 1 2025-07-17T07:36:53.0981896Z 2025-07-17T07:36:53.0982134Z .. note:: Note that when this API is used with the NCCL PG backend, users must set 2025-07-17T07:36:53.0982364Z the current GPU device with `torch.cuda.set_device`, otherwise it will 2025-07-17T07:36:53.0982497Z lead to unexpected hang issues. 2025-07-17T07:36:53.0982573Z 2025-07-17T07:36:53.0982789Z In addition, if this API is the first collective call in the ``group`` 2025-07-17T07:36:53.0983008Z passed to ``dist.P2POp``, all ranks of the ``group`` must participate in 2025-07-17T07:36:53.0983229Z this API call; otherwise, the behavior is undefined. If this API call is 2025-07-17T07:36:53.0983456Z not the first collective call in the ``group``, batched P2P operations 2025-07-17T07:36:53.0983648Z involving only a subset of ranks of the ``group`` are allowed. 2025-07-17T07:36:53.0983764Z 2025-07-17T07:36:53.0984011Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0984087Z 2025-07-17T07:36:53.0984193Z warnings.warn(msg) 2025-07-17T07:36:53.0984271Z 2025-07-17T07:36:53.0984457Z --- Parse Warning: 47 / 136 --- 2025-07-17T07:36:53.0985414Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_reduce in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2838. 2025-07-17T07:36:53.0985722Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0985813Z 2025-07-17T07:36:53.0986075Z Reduces the tensor data across all machines in a way that all get the final result. 2025-07-17T07:36:53.0986184Z 2025-07-17T07:36:53.0986437Z After the call ``tensor`` is going to be bitwise identical in all processes. 2025-07-17T07:36:53.0986516Z 2025-07-17T07:36:53.0986623Z Complex tensors are supported. 2025-07-17T07:36:53.0986710Z 2025-07-17T07:36:53.0986791Z Args: 2025-07-17T07:36:53.0986991Z tensor (Tensor): Input and output of the collective. The function 2025-07-17T07:36:53.0987102Z operates in-place. 2025-07-17T07:36:53.0987220Z op (optional): One of the values from 2025-07-17T07:36:53.0987348Z ``torch.distributed.ReduceOp`` 2025-07-17T07:36:53.0987548Z enum. Specifies an operation used for element-wise reductions. 2025-07-17T07:36:53.0987780Z group (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:53.0987916Z the default process group will be used. 2025-07-17T07:36:53.0988107Z async_op (bool, optional): Whether this op should be an async op 2025-07-17T07:36:53.0988184Z 2025-07-17T07:36:53.0988276Z Returns: 2025-07-17T07:36:53.0988414Z Async work handle, if async_op is set to True. 2025-07-17T07:36:53.0988555Z None, if not async_op or if not part of the group 2025-07-17T07:36:53.0988644Z 2025-07-17T07:36:53.0988729Z Examples: 2025-07-17T07:36:53.0988833Z >>> # xdoctest: +SKIP("no rank") 2025-07-17T07:36:53.0988976Z >>> # All tensors below are of torch.int64 type. 2025-07-17T07:36:53.0989091Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:53.0989219Z >>> device = torch.device(f"cuda:{rank}") 2025-07-17T07:36:53.0989441Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-07-17T07:36:53.0989526Z >>> tensor 2025-07-17T07:36:53.0989654Z tensor([1, 2], device='cuda:0') # Rank 0 2025-07-17T07:36:53.0989764Z tensor([3, 4], device='cuda:1') # Rank 1 2025-07-17T07:36:53.0989897Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-07-17T07:36:53.0989996Z >>> tensor 2025-07-17T07:36:53.0990104Z tensor([4, 6], device='cuda:0') # Rank 0 2025-07-17T07:36:53.0990226Z tensor([4, 6], device='cuda:1') # Rank 1 2025-07-17T07:36:53.0990304Z 2025-07-17T07:36:53.0990438Z >>> # All tensors below are of torch.cfloat type. 2025-07-17T07:36:53.0990562Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:53.0990661Z >>> tensor = torch.tensor( 2025-07-17T07:36:53.0990832Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-07-17T07:36:53.0990934Z ... ) + 2 * rank * (1 + 1j) 2025-07-17T07:36:53.0991015Z >>> tensor 2025-07-17T07:36:53.0991149Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-07-17T07:36:53.0991297Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-07-17T07:36:53.0991424Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-07-17T07:36:53.0991502Z >>> tensor 2025-07-17T07:36:53.0991647Z tensor([4.+4.j, 6.+6.j], device='cuda:0') # Rank 0 2025-07-17T07:36:53.0991775Z tensor([4.+4.j, 6.+6.j], device='cuda:1') # Rank 1 2025-07-17T07:36:53.0991887Z 2025-07-17T07:36:53.0991964Z 2025-07-17T07:36:53.0992219Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.0992307Z 2025-07-17T07:36:53.0992402Z warnings.warn(msg) 2025-07-17T07:36:53.0992481Z 2025-07-17T07:36:53.0992681Z --- Parse Warning: 48 / 136 --- 2025-07-17T07:36:53.0993645Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=gather_object in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3198. 2025-07-17T07:36:53.0993982Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.0994063Z 2025-07-17T07:36:53.0994286Z Gathers picklable objects from the whole group in a single process. 2025-07-17T07:36:53.0994378Z 2025-07-17T07:36:53.0994609Z Similar to :func:`gather`, but Python objects can be passed in. Note that the 2025-07-17T07:36:53.0994756Z object must be picklable in order to be gathered. 2025-07-17T07:36:53.0994849Z 2025-07-17T07:36:53.0994932Z Args: 2025-07-17T07:36:53.0995058Z obj (Any): Input object. Must be picklable. 2025-07-17T07:36:53.0995276Z object_gather_list (list[Any]): Output list. On the ``dst`` rank, it 2025-07-17T07:36:53.0995461Z should be correctly sized as the size of the group for this 2025-07-17T07:36:53.0995688Z collective and will contain the output. Must be ``None`` on non-dst 2025-07-17T07:36:53.0995794Z ranks. (default is ``None``) 2025-07-17T07:36:53.0996119Z dst (int, optional): Destination rank on global process group (regardless of ``group`` argument). 2025-07-17T07:36:53.0996325Z (If both ``dst`` and ``group_dst`` are None, default is global rank 0) 2025-07-17T07:36:53.0996557Z group: (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:53.0996746Z the default process group will be used. Default is ``None``. 2025-07-17T07:36:53.0997104Z group_dst (int, optional): Destination rank on ``group``. Invalid to specify both ``dst`` and ``group_dst`` 2025-07-17T07:36:53.0997185Z 2025-07-17T07:36:53.0997281Z Returns: 2025-07-17T07:36:53.0997463Z None. On the ``dst`` rank, ``object_gather_list`` will contain the 2025-07-17T07:36:53.0997566Z output of the collective. 2025-07-17T07:36:53.0997661Z 2025-07-17T07:36:53.0997872Z .. note:: Note that this API differs slightly from the gather collective 2025-07-17T07:36:53.0998091Z since it does not provide an async_op handle and thus will be a blocking 2025-07-17T07:36:53.0998185Z call. 2025-07-17T07:36:53.0998265Z 2025-07-17T07:36:53.0998492Z .. note:: For NCCL-based processed groups, internal tensor representations 2025-07-17T07:36:53.0998712Z of objects must be moved to the GPU device before communication takes 2025-07-17T07:36:53.0998856Z place. In this case, the device used is given by 2025-07-17T07:36:53.0999085Z ``torch.cuda.current_device()`` and it is the user's responsibility to 2025-07-17T07:36:53.0999286Z ensure that this is set so that each rank has an individual GPU, via 2025-07-17T07:36:53.0999393Z ``torch.cuda.set_device()``. 2025-07-17T07:36:53.0999509Z 2025-07-17T07:36:53.0999596Z .. warning:: 2025-07-17T07:36:53.0999842Z Object collectives have a number of serious performance and scalability 2025-07-17T07:36:53.1000028Z limitations. See :ref:`object_collectives` for details. 2025-07-17T07:36:53.1000105Z 2025-07-17T07:36:53.1000205Z .. warning:: 2025-07-17T07:36:53.1000398Z :func:`gather_object` uses ``pickle`` module implicitly, which is 2025-07-17T07:36:53.1000612Z known to be insecure. It is possible to construct malicious pickle data 2025-07-17T07:36:53.1000836Z which will execute arbitrary code during unpickling. Only call this 2025-07-17T07:36:53.1000967Z function with data you trust. 2025-07-17T07:36:53.1001043Z 2025-07-17T07:36:53.1001137Z .. warning:: 2025-07-17T07:36:53.1001344Z Calling :func:`gather_object` with GPU tensors is not well supported 2025-07-17T07:36:53.1001562Z and inefficient as it incurs GPU -> CPU transfer since tensors would be 2025-07-17T07:36:53.1001739Z pickled. Please consider using :func:`gather` instead. 2025-07-17T07:36:53.1001819Z 2025-07-17T07:36:53.1001912Z Example:: 2025-07-17T07:36:53.1002043Z >>> # xdoctest: +SKIP("need process group init") 2025-07-17T07:36:53.1002265Z >>> # Note: Process group initialization omitted on each rank. 2025-07-17T07:36:53.1002395Z >>> import torch.distributed as dist 2025-07-17T07:36:53.1002497Z >>> # Assumes world_size of 3. 2025-07-17T07:36:53.1002672Z >>> gather_objects = ["foo", 12, {1: 2}] # any picklable object 2025-07-17T07:36:53.1002805Z >>> output = [None for _ in gather_objects] 2025-07-17T07:36:53.1002904Z >>> dist.gather_object( 2025-07-17T07:36:53.1003034Z ... gather_objects[dist.get_rank()], 2025-07-17T07:36:53.1003174Z ... output if dist.get_rank() == 0 else None, 2025-07-17T07:36:53.1003258Z ... dst=0 2025-07-17T07:36:53.1003351Z ... ) 2025-07-17T07:36:53.1003435Z >>> # On rank 0 2025-07-17T07:36:53.1003523Z >>> output 2025-07-17T07:36:53.1003622Z ['foo', 12, {1: 2}] 2025-07-17T07:36:53.1003698Z 2025-07-17T07:36:53.1003950Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1004042Z 2025-07-17T07:36:53.1004138Z warnings.warn(msg) 2025-07-17T07:36:53.1004214Z 2025-07-17T07:36:53.1004415Z --- Parse Warning: 49 / 136 --- 2025-07-17T07:36:53.1005436Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_gather in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3794. 2025-07-17T07:36:53.1005714Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1005793Z 2025-07-17T07:36:53.1005931Z Gathers tensors from the whole group in a list. 2025-07-17T07:36:53.1006022Z 2025-07-17T07:36:53.1006164Z Complex and uneven sized tensors are supported. 2025-07-17T07:36:53.1006241Z 2025-07-17T07:36:53.1006335Z Args: 2025-07-17T07:36:53.1006511Z tensor_list (list[Tensor]): Output list. It should contain 2025-07-17T07:36:53.1006727Z correctly-sized tensors to be used for output of the collective. 2025-07-17T07:36:53.1006858Z Uneven sized tensors are supported. 2025-07-17T07:36:53.1007044Z tensor (Tensor): Tensor to be broadcast from current process. 2025-07-17T07:36:53.1007280Z group (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:53.1007406Z the default process group will be used. 2025-07-17T07:36:53.1007597Z async_op (bool, optional): Whether this op should be an async op 2025-07-17T07:36:53.1007684Z 2025-07-17T07:36:53.1007766Z Returns: 2025-07-17T07:36:53.1007902Z Async work handle, if async_op is set to True. 2025-07-17T07:36:53.1008100Z None, if not async_op or if not part of the group 2025-07-17T07:36:53.1008214Z 2025-07-17T07:36:53.1008330Z Examples: 2025-07-17T07:36:53.1008519Z >>> # xdoctest: +SKIP("need process group init") 2025-07-17T07:36:53.1008691Z >>> # All tensors below are of torch.int64 dtype. 2025-07-17T07:36:53.1008872Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:53.1009046Z >>> device = torch.device(f"cuda:{rank}") 2025-07-17T07:36:53.1009184Z >>> tensor_list = [ 2025-07-17T07:36:53.1009516Z ... torch.zeros(2, dtype=torch.int64, device=device) for _ in range(2) 2025-07-17T07:36:53.1009676Z ... ] 2025-07-17T07:36:53.1009765Z >>> tensor_list 2025-07-17T07:36:53.1009977Z [tensor([0, 0], device='cuda:0'), tensor([0, 0], device='cuda:0')] # Rank 0 2025-07-17T07:36:53.1010170Z [tensor([0, 0], device='cuda:1'), tensor([0, 0], device='cuda:1')] # Rank 1 2025-07-17T07:36:53.1010393Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-07-17T07:36:53.1010495Z >>> tensor 2025-07-17T07:36:53.1010608Z tensor([1, 2], device='cuda:0') # Rank 0 2025-07-17T07:36:53.1010734Z tensor([3, 4], device='cuda:1') # Rank 1 2025-07-17T07:36:53.1010887Z >>> dist.all_gather(tensor_list, tensor) 2025-07-17T07:36:53.1011034Z >>> tensor_list 2025-07-17T07:36:53.1011234Z [tensor([1, 2], device='cuda:0'), tensor([3, 4], device='cuda:0')] # Rank 0 2025-07-17T07:36:53.1011421Z [tensor([1, 2], device='cuda:1'), tensor([3, 4], device='cuda:1')] # Rank 1 2025-07-17T07:36:53.1011500Z 2025-07-17T07:36:53.1011650Z >>> # All tensors below are of torch.cfloat dtype. 2025-07-17T07:36:53.1011763Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:53.1011855Z >>> tensor_list = [ 2025-07-17T07:36:53.1012078Z ... torch.zeros(2, dtype=torch.cfloat, device=device) for _ in range(2) 2025-07-17T07:36:53.1012158Z ... ] 2025-07-17T07:36:53.1012259Z >>> tensor_list 2025-07-17T07:36:53.1012503Z [tensor([0.+0.j, 0.+0.j], device='cuda:0'), tensor([0.+0.j, 0.+0.j], device='cuda:0')] # Rank 0 2025-07-17T07:36:53.1012740Z [tensor([0.+0.j, 0.+0.j], device='cuda:1'), tensor([0.+0.j, 0.+0.j], device='cuda:1')] # Rank 1 2025-07-17T07:36:53.1012854Z >>> tensor = torch.tensor( 2025-07-17T07:36:53.1012994Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-07-17T07:36:53.1013088Z ... ) + 2 * rank * (1 + 1j) 2025-07-17T07:36:53.1013178Z >>> tensor 2025-07-17T07:36:53.1013314Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-07-17T07:36:53.1013457Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-07-17T07:36:53.1013572Z >>> dist.all_gather(tensor_list, tensor) 2025-07-17T07:36:53.1013658Z >>> tensor_list 2025-07-17T07:36:53.1013903Z [tensor([1.+1.j, 2.+2.j], device='cuda:0'), tensor([3.+3.j, 4.+4.j], device='cuda:0')] # Rank 0 2025-07-17T07:36:53.1014137Z [tensor([1.+1.j, 2.+2.j], device='cuda:1'), tensor([3.+3.j, 4.+4.j], device='cuda:1')] # Rank 1 2025-07-17T07:36:53.1014213Z 2025-07-17T07:36:53.1014301Z 2025-07-17T07:36:53.1014555Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1014635Z 2025-07-17T07:36:53.1014739Z warnings.warn(msg) 2025-07-17T07:36:53.1014816Z 2025-07-17T07:36:53.1015049Z --- Parse Warning: 50 / 136 --- 2025-07-17T07:36:53.1016019Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_to_all_single in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4500. 2025-07-17T07:36:53.1016280Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1016367Z 2025-07-17T07:36:53.1016617Z Split input tensor and then scatter the split list to all processes in a group. 2025-07-17T07:36:53.1016726Z 2025-07-17T07:36:53.1016992Z Later the received tensors are concatenated from all the processes in the group 2025-07-17T07:36:53.1017109Z and returned as a single output tensor. 2025-07-17T07:36:53.1017197Z 2025-07-17T07:36:53.1017302Z Complex tensors are supported. 2025-07-17T07:36:53.1017383Z 2025-07-17T07:36:53.1017474Z Args: 2025-07-17T07:36:53.1017637Z output (Tensor): Gathered concatenated output tensor. 2025-07-17T07:36:53.1017758Z input (Tensor): Input tensor to scatter. 2025-07-17T07:36:53.1017988Z output_split_sizes: (list[Int], optional): Output split sizes for dim 0 2025-07-17T07:36:53.1018220Z if specified None or empty, dim 0 of ``output`` tensor must divide 2025-07-17T07:36:53.1018322Z equally by ``world_size``. 2025-07-17T07:36:53.1018543Z input_split_sizes: (list[Int], optional): Input split sizes for dim 0 2025-07-17T07:36:53.1018739Z if specified None or empty, dim 0 of ``input`` tensor must divide 2025-07-17T07:36:53.1018855Z equally by ``world_size``. 2025-07-17T07:36:53.1019082Z group (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:53.1019205Z the default process group will be used. 2025-07-17T07:36:53.1019456Z async_op (bool, optional): Whether this op should be an async op. 2025-07-17T07:36:53.1019534Z 2025-07-17T07:36:53.1019618Z Returns: 2025-07-17T07:36:53.1019771Z Async work handle, if async_op is set to True. 2025-07-17T07:36:53.1019913Z None, if not async_op or if not part of the group. 2025-07-17T07:36:53.1019993Z 2025-07-17T07:36:53.1020094Z .. warning:: 2025-07-17T07:36:53.1020263Z `all_to_all_single` is experimental and subject to change. 2025-07-17T07:36:53.1020352Z 2025-07-17T07:36:53.1020436Z Examples: 2025-07-17T07:36:53.1020553Z >>> # xdoctest: +SKIP("Undefined rank") 2025-07-17T07:36:53.1020679Z >>> input = torch.arange(4) + rank * 4 2025-07-17T07:36:53.1020759Z >>> input 2025-07-17T07:36:53.1020856Z tensor([0, 1, 2, 3]) # Rank 0 2025-07-17T07:36:53.1020960Z tensor([4, 5, 6, 7]) # Rank 1 2025-07-17T07:36:53.1021054Z tensor([8, 9, 10, 11]) # Rank 2 2025-07-17T07:36:53.1021153Z tensor([12, 13, 14, 15]) # Rank 3 2025-07-17T07:36:53.1021299Z >>> output = torch.empty([4], dtype=torch.int64) 2025-07-17T07:36:53.1021417Z >>> dist.all_to_all_single(output, input) 2025-07-17T07:36:53.1021499Z >>> output 2025-07-17T07:36:53.1021604Z tensor([0, 4, 8, 12]) # Rank 0 2025-07-17T07:36:53.1021700Z tensor([1, 5, 9, 13]) # Rank 1 2025-07-17T07:36:53.1021803Z tensor([2, 6, 10, 14]) # Rank 2 2025-07-17T07:36:53.1021894Z tensor([3, 7, 11, 15]) # Rank 3 2025-07-17T07:36:53.1021972Z 2025-07-17T07:36:53.1022140Z >>> # Essentially, it is similar to following operation: 2025-07-17T07:36:53.1022291Z >>> scatter_list = list(input.chunk(world_size)) 2025-07-17T07:36:53.1022425Z >>> gather_list = list(output.chunk(world_size)) 2025-07-17T07:36:53.1022540Z >>> for i in range(world_size): 2025-07-17T07:36:53.1022768Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src = i) 2025-07-17T07:36:53.1022849Z 2025-07-17T07:36:53.1022977Z >>> # Another example with uneven split 2025-07-17T07:36:53.1023061Z >>> input 2025-07-17T07:36:53.1023225Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-07-17T07:36:53.1023389Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-07-17T07:36:53.1023540Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-07-17T07:36:53.1023706Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-07-17T07:36:53.1023799Z >>> input_splits 2025-07-17T07:36:53.1023948Z [2, 2, 1, 1] # Rank 0 2025-07-17T07:36:53.1024079Z [3, 2, 2, 2] # Rank 1 2025-07-17T07:36:53.1024194Z [2, 1, 1, 1] # Rank 2 2025-07-17T07:36:53.1024329Z [2, 2, 2, 1] # Rank 3 2025-07-17T07:36:53.1024425Z >>> output_splits 2025-07-17T07:36:53.1024541Z [2, 3, 2, 2] # Rank 0 2025-07-17T07:36:53.1024671Z [2, 2, 1, 2] # Rank 1 2025-07-17T07:36:53.1024812Z [1, 2, 1, 2] # Rank 2 2025-07-17T07:36:53.1024929Z [1, 2, 1, 1] # Rank 3 2025-07-17T07:36:53.1025034Z >>> output = ... 2025-07-17T07:36:53.1025238Z >>> dist.all_to_all_single(output, input, output_splits, input_splits) 2025-07-17T07:36:53.1025340Z >>> output 2025-07-17T07:36:53.1025493Z tensor([ 0, 1, 10, 11, 12, 20, 21, 30, 31]) # Rank 0 2025-07-17T07:36:53.1025643Z tensor([ 2, 3, 13, 14, 22, 32, 33]) # Rank 1 2025-07-17T07:36:53.1025868Z tensor([ 4, 15, 16, 23, 34, 35]) # Rank 2 2025-07-17T07:36:53.1026016Z tensor([ 5, 17, 18, 24, 36]) # Rank 3 2025-07-17T07:36:53.1026095Z 2025-07-17T07:36:53.1026190Z 2025-07-17T07:36:53.1026354Z >>> # Another example with tensors of torch.cfloat type. 2025-07-17T07:36:53.1026471Z >>> input = torch.tensor( 2025-07-17T07:36:53.1026605Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-07-17T07:36:53.1026699Z ... ) + 4 * rank * (1 + 1j) 2025-07-17T07:36:53.1026796Z >>> input 2025-07-17T07:36:53.1026967Z tensor([1+1j, 2+2j, 3+3j, 4+4j]) # Rank 0 2025-07-17T07:36:53.1027131Z tensor([5+5j, 6+6j, 7+7j, 8+8j]) # Rank 1 2025-07-17T07:36:53.1027322Z tensor([9+9j, 10+10j, 11+11j, 12+12j]) # Rank 2 2025-07-17T07:36:53.1027500Z tensor([13+13j, 14+14j, 15+15j, 16+16j]) # Rank 3 2025-07-17T07:36:53.1027650Z >>> output = torch.empty([4], dtype=torch.int64) 2025-07-17T07:36:53.1027770Z >>> dist.all_to_all_single(output, input) 2025-07-17T07:36:53.1027854Z >>> output 2025-07-17T07:36:53.1028032Z tensor([1+1j, 5+5j, 9+9j, 13+13j]) # Rank 0 2025-07-17T07:36:53.1028197Z tensor([2+2j, 6+6j, 10+10j, 14+14j]) # Rank 1 2025-07-17T07:36:53.1028362Z tensor([3+3j, 7+7j, 11+11j, 15+15j]) # Rank 2 2025-07-17T07:36:53.1028542Z tensor([4+4j, 8+8j, 12+12j, 16+16j]) # Rank 3 2025-07-17T07:36:53.1028623Z 2025-07-17T07:36:53.1028878Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1028965Z 2025-07-17T07:36:53.1029061Z warnings.warn(msg) 2025-07-17T07:36:53.1029147Z 2025-07-17T07:36:53.1029349Z --- Parse Warning: 51 / 136 --- 2025-07-17T07:36:53.1030294Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_to_all in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4642. 2025-07-17T07:36:53.1030565Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1030642Z 2025-07-17T07:36:53.1031009Z Scatters list of input tensors to all processes in a group and return gathered list of tensors in output list. 2025-07-17T07:36:53.1031098Z 2025-07-17T07:36:53.1031203Z Complex tensors are supported. 2025-07-17T07:36:53.1031323Z 2025-07-17T07:36:53.1031403Z Args: 2025-07-17T07:36:53.1031621Z output_tensor_list (list[Tensor]): List of tensors to be gathered one 2025-07-17T07:36:53.1031722Z per rank. 2025-07-17T07:36:53.1031948Z input_tensor_list (list[Tensor]): List of tensors to scatter one per rank. 2025-07-17T07:36:53.1032178Z group (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:53.1032314Z the default process group will be used. 2025-07-17T07:36:53.1032511Z async_op (bool, optional): Whether this op should be an async op. 2025-07-17T07:36:53.1032617Z 2025-07-17T07:36:53.1032712Z Returns: 2025-07-17T07:36:53.1032850Z Async work handle, if async_op is set to True. 2025-07-17T07:36:53.1033007Z None, if not async_op or if not part of the group. 2025-07-17T07:36:53.1033086Z 2025-07-17T07:36:53.1033176Z .. warning:: 2025-07-17T07:36:53.1033336Z `all_to_all` is experimental and subject to change. 2025-07-17T07:36:53.1033414Z 2025-07-17T07:36:53.1033497Z Examples: 2025-07-17T07:36:53.1033624Z >>> # xdoctest: +SKIP("Undefined rank") 2025-07-17T07:36:53.1033737Z >>> input = torch.arange(4) + rank * 4 2025-07-17T07:36:53.1033843Z >>> input = list(input.chunk(4)) 2025-07-17T07:36:53.1033992Z >>> input 2025-07-17T07:36:53.1034158Z [tensor([0]), tensor([1]), tensor([2]), tensor([3])] # Rank 0 2025-07-17T07:36:53.1034319Z [tensor([4]), tensor([5]), tensor([6]), tensor([7])] # Rank 1 2025-07-17T07:36:53.1034491Z [tensor([8]), tensor([9]), tensor([10]), tensor([11])] # Rank 2 2025-07-17T07:36:53.1034655Z [tensor([12]), tensor([13]), tensor([14]), tensor([15])] # Rank 3 2025-07-17T07:36:53.1034845Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-07-17T07:36:53.1034955Z >>> dist.all_to_all(output, input) 2025-07-17T07:36:53.1035036Z >>> output 2025-07-17T07:36:53.1035209Z [tensor([0]), tensor([4]), tensor([8]), tensor([12])] # Rank 0 2025-07-17T07:36:53.1035366Z [tensor([1]), tensor([5]), tensor([9]), tensor([13])] # Rank 1 2025-07-17T07:36:53.1035525Z [tensor([2]), tensor([6]), tensor([10]), tensor([14])] # Rank 2 2025-07-17T07:36:53.1035699Z [tensor([3]), tensor([7]), tensor([11]), tensor([15])] # Rank 3 2025-07-17T07:36:53.1035779Z 2025-07-17T07:36:53.1035953Z >>> # Essentially, it is similar to following operation: 2025-07-17T07:36:53.1036053Z >>> scatter_list = input 2025-07-17T07:36:53.1036150Z >>> gather_list = output 2025-07-17T07:36:53.1036269Z >>> for i in range(world_size): 2025-07-17T07:36:53.1036488Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src=i) 2025-07-17T07:36:53.1036565Z 2025-07-17T07:36:53.1036660Z >>> input 2025-07-17T07:36:53.1036807Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-07-17T07:36:53.1036965Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-07-17T07:36:53.1037127Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-07-17T07:36:53.1037279Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-07-17T07:36:53.1037387Z >>> input_splits 2025-07-17T07:36:53.1037507Z [2, 2, 1, 1] # Rank 0 2025-07-17T07:36:53.1037622Z [3, 2, 2, 2] # Rank 1 2025-07-17T07:36:53.1037752Z [2, 1, 1, 1] # Rank 2 2025-07-17T07:36:53.1037866Z [2, 2, 2, 1] # Rank 3 2025-07-17T07:36:53.1037957Z >>> output_splits 2025-07-17T07:36:53.1038080Z [2, 3, 2, 2] # Rank 0 2025-07-17T07:36:53.1038225Z [2, 2, 1, 2] # Rank 1 2025-07-17T07:36:53.1038350Z [1, 2, 1, 2] # Rank 2 2025-07-17T07:36:53.1038463Z [1, 2, 1, 1] # Rank 3 2025-07-17T07:36:53.1038589Z >>> input = list(input.split(input_splits)) 2025-07-17T07:36:53.1038682Z >>> input 2025-07-17T07:36:53.1038882Z [tensor([0, 1]), tensor([2, 3]), tensor([4]), tensor([5])] # Rank 0 2025-07-17T07:36:53.1039081Z [tensor([10, 11, 12]), tensor([13, 14]), tensor([15, 16]), tensor([17, 18])] # Rank 1 2025-07-17T07:36:53.1039316Z [tensor([20, 21]), tensor([22]), tensor([23]), tensor([24])] # Rank 2 2025-07-17T07:36:53.1039511Z [tensor([30, 31]), tensor([32, 33]), tensor([34, 35]), tensor([36])] # Rank 3 2025-07-17T07:36:53.1039612Z >>> output = ... 2025-07-17T07:36:53.1039745Z >>> dist.all_to_all(output, input) 2025-07-17T07:36:53.1039826Z >>> output 2025-07-17T07:36:53.1040031Z [tensor([0, 1]), tensor([10, 11, 12]), tensor([20, 21]), tensor([30, 31])] # Rank 0 2025-07-17T07:36:53.1040226Z [tensor([2, 3]), tensor([13, 14]), tensor([22]), tensor([32, 33])] # Rank 1 2025-07-17T07:36:53.1040483Z [tensor([4]), tensor([15, 16]), tensor([23]), tensor([34, 35])] # Rank 2 2025-07-17T07:36:53.1040679Z [tensor([5]), tensor([17, 18]), tensor([24]), tensor([36])] # Rank 3 2025-07-17T07:36:53.1040756Z 2025-07-17T07:36:53.1040927Z >>> # Another example with tensors of torch.cfloat type. 2025-07-17T07:36:53.1041028Z >>> input = torch.tensor( 2025-07-17T07:36:53.1041162Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-07-17T07:36:53.1041265Z ... ) + 4 * rank * (1 + 1j) 2025-07-17T07:36:53.1041371Z >>> input = list(input.chunk(4)) 2025-07-17T07:36:53.1041455Z >>> input 2025-07-17T07:36:53.1041672Z [tensor([1+1j]), tensor([2+2j]), tensor([3+3j]), tensor([4+4j])] # Rank 0 2025-07-17T07:36:53.1041876Z [tensor([5+5j]), tensor([6+6j]), tensor([7+7j]), tensor([8+8j])] # Rank 1 2025-07-17T07:36:53.1042104Z [tensor([9+9j]), tensor([10+10j]), tensor([11+11j]), tensor([12+12j])] # Rank 2 2025-07-17T07:36:53.1042319Z [tensor([13+13j]), tensor([14+14j]), tensor([15+15j]), tensor([16+16j])] # Rank 3 2025-07-17T07:36:53.1042497Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-07-17T07:36:53.1042618Z >>> dist.all_to_all(output, input) 2025-07-17T07:36:53.1042700Z >>> output 2025-07-17T07:36:53.1042906Z [tensor([1+1j]), tensor([5+5j]), tensor([9+9j]), tensor([13+13j])] # Rank 0 2025-07-17T07:36:53.1043121Z [tensor([2+2j]), tensor([6+6j]), tensor([10+10j]), tensor([14+14j])] # Rank 1 2025-07-17T07:36:53.1043323Z [tensor([3+3j]), tensor([7+7j]), tensor([11+11j]), tensor([15+15j])] # Rank 2 2025-07-17T07:36:53.1043539Z [tensor([4+4j]), tensor([8+8j]), tensor([12+12j]), tensor([16+16j])] # Rank 3 2025-07-17T07:36:53.1043616Z 2025-07-17T07:36:53.1043693Z 2025-07-17T07:36:53.1043960Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1044036Z 2025-07-17T07:36:53.1044131Z warnings.warn(msg) 2025-07-17T07:36:53.1044218Z 2025-07-17T07:36:53.1044413Z --- Parse Warning: 52 / 136 --- 2025-07-17T07:36:53.1045271Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=__doc__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/launch.py line=2. 2025-07-17T07:36:53.1045633Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1045711Z 2025-07-17T07:36:53.1045838Z Module ``torch.distributed.launch``. 2025-07-17T07:36:53.1045988Z 2025-07-17T07:36:53.1046238Z ``torch.distributed.launch`` is a module that spawns up multiple distributed 2025-07-17T07:36:53.1046397Z training processes on each of the training nodes. 2025-07-17T07:36:53.1046475Z 2025-07-17T07:36:53.1046604Z .. warning:: 2025-07-17T07:36:53.1046698Z 2025-07-17T07:36:53.1046949Z This module is going to be deprecated in favor of :ref:`torchrun `. 2025-07-17T07:36:53.1047026Z 2025-07-17T07:36:53.1047279Z The utility can be used for single-node distributed training, in which one or 2025-07-17T07:36:53.1047545Z more processes per node will be spawned. The utility can be used for either 2025-07-17T07:36:53.1047776Z CPU training or GPU training. If the utility is used for GPU training, 2025-07-17T07:36:53.1048018Z each distributed process will be operating on a single GPU. This can achieve 2025-07-17T07:36:53.1048251Z well-improved single-node training performance. It can also be used in 2025-07-17T07:36:53.1048533Z multi-node distributed training, by spawning up multiple processes on each node 2025-07-17T07:36:53.1048805Z for well-improved multi-node distributed training performance as well. 2025-07-17T07:36:53.1049047Z This will especially be beneficial for systems with multiple Infiniband 2025-07-17T07:36:53.1049375Z interfaces that have direct-GPU support, since all of them can be utilized for 2025-07-17T07:36:53.1049490Z aggregated communication bandwidth. 2025-07-17T07:36:53.1049581Z 2025-07-17T07:36:53.1049814Z In both cases of single-node distributed training or multi-node distributed 2025-07-17T07:36:53.1050049Z training, this utility will launch the given number of processes per node 2025-07-17T07:36:53.1050285Z (``--nproc-per-node``). If used for GPU training, this number needs to be less 2025-07-17T07:36:53.1050500Z or equal to the number of GPUs on the current system (``nproc_per_node``), 2025-07-17T07:36:53.1050701Z and each process will be operating on a single GPU from *GPU 0 to 2025-07-17T07:36:53.1071625Z GPU (nproc_per_node - 1)*. 2025-07-17T07:36:53.1071706Z 2025-07-17T07:36:53.1071820Z **How to use this module:** 2025-07-17T07:36:53.1071898Z 2025-07-17T07:36:53.1072065Z 1. Single-Node multi-process distributed training 2025-07-17T07:36:53.1072172Z 2025-07-17T07:36:53.1072257Z :: 2025-07-17T07:36:53.1072333Z 2025-07-17T07:36:53.1072591Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-07-17T07:36:53.1072782Z YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other 2025-07-17T07:36:53.1072910Z arguments of your training script) 2025-07-17T07:36:53.1073001Z 2025-07-17T07:36:53.1073211Z 2. Multi-Node multi-process distributed training: (e.g. two nodes) 2025-07-17T07:36:53.1073303Z 2025-07-17T07:36:53.1073378Z 2025-07-17T07:36:53.1073520Z Node 1: *(IP: 192.168.1.1, and has a free port: 1234)* 2025-07-17T07:36:53.1073615Z 2025-07-17T07:36:53.1073694Z :: 2025-07-17T07:36:53.1073771Z 2025-07-17T07:36:53.1074018Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-07-17T07:36:53.1074173Z --nnodes=2 --node-rank=0 --master-addr="192.168.1.1" 2025-07-17T07:36:53.1074414Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-07-17T07:36:53.1074575Z and all other arguments of your training script) 2025-07-17T07:36:53.1074653Z 2025-07-17T07:36:53.1074735Z Node 2: 2025-07-17T07:36:53.1074825Z 2025-07-17T07:36:53.1074904Z :: 2025-07-17T07:36:53.1075000Z 2025-07-17T07:36:53.1075242Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-07-17T07:36:53.1075395Z --nnodes=2 --node-rank=1 --master-addr="192.168.1.1" 2025-07-17T07:36:53.1075612Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-07-17T07:36:53.1075895Z and all other arguments of your training script) 2025-07-17T07:36:53.1075973Z 2025-07-17T07:36:53.1076146Z 3. To look up what optional arguments this module offers: 2025-07-17T07:36:53.1076225Z 2025-07-17T07:36:53.1076305Z :: 2025-07-17T07:36:53.1076395Z 2025-07-17T07:36:53.1076536Z python -m torch.distributed.launch --help 2025-07-17T07:36:53.1076612Z 2025-07-17T07:36:53.1076707Z 2025-07-17T07:36:53.1076807Z **Important Notices:** 2025-07-17T07:36:53.1076896Z 2025-07-17T07:36:53.1077081Z 1. This utility and multi-process distributed (single-node or 2025-07-17T07:36:53.1077375Z multi-node) GPU training currently only achieves the best performance using 2025-07-17T07:36:53.1077640Z the NCCL distributed backend. Thus NCCL backend is the recommended backend to 2025-07-17T07:36:53.1077737Z use for GPU training. 2025-07-17T07:36:53.1077815Z 2025-07-17T07:36:53.1078042Z 2. In your training program, you must parse the command-line argument: 2025-07-17T07:36:53.1078271Z ``--local-rank=LOCAL_PROCESS_RANK``, which will be provided by this module. 2025-07-17T07:36:53.1078495Z If your training program uses GPUs, you should ensure that your code only 2025-07-17T07:36:53.1078783Z runs on the GPU device of LOCAL_PROCESS_RANK. This can be done by: 2025-07-17T07:36:53.1078863Z 2025-07-17T07:36:53.1078986Z Parsing the local_rank argument 2025-07-17T07:36:53.1079062Z 2025-07-17T07:36:53.1079142Z :: 2025-07-17T07:36:53.1079228Z 2025-07-17T07:36:53.1079323Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1079416Z >>> import argparse 2025-07-17T07:36:53.1079559Z >>> parser = argparse.ArgumentParser() 2025-07-17T07:36:53.1079752Z >>> parser.add_argument("--local-rank", "--local_rank", type=int) 2025-07-17T07:36:53.1079860Z >>> args = parser.parse_args() 2025-07-17T07:36:53.1079949Z 2025-07-17T07:36:53.1080071Z Set your device to local rank using either 2025-07-17T07:36:53.1080197Z 2025-07-17T07:36:53.1080289Z :: 2025-07-17T07:36:53.1080365Z 2025-07-17T07:36:53.1080576Z >>> torch.cuda.set_device(args.local_rank) # before your code runs 2025-07-17T07:36:53.1080652Z 2025-07-17T07:36:53.1080730Z or 2025-07-17T07:36:53.1080820Z 2025-07-17T07:36:53.1080903Z :: 2025-07-17T07:36:53.1080979Z 2025-07-17T07:36:53.1081124Z >>> with torch.cuda.device(args.local_rank): 2025-07-17T07:36:53.1081234Z >>> # your code to run 2025-07-17T07:36:53.1081318Z >>> ... 2025-07-17T07:36:53.1081409Z 2025-07-17T07:36:53.1081514Z .. versionchanged:: 2.0.0 2025-07-17T07:36:53.1081592Z 2025-07-17T07:36:53.1081850Z The launcher will passes the ``--local-rank=`` argument to your script. 2025-07-17T07:36:53.1082085Z From PyTorch 2.0.0 onwards, the dashed ``--local-rank`` is preferred over the 2025-07-17T07:36:53.1082236Z previously used underscored ``--local_rank``. 2025-07-17T07:36:53.1082317Z 2025-07-17T07:36:53.1082556Z For backward compatibility, it may be necessary for users to handle both 2025-07-17T07:36:53.1082834Z cases in their argument parsing code. This means including both ``"--local-rank"`` 2025-07-17T07:36:53.1083051Z and ``"--local_rank"`` in the argument parser. If only ``"--local_rank"`` is 2025-07-17T07:36:53.1083302Z provided, the launcher will trigger an error: "error: unrecognized arguments: 2025-07-17T07:36:53.1083544Z --local-rank=". For training code that only supports PyTorch 2.0.0+, 2025-07-17T07:36:53.1083696Z including ``"--local-rank"`` should be sufficient. 2025-07-17T07:36:53.1083785Z 2025-07-17T07:36:53.1084015Z 3. In your training program, you are supposed to call the following function 2025-07-17T07:36:53.1084250Z at the beginning to start the distributed backend. It is strongly recommended 2025-07-17T07:36:53.1084476Z that ``init_method=env://``. Other init methods (e.g. ``tcp://``) may work, 2025-07-17T07:36:53.1084695Z but ``env://`` is the one that is officially supported by this module. 2025-07-17T07:36:53.1084771Z 2025-07-17T07:36:53.1084863Z :: 2025-07-17T07:36:53.1084939Z 2025-07-17T07:36:53.1085144Z >>> torch.distributed.init_process_group(backend='YOUR BACKEND', 2025-07-17T07:36:53.1085290Z >>> init_method='env://') 2025-07-17T07:36:53.1085447Z 2025-07-17T07:36:53.1085697Z 4. In your training program, you can either use regular distributed functions 2025-07-17T07:36:53.1085935Z or use :func:`torch.nn.parallel.DistributedDataParallel` module. If your 2025-07-17T07:36:53.1086176Z training program uses GPUs for training and you would like to use 2025-07-17T07:36:53.1086377Z :func:`torch.nn.parallel.DistributedDataParallel` module, 2025-07-17T07:36:53.1086482Z here is how to configure it. 2025-07-17T07:36:53.1086558Z 2025-07-17T07:36:53.1086659Z :: 2025-07-17T07:36:53.1086735Z 2025-07-17T07:36:53.1086926Z >>> model = torch.nn.parallel.DistributedDataParallel(model, 2025-07-17T07:36:53.1087072Z >>> device_ids=[args.local_rank], 2025-07-17T07:36:53.1087258Z >>> output_device=args.local_rank) 2025-07-17T07:36:53.1087349Z 2025-07-17T07:36:53.1087588Z Please ensure that ``device_ids`` argument is set to be the only GPU device id 2025-07-17T07:36:53.1087821Z that your code will be operating on. This is generally the local rank of the 2025-07-17T07:36:53.1088072Z process. In other words, the ``device_ids`` needs to be ``[args.local_rank]``, 2025-07-17T07:36:53.1088286Z and ``output_device`` needs to be ``args.local_rank`` in order to use this 2025-07-17T07:36:53.1088369Z utility 2025-07-17T07:36:53.1088459Z 2025-07-17T07:36:53.1088695Z 5. Another way to pass ``local_rank`` to the subprocesses via environment variable 2025-07-17T07:36:53.1088924Z ``LOCAL_RANK``. This behavior is enabled when you launch the script with 2025-07-17T07:36:53.1089140Z ``--use-env=True``. You must adjust the subprocess example above to replace 2025-07-17T07:36:53.1089330Z ``args.local_rank`` with ``os.environ['LOCAL_RANK']``; the launcher 2025-07-17T07:36:53.1089515Z will not pass ``--local-rank`` when you specify this flag. 2025-07-17T07:36:53.1089593Z 2025-07-17T07:36:53.1089678Z .. warning:: 2025-07-17T07:36:53.1089769Z 2025-07-17T07:36:53.1089969Z ``local_rank`` is NOT globally unique: it is only unique per process 2025-07-17T07:36:53.1090156Z on a machine. Thus, don't use it to decide if you should, e.g., 2025-07-17T07:36:53.1090288Z write to a networked filesystem. See 2025-07-17T07:36:53.1090508Z https://github.com/pytorch/pytorch/issues/12042 for an example of 2025-07-17T07:36:53.1090681Z how things can go wrong if you don't do this correctly. 2025-07-17T07:36:53.1090761Z 2025-07-17T07:36:53.1090840Z 2025-07-17T07:36:53.1090928Z 2025-07-17T07:36:53.1091003Z 2025-07-17T07:36:53.1091255Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1091341Z 2025-07-17T07:36:53.1091434Z warnings.warn(msg) 2025-07-17T07:36:53.1091515Z 2025-07-17T07:36:53.1091769Z --- Parse Warning: 53 / 136 --- 2025-07-17T07:36:53.1092829Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=init_from_local_shards in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py line=361. 2025-07-17T07:36:53.1093108Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1093185Z 2025-07-17T07:36:53.1093421Z Creates an :class:`ShardedTensor` from local shards and the global metadata. 2025-07-17T07:36:53.1093617Z Needs to be called on all ranks in an SPMD fashion. 2025-07-17T07:36:53.1093692Z 2025-07-17T07:36:53.1093771Z Args: 2025-07-17T07:36:53.1094054Z local_shards (List[:class `torch.distributed._shard.sharded_tensor.Shard`]): A list 2025-07-17T07:36:53.1094220Z of shards that represent the local shards on this rank. 2025-07-17T07:36:53.1094460Z global_size (int...): a list, tuple, or `torch.Size` of integers defining the 2025-07-17T07:36:53.1094576Z shape of the overall sharded tensor. 2025-07-17T07:36:53.1094652Z 2025-07-17T07:36:53.1094751Z Keyword args: 2025-07-17T07:36:53.1095035Z process_group (ProcessGroup, optional): The process group to work on. If None, 2025-07-17T07:36:53.1095159Z the default process group will be used. 2025-07-17T07:36:53.1095344Z init_rrefs (bool, optional): Whether or not to initialize 2025-07-17T07:36:53.1095550Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-07-17T07:36:53.1095741Z Need to initialize the RPC Framework if specified as ``True``. 2025-07-17T07:36:53.1095848Z Default: ``False``. 2025-07-17T07:36:53.1095926Z 2025-07-17T07:36:53.1096021Z Returns: 2025-07-17T07:36:53.1096169Z A :class:`ShardedTensor` object handle on this rank 2025-07-17T07:36:53.1096298Z 2025-07-17T07:36:53.1096388Z 2025-07-17T07:36:53.1096473Z Examples: 2025-07-17T07:36:53.1096723Z Suppose we want construct a sharded tensor on two ranks, global size = (10, 5), 2025-07-17T07:36:53.1096919Z each shard have a (5, 5) local tensor, we can do it like below: 2025-07-17T07:36:53.1096999Z 2025-07-17T07:36:53.1097084Z on rank 0: 2025-07-17T07:36:53.1097218Z >>> # xdoctest: +SKIP("not distributed") 2025-07-17T07:36:53.1097341Z >>> local_shard_metadata = ShardMetadata( 2025-07-17T07:36:53.1097443Z >>> shard_offsets=[0, 0], 2025-07-17T07:36:53.1097554Z >>> shard_lengths=[5, 5], 2025-07-17T07:36:53.1097662Z >>> placement="rank:0/cuda:0" 2025-07-17T07:36:53.1097757Z >>> ) 2025-07-17T07:36:53.1097946Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-07-17T07:36:53.1098139Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-07-17T07:36:53.1098234Z 2025-07-17T07:36:53.1098317Z on rank 1: 2025-07-17T07:36:53.1098436Z >>> # xdoctest: +SKIP("not distributed") 2025-07-17T07:36:53.1098564Z >>> local_shard_metadata = ShardMetadata( 2025-07-17T07:36:53.1098663Z >>> shard_offsets=[5, 0], 2025-07-17T07:36:53.1098766Z >>> shard_lengths=[5, 5], 2025-07-17T07:36:53.1098882Z >>> placement="rank:1/cuda:1" 2025-07-17T07:36:53.1098961Z >>> ) 2025-07-17T07:36:53.1099160Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-07-17T07:36:53.1099350Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-07-17T07:36:53.1099429Z 2025-07-17T07:36:53.1099699Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1099774Z 2025-07-17T07:36:53.1099868Z warnings.warn(msg) 2025-07-17T07:36:53.1099959Z 2025-07-17T07:36:53.1100147Z --- Parse Warning: 54 / 136 --- 2025-07-17T07:36:53.1101257Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardedTensor._init_from_local_tensor in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=835. 2025-07-17T07:36:53.1101530Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1101608Z 2025-07-17T07:36:53.1101880Z Initialize a ShardedTensor given only one local tensor, global sharded tensor 2025-07-17T07:36:53.1101991Z size and sharding spec on each rank. 2025-07-17T07:36:53.1102071Z 2025-07-17T07:36:53.1102208Z Args: 2025-07-17T07:36:53.1102427Z local_tensor (Tensor): Single tensor of local shard stored in each rank. 2025-07-17T07:36:53.1102686Z sharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): 2025-07-17T07:36:53.1102865Z The specification describing how to shard the Tensor. 2025-07-17T07:36:53.1103034Z global_size (Sequence[int]): Size of the sharded tensor. 2025-07-17T07:36:53.1103297Z process_group (ProcessGroup, optional): The process group to aggregate on. 2025-07-17T07:36:53.1103390Z Default: None 2025-07-17T07:36:53.1103555Z init_rrefs (bool, optional): Whether or not to initialize 2025-07-17T07:36:53.1103800Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-07-17T07:36:53.1103989Z Need to initialize the RPC Framework if specified as ``True``. 2025-07-17T07:36:53.1104083Z Default: ``False``. 2025-07-17T07:36:53.1104173Z 2025-07-17T07:36:53.1104258Z Returns: 2025-07-17T07:36:53.1104497Z A :class:`ShardedTensor` sharded based on the given sharding_spec with local 2025-07-17T07:36:53.1104623Z tensor stored in the current rank. 2025-07-17T07:36:53.1104700Z 2025-07-17T07:36:53.1104797Z Examples: 2025-07-17T07:36:53.1104891Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1105073Z >>> # All tensors below are of torch.int64 type. 2025-07-17T07:36:53.1105206Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:53.1105378Z >>> tensor = torch.arange(2, dtype=torch.int64) + 1 + 2 * rank 2025-07-17T07:36:53.1105578Z >>> local_tensor = torch.unsqueeze(torch.cat([tensor, tensor + 2])) 2025-07-17T07:36:53.1105682Z >>> local_tensor 2025-07-17T07:36:53.1105777Z tensor([[1, 2, 3, 4]]) # Rank 0 2025-07-17T07:36:53.1105875Z tensor([[3, 4, 5, 6]]) # Rank 1 2025-07-17T07:36:53.1105992Z >>> sharding_dim = 0 2025-07-17T07:36:53.1106112Z >>> sharding_spec = ChunkShardingSpec( 2025-07-17T07:36:53.1106279Z dim=sharding_dim, 2025-07-17T07:36:53.1106371Z placements=[ 2025-07-17T07:36:53.1106463Z "rank:0/cuda:0", 2025-07-17T07:36:53.1106567Z "rank:1/cuda:1", 2025-07-17T07:36:53.1106649Z ], 2025-07-17T07:36:53.1106729Z ) 2025-07-17T07:36:53.1106873Z >>> st = ShardedTensor._init_from_local_tensor( 2025-07-17T07:36:53.1106993Z ... local_tensor, sharding_spec, [2, 4] 2025-07-17T07:36:53.1107072Z ... ) 2025-07-17T07:36:53.1107166Z >>> st 2025-07-17T07:36:53.1107256Z ShardedTensor( 2025-07-17T07:36:53.1107358Z ShardedTensorMetadata( 2025-07-17T07:36:53.1107463Z shards_metadata=[ 2025-07-17T07:36:53.1107727Z ShardMetadata(shard_offsets=[0, 0], shard_sizes=[1, 4], placement=rank:0/cuda:0), 2025-07-17T07:36:53.1107996Z ShardMetadata(shard_offsets=[1, 0], shard_sizes=[1, 4], placement=rank:1/cuda:1), 2025-07-17T07:36:53.1108075Z ], 2025-07-17T07:36:53.1108177Z size=torch.Size([2, 4]) 2025-07-17T07:36:53.1108268Z ) 2025-07-17T07:36:53.1108359Z >>> st.local_tensor() 2025-07-17T07:36:53.1108451Z tensor([1, 2, 3, 4]) # Rank 0 2025-07-17T07:36:53.1108562Z tensor([3, 4, 5, 6]) # Rank 1 2025-07-17T07:36:53.1108635Z 2025-07-17T07:36:53.1108904Z Warning: This API is experimental and subject to change. It lacks of a fully across 2025-07-17T07:36:53.1109154Z rank validations, and we only validate the local shard on the current rank. 2025-07-17T07:36:53.1109366Z We fully rely on the user to ensure local tensor is sharded based on the 2025-07-17T07:36:53.1109472Z sharding spec. 2025-07-17T07:36:53.1109548Z 2025-07-17T07:36:53.1109801Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1109891Z 2025-07-17T07:36:53.1110012Z warnings.warn(msg) 2025-07-17T07:36:53.1110087Z 2025-07-17T07:36:53.1110290Z --- Parse Warning: 55 / 136 --- 2025-07-17T07:36:53.1111349Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardedTensor.reshard in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=1076. 2025-07-17T07:36:53.1111623Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1111700Z 2025-07-17T07:36:53.1111951Z Reshard a sharded tensor given the ``resharding_spec``. For now, we only support 2025-07-17T07:36:53.1112085Z single local shard. 2025-07-17T07:36:53.1112162Z 2025-07-17T07:36:53.1112380Z If ``resharding_spec`` is same as the original one, this becomes a no-op. 2025-07-17T07:36:53.1112633Z If only ``resharding_spec`` shares the same sharding dim with the original one, 2025-07-17T07:36:53.1112742Z we swap local shards directly. 2025-07-17T07:36:53.1112996Z For more generic cases, we merge different shards across different ranks and split 2025-07-17T07:36:53.1113256Z the local shards based on the ``resharding_spec`` via `all_to_all` collective API. 2025-07-17T07:36:53.1113331Z 2025-07-17T07:36:53.1113425Z Args: 2025-07-17T07:36:53.1113762Z resharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): The 2025-07-17T07:36:53.1113926Z specification describing how the tensor is sharded. 2025-07-17T07:36:53.1114018Z 2025-07-17T07:36:53.1114099Z Returns: 2025-07-17T07:36:53.1114303Z A :class:`ShardedTensor` object whose local shards are resharded. 2025-07-17T07:36:53.1114393Z 2025-07-17T07:36:53.1114482Z Examples: 2025-07-17T07:36:53.1114576Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1114698Z >>> # We have 2 process groups, 2 ranks. 2025-07-17T07:36:53.1114869Z >>> tensor = torch.arange(4, dtype=torch.int64) + 1 + 2 * rank 2025-07-17T07:36:53.1114991Z >>> tensor = torch.stack([tensor, tensor]) 2025-07-17T07:36:53.1115082Z >>> tensor 2025-07-17T07:36:53.1115196Z tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) # Rank 0 2025-07-17T07:36:53.1115316Z tensor([[3, 4, 5, 6], [3, 4, 5, 6]]) # Rank 1 2025-07-17T07:36:53.1115428Z tensor([[5, 6, 7, 8], [5, 6, 7, 8]]) # Rank 2 2025-07-17T07:36:53.1115545Z tensor([[7, 8, 9, 10], [7, 8, 9, 10]]) # Rank 3 2025-07-17T07:36:53.1115649Z >>> sharding_dim = 0 2025-07-17T07:36:53.1115757Z >>> spec = ChunkShardingSpec( 2025-07-17T07:36:53.1115851Z dim=sharding_dim, 2025-07-17T07:36:53.1115953Z placements=[ 2025-07-17T07:36:53.1116043Z "rank:0/cuda:0", 2025-07-17T07:36:53.1116131Z "rank:1/cuda:1", 2025-07-17T07:36:53.1116234Z "rank:2/cuda:2", 2025-07-17T07:36:53.1116333Z "rank:3/cuda:3", 2025-07-17T07:36:53.1116424Z ], 2025-07-17T07:36:53.1116501Z ) 2025-07-17T07:36:53.1116602Z >>> current_offsets = [0] * 2 2025-07-17T07:36:53.1116716Z >>> current_offsets[0] = rank * 2 2025-07-17T07:36:53.1116826Z >>> shard_metadata = ShardMetadata( 2025-07-17T07:36:53.1116974Z shard_offsets=copy.deepcopy(current_offsets), 2025-07-17T07:36:53.1117092Z shard_sizes=tensor.size(), 2025-07-17T07:36:53.1117212Z placement=spec.placements[rank], 2025-07-17T07:36:53.1117291Z ) 2025-07-17T07:36:53.1117394Z >>> local_shards = [ 2025-07-17T07:36:53.1117478Z Shard( 2025-07-17T07:36:53.1117567Z tensor=tensor, 2025-07-17T07:36:53.1117682Z metadata=shard_metadata, 2025-07-17T07:36:53.1117757Z ) 2025-07-17T07:36:53.1117843Z ] 2025-07-17T07:36:53.1118065Z >>> st = ShardedTensor._init_from_local_shards(local_shards, tensor.size()) 2025-07-17T07:36:53.1118184Z >>> sharding_dim = 1 2025-07-17T07:36:53.1118314Z >>> resharding_spec = ChunkShardingSpec( 2025-07-17T07:36:53.1118406Z dim=sharding_dim, 2025-07-17T07:36:53.1118495Z placements=[ 2025-07-17T07:36:53.1118599Z "rank:0/cuda:0", 2025-07-17T07:36:53.1118694Z "rank:1/cuda:1", 2025-07-17T07:36:53.1118781Z "rank:2/cuda:2", 2025-07-17T07:36:53.1118882Z "rank:3/cuda:3", 2025-07-17T07:36:53.1118959Z ], 2025-07-17T07:36:53.1119035Z ) 2025-07-17T07:36:53.1119155Z >>> st.reshard(resharding_spec) 2025-07-17T07:36:53.1119293Z >>> tensor = st.local_shards()[0].tensor 2025-07-17T07:36:53.1119383Z >>> tensor 2025-07-17T07:36:53.1119520Z tensor([[1], [1], [3], [3], [5], [5], [7], [7]]) # Rank 0 2025-07-17T07:36:53.1119649Z tensor([[2], [2], [4], [4], [6], [6], [8], [8]]) # Rank 1 2025-07-17T07:36:53.1119789Z tensor([[3], [3], [5], [5], [7], [7], [9], [9]]) # Rank 2 2025-07-17T07:36:53.1119929Z tensor([[4], [4], [6], [6], [8], [8], [10], [10]]) # Rank 3 2025-07-17T07:36:53.1120003Z 2025-07-17T07:36:53.1120263Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1120339Z 2025-07-17T07:36:53.1120479Z warnings.warn(msg) 2025-07-17T07:36:53.1120569Z 2025-07-17T07:36:53.1120762Z --- Parse Warning: 56 / 136 --- 2025-07-17T07:36:53.1121771Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardingPlan in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharding_plan/api.py line=12. 2025-07-17T07:36:53.1122036Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1122112Z 2025-07-17T07:36:53.1122340Z Representation of a sharding plan, describes how to shard a module 2025-07-17T07:36:53.1122610Z across hosts. `plan` is used to shard module parameters according to the spec provided, 2025-07-17T07:36:53.1122912Z `output_plan` and `return_local_tensor` are optional, they are used to specify the output 2025-07-17T07:36:53.1123161Z layout of a module with a spec, and when to convert back to data parallel fashion. 2025-07-17T07:36:53.1123237Z 2025-07-17T07:36:53.1123327Z Args: 2025-07-17T07:36:53.1123594Z plan (Dict[str, Union[:class:`torch.distributed._shard.sharding_spec.ShardingSpec`, 2025-07-17T07:36:53.1123758Z :class:`torch.distributed._shard.sharder.Sharder`]): 2025-07-17T07:36:53.1124039Z a dict describes how to shard a module, there're currently two ways to shard a module: 2025-07-17T07:36:53.1124287Z 1. directly shard a module parameter by a `ShardingSpec`, keyed by the name of 2025-07-17T07:36:53.1124416Z a parameter to a `ShardingSpec`. 2025-07-17T07:36:53.1124666Z 2. shard a submodule by applying a `Sharder` on it, keyed by the name of a module 2025-07-17T07:36:53.1124769Z to a `Sharder` object. 2025-07-17T07:36:53.1125106Z output_plan (Dict[str, :class:`torch.distributed._shard.sharding_spec.ShardingSpec`), optional): 2025-07-17T07:36:53.1125441Z a dict specifies the layout of a module's output which produces a ShardedTensor, 2025-07-17T07:36:53.1125674Z keyed by the name of module to ShardingSpec("" in key means the root module). 2025-07-17T07:36:53.1125779Z Default: `None` 2025-07-17T07:36:53.1126029Z return_local_tensor (List[str], optional): a list of string, each element enables 2025-07-17T07:36:53.1126278Z a module's sharded output to be returned as a Tensor from its local shards to 2025-07-17T07:36:53.1126524Z ensure further processing in a data parallel fashion. ("" in list means the 2025-07-17T07:36:53.1126613Z root module). 2025-07-17T07:36:53.1126750Z Default: None 2025-07-17T07:36:53.1126832Z Example: 2025-07-17T07:36:53.1127109Z Suppose we want to shard a module with two linear layers and then run it with DDP, we also 2025-07-17T07:36:53.1127400Z want to convert the output of the second linear layer back to DDP, we can do it as follows: 2025-07-17T07:36:53.1127476Z 2025-07-17T07:36:53.1127645Z >>> # xdoctest: +REQUIRES(module:torch._C._distributed_c10d) 2025-07-17T07:36:53.1127760Z >>> class MyModule(nn.Module): 2025-07-17T07:36:53.1127867Z >>> def __init__(self) -> None: 2025-07-17T07:36:53.1127972Z >>> super().__init__() 2025-07-17T07:36:53.1128100Z >>> self.fc1 = nn.Linear() 2025-07-17T07:36:53.1128198Z >>> self.gelu = nn.GELU() 2025-07-17T07:36:53.1128307Z >>> self.fc2 = nn.Linear() 2025-07-17T07:36:53.1128407Z >>> self.relu = nn.Linear() 2025-07-17T07:36:53.1128487Z >>> 2025-07-17T07:36:53.1128597Z >>> def forward(self, input): 2025-07-17T07:36:53.1128764Z >>> return self.relu(self.fc2(self.gelu(self.fc1(input)))) 2025-07-17T07:36:53.1128853Z 2025-07-17T07:36:53.1128928Z 2025-07-17T07:36:53.1129051Z >>> # xdoctest: +SKIP("Undefined spec1, spec2) 2025-07-17T07:36:53.1129228Z >>> sharding_plan = ShardingPlan( 2025-07-17T07:36:53.1129309Z >>> plan={ 2025-07-17T07:36:53.1129400Z >>> "fc1.weight": spec1, 2025-07-17T07:36:53.1129511Z >>> "fc2.weight": spec2 2025-07-17T07:36:53.1129586Z >>> }, 2025-07-17T07:36:53.1129684Z >>> output_plan={ 2025-07-17T07:36:53.1129780Z >>> "fc2": output_spec 2025-07-17T07:36:53.1129855Z >>> }, 2025-07-17T07:36:53.1129966Z >>> return_local_tensor=["fc2"] 2025-07-17T07:36:53.1130081Z >>> ) 2025-07-17T07:36:53.1130158Z 2025-07-17T07:36:53.1130417Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1130490Z 2025-07-17T07:36:53.1130582Z warnings.warn(msg) 2025-07-17T07:36:53.1130667Z 2025-07-17T07:36:53.1130857Z --- Parse Warning: 57 / 136 --- 2025-07-17T07:36:53.1131982Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=post_localSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/post_localSGD_hook.py line=72. 2025-07-17T07:36:53.1132250Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1132324Z 2025-07-17T07:36:53.1132443Z Run post-localSGD algorithm. 2025-07-17T07:36:53.1132516Z 2025-07-17T07:36:53.1132749Z This DDP communication hook is used for running post-localSGD algorithm, 2025-07-17T07:36:53.1132914Z by combining with a model averaging component (e.g., 2025-07-17T07:36:53.1133240Z :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`) 2025-07-17T07:36:53.1133350Z that runs after the optimizer step. 2025-07-17T07:36:53.1133439Z 2025-07-17T07:36:53.1133516Z Args: 2025-07-17T07:36:53.1133751Z state (PostLocalSGDState): State information to run post-localSGD. 2025-07-17T07:36:53.1134023Z Users mainly need to tune ``start_localSGD_iter`` to determine when to start local SGD. 2025-07-17T07:36:53.1134441Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-07-17T07:36:53.1134697Z Note that since DDP comm hook only supports single process single device mode, 2025-07-17T07:36:53.1134840Z only exactly one tensor is stored in this bucket. 2025-07-17T07:36:53.1134916Z 2025-07-17T07:36:53.1135004Z Returns: 2025-07-17T07:36:53.1135242Z Future handler of the communication, which updates the gradients in place. 2025-07-17T07:36:53.1135320Z 2025-07-17T07:36:53.1135443Z Example:: 2025-07-17T07:36:53.1135533Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1135794Z >>> state = PostLocalSGDState(process_group=process_group, subgroup=subgroup, 2025-07-17T07:36:53.1135904Z start_localSGD_iter=10) 2025-07-17T07:36:53.1136071Z >>> ddp_model.register_comm_hook(state, post_localSGD_hook) 2025-07-17T07:36:53.1136408Z >>> # Also need to establish a model averaging module and run model averaging after ``optimizer.step()``. 2025-07-17T07:36:53.1136750Z >>> # Please refer to the examples in ``torch.distributed.algorithms.model_averaging.averagers`` module. 2025-07-17T07:36:53.1136854Z 2025-07-17T07:36:53.1137112Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1137184Z 2025-07-17T07:36:53.1137289Z warnings.warn(msg) 2025-07-17T07:36:53.1137358Z 2025-07-17T07:36:53.1137534Z --- Parse Warning: 58 / 136 --- 2025-07-17T07:36:53.1138628Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=powerSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py line=342. 2025-07-17T07:36:53.1138933Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1139008Z 2025-07-17T07:36:53.1139119Z Implement PowerSGD algorithm. 2025-07-17T07:36:53.1139193Z 2025-07-17T07:36:53.1139427Z This DDP communication hook implements PowerSGD gradient compression 2025-07-17T07:36:53.1139661Z algorithm described in the `paper `_. 2025-07-17T07:36:53.1139896Z Once gradient tensors are aggregated across all workers, this hook applies 2025-07-17T07:36:53.1140005Z compression as follows: 2025-07-17T07:36:53.1140075Z 2025-07-17T07:36:53.1140512Z 1. Views the input flattened 1D gradient tensor as a list of per-parameter tensors, and divides all the tensors into two groups: 2025-07-17T07:36:53.1140597Z 2025-07-17T07:36:53.1141015Z 1.1 The tensors that should be compressed before allreduce, because the compression can give enough saving in bandwidth. 2025-07-17T07:36:53.1141088Z 2025-07-17T07:36:53.1141506Z 1.2 Rest of the tensors will be directly allreduced without compression, including all the vector tensors (for biases). 2025-07-17T07:36:53.1141578Z 2025-07-17T07:36:53.1141695Z 2. Handles uncompressed tensors: 2025-07-17T07:36:53.1141765Z 2025-07-17T07:36:53.1142276Z 2.1. Allocate contiguous memory for those uncompressed tensors, and allreduces all the uncompressed tensors as a batch, without compression; 2025-07-17T07:36:53.1142363Z 2025-07-17T07:36:53.1142699Z 2.2. Copies the individual uncompressed tensors from the contiguous memory back to the input tensor. 2025-07-17T07:36:53.1142770Z 2025-07-17T07:36:53.1143008Z 3. Handles the tensors that should be compressed by PowerSGD compression: 2025-07-17T07:36:53.1143081Z 2025-07-17T07:36:53.1143323Z 3.1. For each tensor M, creates two low-rank tensors P and Q for decomposing M, 2025-07-17T07:36:53.1143626Z such that M = PQ^T, where Q is initialized from a standard normal distribution and orthogonalized; 2025-07-17T07:36:53.1143698Z 2025-07-17T07:36:53.1143852Z 3.2. Computes each P in Ps, which is equal to MQ; 2025-07-17T07:36:53.1143922Z 2025-07-17T07:36:53.1144022Z 3.3. Allreduces Ps as a batch; 2025-07-17T07:36:53.1144107Z 2025-07-17T07:36:53.1144216Z 3.4. Orthogonalizes each P in Ps; 2025-07-17T07:36:53.1144291Z 2025-07-17T07:36:53.1144491Z 3.5. Computes each Q in Qs, which is approximately equal to M^TP; 2025-07-17T07:36:53.1144561Z 2025-07-17T07:36:53.1144661Z 3.6. Allreduces Qs as a batch; 2025-07-17T07:36:53.1144743Z 2025-07-17T07:36:53.1145032Z 3.7. Computes each M among all the compressed tensors, which is approximately equal to PQ^T. 2025-07-17T07:36:53.1145140Z 2025-07-17T07:36:53.1145544Z Note that this communication hook enforces vanilla allreduce for the first ``state.start_powerSGD_iter`` iterations. 2025-07-17T07:36:53.1145818Z This not only gives the user more control over the tradeoff between speedup and accuracy, 2025-07-17T07:36:53.1146262Z but also helps abstract away some complexity of the internal optimization of DDP for future communication hook developers. 2025-07-17T07:36:53.1146333Z 2025-07-17T07:36:53.1146410Z Args: 2025-07-17T07:36:53.1146855Z state (PowerSGDState): State information to configure the compression rate and support error feedback, warm start, etc. 2025-07-17T07:36:53.1147234Z To tune the compression configs, mainly need to tune ``matrix_approximation_rank``, ``start_powerSGD_iter`` 2025-07-17T07:36:53.1147348Z and ``min_compression_rate``. 2025-07-17T07:36:53.1147760Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-07-17T07:36:53.1148003Z Note that since DDP comm hook only supports single process single device mode, 2025-07-17T07:36:53.1148161Z only exactly one tensor is stored in this bucket. 2025-07-17T07:36:53.1148231Z 2025-07-17T07:36:53.1148355Z Returns: 2025-07-17T07:36:53.1148609Z Future handler of the communication, which updates the gradients in place. 2025-07-17T07:36:53.1148683Z 2025-07-17T07:36:53.1148777Z Example:: 2025-07-17T07:36:53.1148866Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1149132Z >>> state = PowerSGDState(process_group=process_group, matrix_approximation_rank=1, 2025-07-17T07:36:53.1149296Z start_powerSGD_iter=10, min_compression_rate=0.5) 2025-07-17T07:36:53.1149447Z >>> ddp_model.register_comm_hook(state, powerSGD_hook) 2025-07-17T07:36:53.1149520Z 2025-07-17T07:36:53.1149776Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1149850Z 2025-07-17T07:36:53.1149940Z warnings.warn(msg) 2025-07-17T07:36:53.1150019Z 2025-07-17T07:36:53.1150197Z --- Parse Warning: 59 / 136 --- 2025-07-17T07:36:53.1151337Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PeriodicModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/averagers.py line=38. 2025-07-17T07:36:53.1151593Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1151668Z 2025-07-17T07:36:53.1151862Z Averages parameters periodically after the warm-up stage. 2025-07-17T07:36:53.1151934Z 2025-07-17T07:36:53.1152185Z This can be used for running `post-local SGD `_, 2025-07-17T07:36:53.1152380Z by running :class:`~torch.nn.DistributedDataParallel` (DDP) 2025-07-17T07:36:53.1152614Z using the subgroups created by :meth:`~torch.distributed.new_subgroups`. 2025-07-17T07:36:53.1152698Z 2025-07-17T07:36:53.1152770Z Args: 2025-07-17T07:36:53.1152930Z period (int): The number of steps per model averaging. 2025-07-17T07:36:53.1153208Z Usually the period should be greater than ``1`` to reduce the communication cost. 2025-07-17T07:36:53.1153330Z Otherwise, only DDP needs to be used. 2025-07-17T07:36:53.1153530Z warmup_steps (int): The number of warm-up steps. During this stage, 2025-07-17T07:36:53.1153652Z model averaging is skipped. 2025-07-17T07:36:53.1153836Z process_group: The process group to be used for all-reduce. 2025-07-17T07:36:53.1153985Z If ``None``, the default process group, which 2025-07-17T07:36:53.1154165Z is created by :func:`torch.distributed.init_process_group`, 2025-07-17T07:36:53.1154308Z will be used. (default: ``None``) 2025-07-17T07:36:53.1154394Z 2025-07-17T07:36:53.1154474Z Example:: 2025-07-17T07:36:53.1154547Z 2025-07-17T07:36:53.1154678Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.1154763Z >>> import torch 2025-07-17T07:36:53.1154880Z >>> import torch.distributed as dist 2025-07-17T07:36:53.1155199Z >>> import torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook as post_localSGD 2025-07-17T07:36:53.1155466Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-07-17T07:36:53.1155601Z >>> import torch.nn as nn 2025-07-17T07:36:53.1155674Z >>> 2025-07-17T07:36:53.1155841Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-07-17T07:36:53.1155956Z >>> torch.cuda.set_device(rank) 2025-07-17T07:36:53.1156079Z >>> module = nn.Linear(1, 1, bias=False).cuda() 2025-07-17T07:36:53.1156229Z >>> model = nn.parallel.DistributedDataParallel( 2025-07-17T07:36:53.1156371Z >>> module, device_ids=[rank], output_device=rank 2025-07-17T07:36:53.1156444Z >>> ) 2025-07-17T07:36:53.1156585Z >>> # Register a post-localSGD communication hook. 2025-07-17T07:36:53.1156926Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-07-17T07:36:53.1157084Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-07-17T07:36:53.1157169Z >>> 2025-07-17T07:36:53.1157426Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-07-17T07:36:53.1157577Z >>> # After 100 steps, run model averaging every 4 steps. 2025-07-17T07:36:53.1157897Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-07-17T07:36:53.1158137Z >>> averager = averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-07-17T07:36:53.1158237Z >>> for step in range(0, 200): 2025-07-17T07:36:53.1158343Z >>> optimizer.zero_grad() 2025-07-17T07:36:53.1158446Z >>> loss = loss_fn(output, labels) 2025-07-17T07:36:53.1158554Z >>> loss.backward() 2025-07-17T07:36:53.1158646Z >>> optimizer.step() 2025-07-17T07:36:53.1158834Z >>> # Will average model parameters globally every 4 steps. Thus, 2025-07-17T07:36:53.1159039Z >>> # inter-node communication only occurs every 4 iterations after 2025-07-17T07:36:53.1159158Z >>> # the initial ``warmup_steps`` period. 2025-07-17T07:36:53.1159317Z >>> averager.average_parameters(model.parameters()) 2025-07-17T07:36:53.1159401Z 2025-07-17T07:36:53.1159645Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1159718Z 2025-07-17T07:36:53.1159816Z warnings.warn(msg) 2025-07-17T07:36:53.1159889Z 2025-07-17T07:36:53.1160078Z --- Parse Warning: 60 / 136 --- 2025-07-17T07:36:53.1161313Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=HierarchicalModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/hierarchical_model_averager.py line=19. 2025-07-17T07:36:53.1161574Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1161661Z 2025-07-17T07:36:53.1161994Z Runs hierarchical model averaging (`hierarchical SGD `_). 2025-07-17T07:36:53.1162073Z 2025-07-17T07:36:53.1162390Z Process groups of different sizes are organized in a hierarchy, and they average parameters 2025-07-17T07:36:53.1162590Z by using different periods concurrently after the warm-up stage. 2025-07-17T07:36:53.1163010Z This is an extension of :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager` 2025-07-17T07:36:53.1163373Z that supports `post-local SGD `_, which essentially only supports 2025-07-17T07:36:53.1163677Z a two-level hierarchy: the intra-machine level and the global level, where the intra-machine 2025-07-17T07:36:53.1164047Z level is usually embedded in :meth:`~torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook`. 2025-07-17T07:36:53.1164348Z Similarly, the process groups within this class do not have such an intra-machine process 2025-07-17T07:36:53.1164634Z subgroup, which should be embedded by the post-local SGD communication hook instead. 2025-07-17T07:36:53.1164740Z 2025-07-17T07:36:53.1164821Z Args: 2025-07-17T07:36:53.1165095Z period_group_size_dict: An ordered dict mapping keys of model averaging period to 2025-07-17T07:36:53.1165292Z process group size, used for initializing process groups of 2025-07-17T07:36:53.1165592Z different sizes in a hierarchy to average parameters concurrently. 2025-07-17T07:36:53.1165822Z Particularly, at each iteration, there will be at most a single 2025-07-17T07:36:53.1166050Z process group that runs averaging -- the period of such group should 2025-07-17T07:36:53.1166342Z have the largest period which the current step can be divided by. 2025-07-17T07:36:53.1166509Z For example, if the dict has three keys: 2, 4, and 8, 2025-07-17T07:36:53.1166712Z then this means totally three process groups will be created to 2025-07-17T07:36:53.1166937Z average parameters every 2, 4, and 8 iterations, respectively. 2025-07-17T07:36:53.1167126Z At the 4th iteration, only the second process group will run 2025-07-17T07:36:53.1167315Z averaging, because the first process group should be a 2025-07-17T07:36:53.1167536Z subset of the second process group, and no need to execute the first 2025-07-17T07:36:53.1167659Z process group redundantly. 2025-07-17T07:36:53.1167892Z On the other hand, the third process group can only be triggered 2025-07-17T07:36:53.1168115Z every 8 iterations, so it will not be triggered at the 4th iteration. 2025-07-17T07:36:53.1168417Z warmup_steps (int): The number of warm-up steps. During this stage, model averaging is skipped. 2025-07-17T07:36:53.1168880Z process_group (ProcessGroup, optional): The overall process group containing all the processes that runs model averaging. 2025-07-17T07:36:53.1169049Z If ``None``, the default process group, which is created 2025-07-17T07:36:53.1169271Z by :func:`torch.distributed.init_process_group`, will be used. 2025-07-17T07:36:53.1169395Z (default: ``None``) 2025-07-17T07:36:53.1169475Z 2025-07-17T07:36:53.1169579Z Example:: 2025-07-17T07:36:53.1169697Z >>> # xdoctest: +SKIP('undefined rank') 2025-07-17T07:36:53.1169820Z >>> from collections import OrderedDict 2025-07-17T07:36:53.1169925Z >>> import torch 2025-07-17T07:36:53.1170234Z >>> import torch.distributed as dist 2025-07-17T07:36:53.1170524Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-07-17T07:36:53.1170629Z >>> PostLocalSGDState, 2025-07-17T07:36:53.1170734Z >>> post_localSGD_hook, 2025-07-17T07:36:53.1170828Z >>> ) 2025-07-17T07:36:53.1171206Z >>> import torch.distributed.algorithms.model_averaging.hierarchical_model_averager as hierarchicalSGD 2025-07-17T07:36:53.1171307Z >>> import torch.nn as nn 2025-07-17T07:36:53.1171401Z >>> 2025-07-17T07:36:53.1171652Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-07-17T07:36:53.1171761Z >>> torch.cuda.set_device(rank) 2025-07-17T07:36:53.1171904Z >>> module = nn.Linear(1, 1, bias=False).to(rank) 2025-07-17T07:36:53.1172056Z >>> model = nn.parallel.DistributedDataParallel( 2025-07-17T07:36:53.1172211Z >>> module, device_ids=[rank], output_device=rank 2025-07-17T07:36:53.1172292Z >>> ) 2025-07-17T07:36:53.1172433Z >>> # Register a post-localSGD communication hook. 2025-07-17T07:36:53.1172720Z >>> # Assume that each machine has 4 GPUs, then each intra-machine subgroup has a size of 4. 2025-07-17T07:36:53.1172877Z >>> subgroup, _ = dist.new_subgroups() 2025-07-17T07:36:53.1173188Z >>> state = PostLocalSGDState(process_group=None, subgroup=subgroup, start_localSGD_iter=100) 2025-07-17T07:36:53.1173358Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-07-17T07:36:53.1173436Z >>> 2025-07-17T07:36:53.1173725Z >>> # Average parameters among each group of 8 processes every 4 iterations, and among all 2025-07-17T07:36:53.1173843Z >>> # the 16 processes every 16 iterations. 2025-07-17T07:36:53.1174026Z >>> averager = hierarchicalSGD.HierarchicalModelAverager( 2025-07-17T07:36:53.1174345Z >>> period_group_size_dict=OrderedDict([(4, 8), (16, 16)]), warmup_steps=100) 2025-07-17T07:36:53.1174656Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-07-17T07:36:53.1174917Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-07-17T07:36:53.1175079Z >>> # After 100 steps, run model averaging at two levels. 2025-07-17T07:36:53.1175180Z >>> for step in range(0, 200): 2025-07-17T07:36:53.1175295Z >>> optimizer.zero_grad() 2025-07-17T07:36:53.1175405Z >>> loss = loss_fn(output, labels) 2025-07-17T07:36:53.1175502Z >>> loss.backward() 2025-07-17T07:36:53.1175614Z >>> optimizer.step() 2025-07-17T07:36:53.1175767Z >>> # Average parameters after ``optimizer.step()``. 2025-07-17T07:36:53.1176051Z >>> # Thus, the inter-node communication only occurs periodically after ``warmup_steps``. 2025-07-17T07:36:53.1176225Z >>> averager.average_parameters(model.parameters()) 2025-07-17T07:36:53.1176304Z 2025-07-17T07:36:53.1176406Z .. warning :: 2025-07-17T07:36:53.1176655Z The last group size in the dict must be the size of the provided ``process_group``, 2025-07-17T07:36:53.1176887Z which indicates model averaging at the highest level of the hierarchy. 2025-07-17T07:36:53.1177200Z If ``process_group`` is not provided, then the last group size should be equal to the world size. 2025-07-17T07:36:53.1177277Z 2025-07-17T07:36:53.1177363Z .. warning :: 2025-07-17T07:36:53.1177609Z `HierarchicalModelAverager` is experimental and subject to change. 2025-07-17T07:36:53.1177688Z 2025-07-17T07:36:53.1177940Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1178029Z 2025-07-17T07:36:53.1178123Z warnings.warn(msg) 2025-07-17T07:36:53.1178217Z 2025-07-17T07:36:53.1178432Z --- Parse Warning: 61 / 136 --- 2025-07-17T07:36:53.1179525Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BroadcastingTorchSaveReader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=40. 2025-07-17T07:36:53.1179800Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1179876Z 2025-07-17T07:36:53.1180162Z StorageReader for reading a Torch Save file. This reader will read the entire checkpoint 2025-07-17T07:36:53.1180417Z on the coordinator rank, and then broadcast and shard each tensor to all ranks. 2025-07-17T07:36:53.1180525Z 2025-07-17T07:36:53.1180696Z . N.B. Intended to be used with DynamicMetaLoadPlanner 2025-07-17T07:36:53.1180772Z 2025-07-17T07:36:53.1180856Z .. warning:: 2025-07-17T07:36:53.1181038Z Current implementation only supports loading Tensors. 2025-07-17T07:36:53.1181115Z 2025-07-17T07:36:53.1181230Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:53.1181332Z >>> sd = {"mode": model} 2025-07-17T07:36:53.1181416Z >>> dcp.load( 2025-07-17T07:36:53.1181494Z >>> sd, 2025-07-17T07:36:53.1181657Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-07-17T07:36:53.1181807Z >>> planner=DynamicMetaLoadPlanner(), 2025-07-17T07:36:53.1181921Z >>> checkpoint_id="path_to_model.pt" 2025-07-17T07:36:53.1182013Z >>> ) 2025-07-17T07:36:53.1182091Z 2025-07-17T07:36:53.1182353Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1182430Z 2025-07-17T07:36:53.1182527Z warnings.warn(msg) 2025-07-17T07:36:53.1182617Z 2025-07-17T07:36:53.1182799Z --- Parse Warning: 62 / 136 --- 2025-07-17T07:36:53.1183908Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DynamicMetaLoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=151. 2025-07-17T07:36:53.1184182Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1184259Z 2025-07-17T07:36:53.1184635Z Extension of DefaultLoadPlanner, which creates a new Metadata object based on the passed in state dict, 2025-07-17T07:36:53.1184958Z avoiding the need to read metadata from disk. This is useful when reading formats which don't have a 2025-07-17T07:36:53.1185068Z metadata file, like Torch Save files. 2025-07-17T07:36:53.1185156Z 2025-07-17T07:36:53.1185333Z . N.B. Intended to be used with BroadcastingTorchSaveReader 2025-07-17T07:36:53.1185412Z 2025-07-17T07:36:53.1185509Z .. warning:: 2025-07-17T07:36:53.1185677Z Current implementation only supports loading Tensors. 2025-07-17T07:36:53.1185752Z 2025-07-17T07:36:53.1185876Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:53.1185970Z >>> sd = {"mode": model} 2025-07-17T07:36:53.1186052Z >>> dcp.load( 2025-07-17T07:36:53.1186145Z >>> sd, 2025-07-17T07:36:53.1186295Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-07-17T07:36:53.1186429Z >>> planner=DynamicMetaLoadPlanner(), 2025-07-17T07:36:53.1186539Z >>> checkpoint_id="path_to_model.pt" 2025-07-17T07:36:53.1186621Z >>> ) 2025-07-17T07:36:53.1186710Z 2025-07-17T07:36:53.1186961Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1187036Z 2025-07-17T07:36:53.1187141Z warnings.warn(msg) 2025-07-17T07:36:53.1187217Z 2025-07-17T07:36:53.1187397Z --- Parse Warning: 63 / 136 --- 2025-07-17T07:36:53.1188477Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_sharded_optimizer_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/optimizer.py line=221. 2025-07-17T07:36:53.1188742Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1188832Z 2025-07-17T07:36:53.1189037Z Load a state_dict in conjunction with FSDP sharded optimizer state. 2025-07-17T07:36:53.1189114Z 2025-07-17T07:36:53.1189289Z This is the current recommended way to checkpoint FSDP. 2025-07-17T07:36:53.1189382Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1189531Z >>> import torch.distributed.checkpoint as dist_cp 2025-07-17T07:36:53.1189623Z >>> # Save 2025-07-17T07:36:53.1189719Z >>> model: torch.nn.Model 2025-07-17T07:36:53.1189835Z >>> optim_params = model.parameters() 2025-07-17T07:36:53.1190014Z >>> optim = torch.optim.SGD(optim_params, lr=0.01) 2025-07-17T07:36:53.1190095Z >>> # Save 2025-07-17T07:36:53.1190318Z >>> with FSDP.state_dict_type(model, StateDictType.SHARDED_STATE_DICT): 2025-07-17T07:36:53.1190407Z >>> state_dict = { 2025-07-17T07:36:53.1190563Z >>> "optimizer": FSDP.optim_state_dict(model, optim), 2025-07-17T07:36:53.1190680Z >>> "model": model.state_dict() 2025-07-17T07:36:53.1190759Z >>> } 2025-07-17T07:36:53.1190858Z >>> dist_cp.save_state_dict( 2025-07-17T07:36:53.1190969Z >>> state_dict=optim_state, 2025-07-17T07:36:53.1191171Z >>> storage_writer=dist_cp.FileSystemWriter("checkpoint"), 2025-07-17T07:36:53.1191303Z >>> planner=dist_cp.DefaultSavePlanner(), 2025-07-17T07:36:53.1191394Z >>> ) 2025-07-17T07:36:53.1191473Z >>> 2025-07-17T07:36:53.1191564Z >>> # Load 2025-07-17T07:36:53.1191787Z >>> with FSDP.state_dict_type(model_tp, StateDictType.SHARDED_STATE_DICT): 2025-07-17T07:36:53.1191914Z >>> model_state_dict = model_tp.state_dict() 2025-07-17T07:36:53.1192018Z >>> checkpoint = { 2025-07-17T07:36:53.1192119Z >>> "model": model_state_dict 2025-07-17T07:36:53.1192198Z >>> } 2025-07-17T07:36:53.1192311Z >>> dist_cp.load_state_dict( 2025-07-17T07:36:53.1192472Z >>> state_dict=checkpoint, 2025-07-17T07:36:53.1192665Z >>> storage_reader=dist_cp.FileSystemReader(checkpoint_file), 2025-07-17T07:36:53.1192810Z >>> planner=dist_cp.DefaultLoadPlanner(), 2025-07-17T07:36:53.1192888Z >>> ) 2025-07-17T07:36:53.1193050Z >>> model.load_state_dict(checkpoint["model_state"]) 2025-07-17T07:36:53.1193131Z >>> 2025-07-17T07:36:53.1193300Z >>> optim_state = dist_cp.load_sharded_optimizer_state_dict( 2025-07-17T07:36:53.1193412Z >>> model_state_dict, 2025-07-17T07:36:53.1193520Z >>> optimizer_key="optimizer", 2025-07-17T07:36:53.1193696Z >>> storage_reader=dist_cp.FileSystemReader("checkpoint"), 2025-07-17T07:36:53.1193789Z >>> ) 2025-07-17T07:36:53.1193870Z >>> 2025-07-17T07:36:53.1194013Z >>> flattened_osd = FSDP.optim_state_dict_to_load( 2025-07-17T07:36:53.1194148Z >>> model, optim, optim_state["optimizer"] 2025-07-17T07:36:53.1194229Z >>> ) 2025-07-17T07:36:53.1194307Z >>> 2025-07-17T07:36:53.1194438Z >>> optim.load_state_dict(flattened_osd) 2025-07-17T07:36:53.1194517Z 2025-07-17T07:36:53.1194779Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1194857Z 2025-07-17T07:36:53.1194951Z warnings.warn(msg) 2025-07-17T07:36:53.1195039Z 2025-07-17T07:36:53.1195220Z --- Parse Warning: 64 / 136 --- 2025-07-17T07:36:53.1196188Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SavePlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=122. 2025-07-17T07:36:53.1196463Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1196540Z 2025-07-17T07:36:53.1196852Z Abstract class defining the protocol used by save_state_dict to plan the save process. 2025-07-17T07:36:53.1196933Z 2025-07-17T07:36:53.1197226Z SavePlanners are stateful objects that can be used to customize the whole save process. 2025-07-17T07:36:53.1197317Z 2025-07-17T07:36:53.1197593Z SavePlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-07-17T07:36:53.1197707Z will be visible to the whole process. 2025-07-17T07:36:53.1197797Z 2025-07-17T07:36:53.1198070Z A planner subclass can expect the following sequence of calls during save_state_dict: 2025-07-17T07:36:53.1198144Z 2025-07-17T07:36:53.1198273Z 1) set_up_planner - called on all ranks. 2025-07-17T07:36:53.1198393Z Signals the start of a checkpoint save. 2025-07-17T07:36:53.1198514Z 2025-07-17T07:36:53.1198635Z 2) create_local_plan - called on all ranks. 2025-07-17T07:36:53.1198917Z Process the state_dict and produces a `SavePlan` that will be sent for global planning. 2025-07-17T07:36:53.1199009Z 2025-07-17T07:36:53.1199191Z 3) create_global_plan - called on the coordinator rank only. 2025-07-17T07:36:53.1199384Z Takes the SavePlan from all ranks and make any global decision. 2025-07-17T07:36:53.1199475Z 2025-07-17T07:36:53.1199583Z 4) finish_plan - called on all ranks. 2025-07-17T07:36:53.1199796Z This gives each rank a chance to adjust to global planning decisions. 2025-07-17T07:36:53.1199931Z 2025-07-17T07:36:53.1200080Z 5) resolve_data - called multiple times on each rank 2025-07-17T07:36:53.1200295Z Lookups a value on the `state_dict` for the storage layer to write. 2025-07-17T07:36:53.1200372Z 2025-07-17T07:36:53.1200677Z Users are recommended to extend DefaultSavePlanner instead of this interface directly as 2025-07-17T07:36:53.1200874Z most changes can be expressed by changes in a single method. 2025-07-17T07:36:53.1200950Z 2025-07-17T07:36:53.1201069Z There are 3 usual patterns of extension: 2025-07-17T07:36:53.1201159Z 2025-07-17T07:36:53.1201458Z Rewriting state_dict. This is the simplest way to extend the save process as it 2025-07-17T07:36:53.1201684Z doesn't requite understanding the intrincacies of how SavePlan works: 2025-07-17T07:36:53.1201770Z 2025-07-17T07:36:53.1201883Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:53.1202028Z >>> class RenamePlanner(DefaultSavePlanner): 2025-07-17T07:36:53.1202127Z >>> def set_up_planner( 2025-07-17T07:36:53.1202211Z >>> self, 2025-07-17T07:36:53.1202337Z >>> state_dict: STATE_DICT_TYPE, 2025-07-17T07:36:53.1202460Z >>> storage_meta: Optional[StorageMeta], 2025-07-17T07:36:53.1202565Z >>> is_coordinator: bool, 2025-07-17T07:36:53.1202667Z >>> ) -> None: 2025-07-17T07:36:53.1202775Z >>> # prefix all keys with `foo_`` 2025-07-17T07:36:53.1203061Z >>> super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator) 2025-07-17T07:36:53.1203149Z 2025-07-17T07:36:53.1203482Z Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted 2025-07-17T07:36:53.1203573Z 2025-07-17T07:36:53.1203681Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:53.1203804Z >>> class FP16Planner(DefaultSavePlanner): 2025-07-17T07:36:53.1203921Z >>> def create_local_plan(self): 2025-07-17T07:36:53.1204034Z >>> plan = super().create_local_plan() 2025-07-17T07:36:53.1204125Z >>> for p in plan: 2025-07-17T07:36:53.1204246Z >>> if p.tensor_data is not None: 2025-07-17T07:36:53.1204399Z >>> p.tensor_data.properties.dtype = torch.float16 2025-07-17T07:36:53.1204489Z >>> return plan 2025-07-17T07:36:53.1204579Z >>> 2025-07-17T07:36:53.1204692Z >>> def resolve_data(self, write_item): 2025-07-17T07:36:53.1204827Z >>> item = super().resolve_data(write_item) 2025-07-17T07:36:53.1205095Z >>> return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16) 2025-07-17T07:36:53.1205177Z 2025-07-17T07:36:53.1205616Z Using the global planning step to make central decisions that can't be made individually by each rank 2025-07-17T07:36:53.1205694Z 2025-07-17T07:36:53.1205803Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:53.1205924Z >>> from itertools import zip_longest 2025-07-17T07:36:53.1206028Z >>> from dataclasses import replace 2025-07-17T07:36:53.1206194Z >>> class DDPLoadBalancingPlanner(DefaultSavePlanner): 2025-07-17T07:36:53.1206477Z >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0 2025-07-17T07:36:53.1206673Z >>> # This sample doesn't handle ShardedTensors 2025-07-17T07:36:53.1206808Z >>> def create_global_plan(self, all_plans): 2025-07-17T07:36:53.1206949Z >>> iters = [iter(all_plans[0].items)] * len(all_plans) 2025-07-17T07:36:53.1207043Z >>> items_per_rank = [ 2025-07-17T07:36:53.1207192Z >>> [item for item in items if item is not None] 2025-07-17T07:36:53.1207344Z >>> for items in zip(*zip_longest(*iters), strict=True) 2025-07-17T07:36:53.1207424Z >>> ] 2025-07-17T07:36:53.1207526Z >>> all_plans = [ 2025-07-17T07:36:53.1207639Z >>> replace(plan, items=items) 2025-07-17T07:36:53.1207852Z >>> for plan, items in zip(all_plans, items_per_rank, strict=True) 2025-07-17T07:36:53.1207943Z >>> ] 2025-07-17T07:36:53.1208078Z >>> return super().create_global_plan(all_plans) 2025-07-17T07:36:53.1208169Z 2025-07-17T07:36:53.1208448Z Finally, some planners need to save additional metadata in the checkpoint, this is 2025-07-17T07:36:53.1208718Z accomplished by having each rank contribute their data items in the local plan and 2025-07-17T07:36:53.1208841Z the global planner aggregate them: 2025-07-17T07:36:53.1208917Z 2025-07-17T07:36:53.1209075Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:53.1209240Z >>> class SaveExtraDataPlanner(DefaultSavePlanner): 2025-07-17T07:36:53.1209366Z >>> def create_local_plan(self) -> SavePlan: 2025-07-17T07:36:53.1209492Z >>> plan = super().create_local_plan() 2025-07-17T07:36:53.1209650Z >>> return replace(plan, planner_data="per-rank-data") 2025-07-17T07:36:53.1209731Z >>> 2025-07-17T07:36:53.1210037Z >>> def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]: 2025-07-17T07:36:53.1210228Z >>> global_plan, metadata = super().create_global_plan(all_plans) 2025-07-17T07:36:53.1210381Z >>> merged_data = [p.planner_data for p in global_plan] 2025-07-17T07:36:53.1210561Z >>> metadata = replace(metadata, planner_data=merged_data) 2025-07-17T07:36:53.1210667Z >>> return global_plan, metadata 2025-07-17T07:36:53.1210744Z 2025-07-17T07:36:53.1211007Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1211084Z 2025-07-17T07:36:53.1211190Z warnings.warn(msg) 2025-07-17T07:36:53.1211265Z 2025-07-17T07:36:53.1211464Z --- Parse Warning: 65 / 136 --- 2025-07-17T07:36:53.1212451Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=305. 2025-07-17T07:36:53.1212715Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1212793Z 2025-07-17T07:36:53.1213097Z Abstract class defining the protocol used by load_state_dict to plan the load process. 2025-07-17T07:36:53.1213176Z 2025-07-17T07:36:53.1213476Z LoadPlanner are stateful objects that can be used to customize the whole load process. 2025-07-17T07:36:53.1213554Z 2025-07-17T07:36:53.1213833Z LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-07-17T07:36:53.1213958Z will be visible to the whole process. 2025-07-17T07:36:53.1214033Z 2025-07-17T07:36:53.1214306Z A planner subclass can expect the following sequence of calls during load_state_dict: 2025-07-17T07:36:53.1214393Z 2025-07-17T07:36:53.1214508Z 1) set_up_planner - called on all ranks. 2025-07-17T07:36:53.1214634Z Signals the start of loading a checkpoint. 2025-07-17T07:36:53.1214718Z 2025-07-17T07:36:53.1214838Z 2) create_local_plan - called on all ranks. 2025-07-17T07:36:53.1215128Z Process the state_dict and produces a `LoadPlan` that will be sent for global planning. 2025-07-17T07:36:53.1215247Z 2025-07-17T07:36:53.1215423Z 3) create_global_plan - called on the coordinator rank only. 2025-07-17T07:36:53.1215626Z Takes the LoadPlan from all ranks and make any global decision. 2025-07-17T07:36:53.1215699Z 2025-07-17T07:36:53.1215842Z 4) load_bytes - called multiple times on each rank 2025-07-17T07:36:53.1216013Z This is called once per non-tensor value in state_dict. 2025-07-17T07:36:53.1216089Z 2025-07-17T07:36:53.1216309Z 5) resolve_tensor and commit_tensor - called multiple times on each rank 2025-07-17T07:36:53.1216495Z They are called in pair for each Tensor value in state_dict. 2025-07-17T07:36:53.1216598Z 2025-07-17T07:36:53.1216911Z Users are recommended to extend DefaultLoadPlanner instead of this interface directly as 2025-07-17T07:36:53.1217088Z most changes can be expressed by changes in a single method. 2025-07-17T07:36:53.1217164Z 2025-07-17T07:36:53.1217301Z There are two usual patterns of extension: 2025-07-17T07:36:53.1217378Z 2025-07-17T07:36:53.1217629Z Rewriting state_dict. This is the simplest way to extend the load process as it 2025-07-17T07:36:53.1217892Z doesn't requite understanding the intrincacies of how LoadPlan works. We need 2025-07-17T07:36:53.1218163Z to keep a reference to the original state_dict as load happens in place so 2025-07-17T07:36:53.1218284Z we need to be able to perform it in place 2025-07-17T07:36:53.1218369Z 2025-07-17T07:36:53.1218479Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:53.1218620Z >>> class RenamePlanner(DefaultLoadPlanner): 2025-07-17T07:36:53.1218717Z >>> def set_up_planner( 2025-07-17T07:36:53.1218799Z >>> self, 2025-07-17T07:36:53.1218913Z >>> state_dict: STATE_DICT_TYPE, 2025-07-17T07:36:53.1219008Z >>> metadata: Metadata, 2025-07-17T07:36:53.1219110Z >>> is_coordinator: bool, 2025-07-17T07:36:53.1219205Z >>> ) -> None: 2025-07-17T07:36:53.1219329Z >>> self.original_state_dict = state_dict 2025-07-17T07:36:53.1219496Z >>> state_dict = {"foo_" + k: v for k, v in state_dict.items()} 2025-07-17T07:36:53.1219584Z >>> 2025-07-17T07:36:53.1219698Z >>> if self.flatten_sharded_tensors: 2025-07-17T07:36:53.1219860Z >>> state_dict = _flatten_sharded_tensors(state_dict) 2025-07-17T07:36:53.1219938Z >>> 2025-07-17T07:36:53.1220043Z >>> if self.flatten_state_dict: 2025-07-17T07:36:53.1220233Z >>> state_dict, self.mappings = flatten_state_dict(state_dict) 2025-07-17T07:36:53.1220314Z >>> 2025-07-17T07:36:53.1220421Z >>> self.state_dict = state_dict 2025-07-17T07:36:53.1220531Z >>> self.metadata = metadata 2025-07-17T07:36:53.1220654Z >>> self.is_coordinator = is_coordinator 2025-07-17T07:36:53.1220732Z >>> 2025-07-17T07:36:53.1220858Z >>> def load_bytes(self, read_item, value): 2025-07-17T07:36:53.1220958Z >>> # Remove the "foo_" prefix 2025-07-17T07:36:53.1221273Z >>> self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False) 2025-07-17T07:36:53.1221360Z 2025-07-17T07:36:53.1221440Z 2025-07-17T07:36:53.1221714Z Modifying resolve_tensor and commit_tensor to handle load time transformation. 2025-07-17T07:36:53.1221812Z 2025-07-17T07:36:53.1221924Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:53.1222090Z >>> class MetaModelMaterialize(DefaultSavePlanner): 2025-07-17T07:36:53.1222203Z >>> def resolve_tensor(self, read_item): 2025-07-17T07:36:53.1222334Z >>> tensor = super().resolve_tensor(read_item) 2025-07-17T07:36:53.1222484Z >>> return torch.empty_like(tensor, device="cpu") 2025-07-17T07:36:53.1222568Z >>> 2025-07-17T07:36:53.1222697Z >>> def commit_tensor(self, read_item, tensor): 2025-07-17T07:36:53.1222859Z >>> self.state_dict[read_item.dest_index.fqn] = tensor 2025-07-17T07:36:53.1222962Z 2025-07-17T07:36:53.1223223Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1223298Z 2025-07-17T07:36:53.1223392Z warnings.warn(msg) 2025-07-17T07:36:53.1223476Z 2025-07-17T07:36:53.1223665Z --- Parse Warning: 66 / 136 --- 2025-07-17T07:36:53.1224664Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict.py line=1118. 2025-07-17T07:36:53.1224965Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1225041Z 2025-07-17T07:36:53.1225214Z Return the model state_dict and optimizers state_dict. 2025-07-17T07:36:53.1225291Z 2025-07-17T07:36:53.1225509Z ``get_state_dict`` can process any module that is parallelized by PyTorch 2025-07-17T07:36:53.1225776Z FSDP/fully_shard, DDP/replicate, tensor_parallel/parallelize_module, and any 2025-07-17T07:36:53.1226023Z combination of these parallelisms. The main functions of ``get_state_dict`` 2025-07-17T07:36:53.1226238Z are: 1.) returning a model and optimizer state_dict that can be resharded 2025-07-17T07:36:53.1226508Z with a different number of trainers and/or different parallelisms. 2025-07-17T07:36:53.1226756Z 2.) hiding the parallelism-specific state_dict APIs. Users don't have to call 2025-07-17T07:36:53.1226853Z these APIs. 2025-07-17T07:36:53.1226973Z 3.) sanity checking the result state_dict. 2025-07-17T07:36:53.1227053Z 2025-07-17T07:36:53.1227268Z The keys of the result state dictionary are the canonical FQNs (Fully 2025-07-17T07:36:53.1227504Z Qualified Names). A canonical FQN refers to the FQN based on a parameter's 2025-07-17T07:36:53.1227741Z position in an nn.Module hierarchy. More specifically, a canonical FQN to a 2025-07-17T07:36:53.1227959Z parameter is the FQN returned by ``module.named_parameters()`` or 2025-07-17T07:36:53.1228166Z ``module.named_buffers()`` when the module is not distributed by any 2025-07-17T07:36:53.1228419Z parallelisms. Since the optimizer internally uses parameter IDs to represent 2025-07-17T07:36:53.1228644Z a parameter, there will be a conversion from the parameter IDs to the 2025-07-17T07:36:53.1228759Z canonical FQNs when calling this API. 2025-07-17T07:36:53.1228850Z 2025-07-17T07:36:53.1229066Z ``get_state_dict`` can also process a module that is not parallelized. In 2025-07-17T07:36:53.1229286Z such a case, ``get_state_dict`` only performs one function -- converting the 2025-07-17T07:36:53.1229444Z optimizer parameter IDs to the canonical FQNs. 2025-07-17T07:36:53.1229521Z 2025-07-17T07:36:53.1229644Z Example: 2025-07-17T07:36:53.1229755Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1229849Z >>> import torch 2025-07-17T07:36:53.1230088Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-07-17T07:36:53.1230305Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-07-17T07:36:53.1230528Z >>> from torch.distributed.checkpoint.state_dict import get_state_dict 2025-07-17T07:36:53.1230616Z 2025-07-17T07:36:53.1230762Z >>> fsdp_model = FSDP(copy.deepcopy(model)) 2025-07-17T07:36:53.1230945Z >>> fsdp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-07-17T07:36:53.1231079Z >>> ddp_model = DDP(copy.deepcopy(model)) 2025-07-17T07:36:53.1231256Z >>> ddp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-07-17T07:36:53.1231339Z 2025-07-17T07:36:53.1231427Z 2025-07-17T07:36:53.1231656Z >>> ddp_state_dict, ddp_optim_state_dict = get_state_dict(ddp_model, ddp_optim) 2025-07-17T07:36:53.1231835Z >>> fsdp_state_dict, fsdp_optim_state_dict = get_state_dict( 2025-07-17T07:36:53.1231942Z ... fsdp_model, fsdp_optim 2025-07-17T07:36:53.1232065Z ... ) 2025-07-17T07:36:53.1232153Z 2025-07-17T07:36:53.1232363Z >>> # if we simply call ddp_model.state_dict() and fsdp_model.state_dict(), 2025-07-17T07:36:53.1232462Z >>> # the asserts will fail. 2025-07-17T07:36:53.1232596Z >>> assert ddp_state_dict == fsdp_state_dict 2025-07-17T07:36:53.1232741Z >>> assert ddp_optim_state == fsdp_optim_state_dict 2025-07-17T07:36:53.1232818Z 2025-07-17T07:36:53.1232932Z 2025-07-17T07:36:53.1233010Z Args: 2025-07-17T07:36:53.1233149Z model (nn.Module): the nn.Module to the model. 2025-07-17T07:36:53.1233338Z optimizers (Union[None, Optimizer, Iterable[Optimizer]]): 2025-07-17T07:36:53.1233518Z The optimizers that are used to optimize ``model``. 2025-07-17T07:36:53.1233807Z submodules (deprecated): Optional[set[nn.Module]]: only return the model parameters 2025-07-17T07:36:53.1233915Z that belong to the submodules. 2025-07-17T07:36:53.1234082Z options (StateDictOptions): the options to control how 2025-07-17T07:36:53.1234298Z model state_dict and optimizer state_dict should be returned. See 2025-07-17T07:36:53.1234420Z `StateDictOptions` for the details. 2025-07-17T07:36:53.1234525Z 2025-07-17T07:36:53.1234615Z Returns: 2025-07-17T07:36:53.1234853Z ``Tuple`` that contain model state_dict and optimizer state_dict. 2025-07-17T07:36:53.1234930Z 2025-07-17T07:36:53.1235164Z :rtype: typing.Tuple[typing.Dict[str, ValueType], OptimizerStateType] 2025-07-17T07:36:53.1235242Z 2025-07-17T07:36:53.1235504Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1235580Z 2025-07-17T07:36:53.1235675Z warnings.warn(msg) 2025-07-17T07:36:53.1235759Z 2025-07-17T07:36:53.1235945Z --- Parse Warning: 67 / 136 --- 2025-07-17T07:36:53.1236922Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_loader.py line=62. 2025-07-17T07:36:53.1237195Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1237271Z 2025-07-17T07:36:53.1237478Z Load a checkpoint into a distributed state dict in SPMD style. 2025-07-17T07:36:53.1237554Z 2025-07-17T07:36:53.1237771Z Each rank must have the same keys in their ``state_dict`` provided to this 2025-07-17T07:36:53.1238006Z API. Mismatched keys may result in hangs or errors. If unsure, you can use 2025-07-17T07:36:53.1238220Z the ``utils._assert_same_keys`` API to check (but may incur communication 2025-07-17T07:36:53.1238300Z costs). 2025-07-17T07:36:53.1238387Z 2025-07-17T07:36:53.1238564Z Each rank will try to read the least amount of data necessary 2025-07-17T07:36:53.1238790Z to fulfill the requested `state_dict`. When loading :class:`ShardedTensor` 2025-07-17T07:36:53.1239042Z or :class:`DTensor` instances, each rank only reads data for their local shards. 2025-07-17T07:36:53.1239119Z 2025-07-17T07:36:53.1239382Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-07-17T07:36:53.1239636Z load will first call ``state_dict`` before attempting deserialization, followed by 2025-07-17T07:36:53.1239800Z ``load_state_dict`` once the deserialization is complete. 2025-07-17T07:36:53.1240065Z For each non-``Stateful`` object, load will deserialize the object, and then replace 2025-07-17T07:36:53.1240210Z it in the ``state_dict`` with the deserialized object. 2025-07-17T07:36:53.1240290Z 2025-07-17T07:36:53.1240391Z .. warning:: 2025-07-17T07:36:53.1240554Z All tensors in ``state_dict`` must be allocated on their 2025-07-17T07:36:53.1240725Z destination device *prior to* calling this function. 2025-07-17T07:36:53.1240798Z 2025-07-17T07:36:53.1241020Z All non-tensor data is loaded using `torch.load()` and modified in place 2025-07-17T07:36:53.1241148Z on state_dict. 2025-07-17T07:36:53.1241224Z 2025-07-17T07:36:53.1241308Z .. warning:: 2025-07-17T07:36:53.1241518Z Users must call `load_state_dict` on the root module to ensure load 2025-07-17T07:36:53.1241700Z pos-processing and non-tensor data properly propagates. 2025-07-17T07:36:53.1241775Z 2025-07-17T07:36:53.1241865Z .. note: 2025-07-17T07:36:53.1242083Z If no process group is initialized, this function will assume the intent 2025-07-17T07:36:53.1242310Z is to load a checkpoint into the local process. This can be useful in the 2025-07-17T07:36:53.1242579Z case of local inference, and when using regular Tensors (as opposed to DTensor 2025-07-17T07:36:53.1242675Z or ShardedTensor) 2025-07-17T07:36:53.1242760Z 2025-07-17T07:36:53.1242849Z .. note: 2025-07-17T07:36:53.1242983Z Rank 0 is assumed to be the coordinator rank. 2025-07-17T07:36:53.1243073Z 2025-07-17T07:36:53.1243151Z Args: 2025-07-17T07:36:53.1243356Z state_dict (Dict[str, Any]): The state_dict to load the checkpoint into. 2025-07-17T07:36:53.1243509Z checkpoint_id (Union[str, os.PathLike, None]): 2025-07-17T07:36:53.1243761Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-07-17T07:36:53.1243971Z depends on the storage. It can be a path to a folder or to a file. 2025-07-17T07:36:53.1244132Z It can also be a key if the storage is a key-value store. 2025-07-17T07:36:53.1244225Z (Default: ``None``) 2025-07-17T07:36:53.1244365Z storage_reader (Optional[StorageReader]): 2025-07-17T07:36:53.1244563Z Instance of StorageWriter used to perform reads. If this is not 2025-07-17T07:36:53.1244758Z specified, DCP will automatically infer the reader based on the 2025-07-17T07:36:53.1244966Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-07-17T07:36:53.1245073Z be raised. (Default: ``None``) 2025-07-17T07:36:53.1245185Z planner (Optional[LoadPlanner]): 2025-07-17T07:36:53.1245478Z Instance of LoadPlanner. If this is not specified, the default 2025-07-17T07:36:53.1245608Z planner will be used. (Default: ``None``) 2025-07-17T07:36:53.1245750Z process_group (Optional[ProcessGroup]): 2025-07-17T07:36:53.1245927Z ProcessGroup to be used for cross-rank synchronization. 2025-07-17T07:36:53.1246020Z (Default: ``None``) 2025-07-17T07:36:53.1246238Z no_dist (bool): If ``True``, this function will assume the intent is to load 2025-07-17T07:36:53.1246489Z a checkpoint without using cross-rank synchronization. (Default: ``False``) 2025-07-17T07:36:53.1246569Z Returns: 2025-07-17T07:36:53.1246660Z None. 2025-07-17T07:36:53.1246736Z 2025-07-17T07:36:53.1246827Z Examples 2025-07-17T07:36:53.1246921Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1247020Z >>> my_model = MyModule() 2025-07-17T07:36:53.1247163Z >>> optimizer = Adagrad(my_model.parameters()) 2025-07-17T07:36:53.1247286Z >>> model_state_dict = my_model.state_dict() 2025-07-17T07:36:53.1247516Z >>> fs_storage_reader = torch.distributed.checkpoint.FileSystemReader( 2025-07-17T07:36:53.1247622Z ... "/checkpoint/1" 2025-07-17T07:36:53.1247701Z ... ) 2025-07-17T07:36:53.1247777Z 2025-07-17T07:36:53.1247938Z >>> torch.distributed.checkpoint.load_state_dict( 2025-07-17T07:36:53.1248046Z >>> state_dict=model_state_dict, 2025-07-17T07:36:53.1248161Z >>> storage_reader=fs_storage_reader, 2025-07-17T07:36:53.1248249Z >>> ) 2025-07-17T07:36:53.1248323Z 2025-07-17T07:36:53.1248522Z >>> # module.load_state_dict() function might have customized steps 2025-07-17T07:36:53.1248643Z >>> # to flush the state_dict, must call it to 2025-07-17T07:36:53.1248745Z >>> # ensure correct behavior. 2025-07-17T07:36:53.1248912Z >>> my_model.load_state_dict(model_state_dict) 2025-07-17T07:36:53.1248986Z 2025-07-17T07:36:53.1249066Z .. note:: 2025-07-17T07:36:53.1249280Z load_state_dict uses collectives to coordinate reads across ranks. 2025-07-17T07:36:53.1249492Z For NCCL-based process groups, internal tensor representations of 2025-07-17T07:36:53.1249718Z objects must be moved to the GPU device before communication takes place. 2025-07-17T07:36:53.1249942Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-07-17T07:36:53.1250164Z and it is the user's responsibility to ensure that this is set so that each 2025-07-17T07:36:53.1250377Z rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-07-17T07:36:53.1250451Z 2025-07-17T07:36:53.1250698Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1250783Z 2025-07-17T07:36:53.1250879Z warnings.warn(msg) 2025-07-17T07:36:53.1250955Z 2025-07-17T07:36:53.1251166Z --- Parse Warning: 68 / 136 --- 2025-07-17T07:36:53.1252189Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=96. 2025-07-17T07:36:53.1252463Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1252541Z 2025-07-17T07:36:53.1252658Z Save a distributed model in SPMD style. 2025-07-17T07:36:53.1252746Z 2025-07-17T07:36:53.1252935Z This function is different from ``torch.save()`` as it handles 2025-07-17T07:36:53.1253191Z ``ShardedTensor`` , and ``DTensor`` by having each rank only save their local shards. 2025-07-17T07:36:53.1253276Z 2025-07-17T07:36:53.1253527Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-07-17T07:36:53.1253677Z save will call ``state_dict`` before serialization. 2025-07-17T07:36:53.1253765Z 2025-07-17T07:36:53.1253851Z .. warning:: 2025-07-17T07:36:53.1254096Z There is no guarantees of Backwards Compatibility across PyTorch versions 2025-07-17T07:36:53.1254195Z for saved state_dicts. 2025-07-17T07:36:53.1254274Z 2025-07-17T07:36:53.1254367Z .. warning:: 2025-07-17T07:36:53.1254570Z If using the `process_group` argument, make sure that only its ranks 2025-07-17T07:36:53.1254771Z call `save_state_dict` and that all data in state_dict belong to it. 2025-07-17T07:36:53.1254859Z 2025-07-17T07:36:53.1254939Z .. note:: 2025-07-17T07:36:53.1255194Z When saving checkpoint for FSDP's `ShardingStrategy.HYBRID_SHARD`, only one of 2025-07-17T07:36:53.1255462Z the shard_group should be calling `save_state_dict` and the corresponding process 2025-07-17T07:36:53.1255568Z group needs to be passed in. 2025-07-17T07:36:53.1255654Z 2025-07-17T07:36:53.1255734Z .. note:: 2025-07-17T07:36:53.1255998Z If no process group is available, this function assumes the intention is to save the 2025-07-17T07:36:53.1256115Z state_dict in the local process. 2025-07-17T07:36:53.1256189Z 2025-07-17T07:36:53.1256268Z .. note: 2025-07-17T07:36:53.1256416Z Rank 0 is assumed to be the coordinator rank. 2025-07-17T07:36:53.1256502Z 2025-07-17T07:36:53.1256578Z 2025-07-17T07:36:53.1256671Z Args: 2025-07-17T07:36:53.1256823Z state_dict (Dict[str, Any]): The state_dict to save. 2025-07-17T07:36:53.1256981Z checkpoint_id (Union[str, os.PathLike, None]): 2025-07-17T07:36:53.1257188Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-07-17T07:36:53.1257390Z depends on the storage. It can be a path to a folder or to a file. 2025-07-17T07:36:53.1257565Z It can also be a key if the storage is a key-value store. 2025-07-17T07:36:53.1257691Z (Default: ``None``) 2025-07-17T07:36:53.1257821Z storage_writer (Optional[StorageWriter]): 2025-07-17T07:36:53.1258039Z Instance of StorageWriter used to perform writes. If this is not 2025-07-17T07:36:53.1258239Z specified, DCP will automatically infer the writer based on the 2025-07-17T07:36:53.1258442Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-07-17T07:36:53.1258563Z be raised. (Default: ``None``) 2025-07-17T07:36:53.1258676Z planner (Optional[SavePlanner]): 2025-07-17T07:36:53.1258887Z Instance of SavePlanner. If this is not specified, the default 2025-07-17T07:36:53.1259042Z planner will be used. (Default: ``None``) 2025-07-17T07:36:53.1259208Z process_group (Optional[ProcessGroup]): 2025-07-17T07:36:53.1259459Z ProcessGroup to be used for cross-rank synchronization. 2025-07-17T07:36:53.1259610Z (Default: ``None``) 2025-07-17T07:36:53.1259754Z no_dist (bool): 2025-07-17T07:36:53.1259995Z If ``True``, this function will assume the intent is to load 2025-07-17T07:36:53.1260165Z a checkpoint without using cross-rank synchronization. 2025-07-17T07:36:53.1260275Z (Default: ``False``) 2025-07-17T07:36:53.1260352Z 2025-07-17T07:36:53.1260507Z Returns: 2025-07-17T07:36:53.1260680Z Metadata: Metadata object for the saved checkpoint. 2025-07-17T07:36:53.1260759Z 2025-07-17T07:36:53.1260842Z Example: 2025-07-17T07:36:53.1260955Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1261053Z >>> my_model = MyModule() 2025-07-17T07:36:53.1261134Z 2025-07-17T07:36:53.1261259Z >>> state_dict = {"model": my_model} 2025-07-17T07:36:53.1261334Z 2025-07-17T07:36:53.1261565Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-07-17T07:36:53.1261678Z ... "/checkpoint/1" 2025-07-17T07:36:53.1261760Z ... ) 2025-07-17T07:36:53.1261907Z >>> torch.distributed.checkpoint.save( 2025-07-17T07:36:53.1262009Z >>> state_dict=state_dict, 2025-07-17T07:36:53.1262122Z >>> storage_writer=fs_storage_writer, 2025-07-17T07:36:53.1262212Z >>> ) 2025-07-17T07:36:53.1262286Z 2025-07-17T07:36:53.1262370Z .. note:: 2025-07-17T07:36:53.1262593Z save_state_dict uses collectives to coordinate writes across ranks. 2025-07-17T07:36:53.1262804Z For NCCL-based process groups, internal tensor representations of 2025-07-17T07:36:53.1263031Z objects must be moved to the GPU device before communication takes place. 2025-07-17T07:36:53.1263261Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-07-17T07:36:53.1263461Z and it is the user's responsibility to ensure that this is set so that 2025-07-17T07:36:53.1263666Z each rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-07-17T07:36:53.1263741Z 2025-07-17T07:36:53.1263992Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1264082Z 2025-07-17T07:36:53.1264175Z warnings.warn(msg) 2025-07-17T07:36:53.1264250Z 2025-07-17T07:36:53.1264468Z --- Parse Warning: 69 / 136 --- 2025-07-17T07:36:53.1265474Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=async_save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=221. 2025-07-17T07:36:53.1265748Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1266010Z Asynchronous version of ``save``. This code first de-stages the state_dict on to the 2025-07-17T07:36:53.1266300Z staging storage (defaults to CPU memory), and then calls the `save` in a separate thread. 2025-07-17T07:36:53.1266391Z 2025-07-17T07:36:53.1266477Z .. warning:: 2025-07-17T07:36:53.1266718Z This feature is experimental and subject to change. 2025-07-17T07:36:53.1266873Z MUST CALL CLOSE AFTER LAST CHECKPOINT IS SAVED 2025-07-17T07:36:53.1266950Z 2025-07-17T07:36:53.1267033Z Args: 2025-07-17T07:36:53.1267195Z state_dict (Dict[str, Any]): The state_dict to save. 2025-07-17T07:36:53.1267340Z checkpoint_id (Union[str, os.PathLike, None]): 2025-07-17T07:36:53.1267557Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-07-17T07:36:53.1267756Z depends on the storage. It can be a path to a folder or to a file. 2025-07-17T07:36:53.1267947Z It can also be a key if the storage is a key-value store. 2025-07-17T07:36:53.1268057Z (Default: ``None``) 2025-07-17T07:36:53.1268189Z storage_writer (Optional[StorageWriter]): 2025-07-17T07:36:53.1268399Z Instance of StorageWriter used to perform 'stage' and 'save'. If 2025-07-17T07:36:53.1268647Z this is not specified, DCP will automatically infer the writer based on the 2025-07-17T07:36:53.1268849Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-07-17T07:36:53.1268970Z be raised. (Default: ``None``) 2025-07-17T07:36:53.1269138Z planner (Optional[SavePlanner]): 2025-07-17T07:36:53.1269335Z Instance of SavePlanner. If this is not specified, the default 2025-07-17T07:36:53.1269476Z planner will be used. (Default: ``None``) 2025-07-17T07:36:53.1269604Z process_group (Optional[ProcessGroup]): 2025-07-17T07:36:53.1269785Z ProcessGroup to be used for cross-rank synchronization. 2025-07-17T07:36:53.1269892Z (Default: ``None``) 2025-07-17T07:36:53.1270232Z async_checkpointer_type (AsyncCheckpointerType): 2025-07-17T07:36:53.1270415Z whether to do checkpoint in separate thread or process 2025-07-17T07:36:53.1270562Z (Default: ``AsyncCheckpointerType.THREAD``) 2025-07-17T07:36:53.1270668Z async_stager (AsyncStager): 2025-07-17T07:36:53.1270936Z provides staging implementation. If storage_writer implements AsyncStager 2025-07-17T07:36:53.1271146Z and async_stager is provided, async_stager will be used for staging 2025-07-17T07:36:53.1271222Z 2025-07-17T07:36:53.1271317Z Returns: 2025-07-17T07:36:53.1271525Z Future: A future holding the resultant Metadata object from `save`. 2025-07-17T07:36:53.1271599Z 2025-07-17T07:36:53.1271691Z Example: 2025-07-17T07:36:53.1271790Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1271904Z >>> my_model = MyModule() 2025-07-17T07:36:53.1271980Z 2025-07-17T07:36:53.1272092Z >>> state_dict = {"model": my_model} 2025-07-17T07:36:53.1272180Z 2025-07-17T07:36:53.1272413Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-07-17T07:36:53.1272510Z ... "/checkpoint/1" 2025-07-17T07:36:53.1272601Z ... ) 2025-07-17T07:36:53.1272808Z >>> checkpoint_future = torch.distributed.checkpoint.async_save( 2025-07-17T07:36:53.1272911Z >>> state_dict=state_dict, 2025-07-17T07:36:53.1273044Z >>> storage_writer=fs_storage_writer, 2025-07-17T07:36:53.1273124Z >>> ) 2025-07-17T07:36:53.1273203Z >>> 2025-07-17T07:36:53.1273310Z >>> # ... do some work ... 2025-07-17T07:36:53.1273389Z >>> 2025-07-17T07:36:53.1273551Z >>> checkpoint_future.result() 2025-07-17T07:36:53.1273629Z 2025-07-17T07:36:53.1273706Z 2025-07-17T07:36:53.1273968Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1274044Z 2025-07-17T07:36:53.1274137Z warnings.warn(msg) 2025-07-17T07:36:53.1274222Z 2025-07-17T07:36:53.1274422Z --- Parse Warning: 70 / 136 --- 2025-07-17T07:36:53.1275575Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=construct_and_record_rdzv_event in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/elastic/events/__init__.py line=94. 2025-07-17T07:36:53.1275856Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1275934Z 2025-07-17T07:36:53.1276149Z Initialize rendezvous event object and record its operations. 2025-07-17T07:36:53.1276225Z 2025-07-17T07:36:53.1276304Z Args: 2025-07-17T07:36:53.1276478Z run_id (str): The run id of the rendezvous. 2025-07-17T07:36:53.1276623Z message (str): The message describing the event. 2025-07-17T07:36:53.1276875Z node_state (NodeState): The state of the node (INIT, RUNNING, SUCCEEDED, FAILED). 2025-07-17T07:36:53.1277065Z name (str): Event name. (E.g. Current action being performed). 2025-07-17T07:36:53.1277182Z hostname (str): Hostname of the node. 2025-07-17T07:36:53.1277331Z pid (Optional[int]): The process id of the node. 2025-07-17T07:36:53.1277571Z master_endpoint (str): The master endpoint for the rendezvous store, if known. 2025-07-17T07:36:53.1277931Z local_id (Optional[int]): The local_id of the node, if defined in dynamic_rendezvous.py 2025-07-17T07:36:53.1278103Z rank (Optional[int]): The rank of the node, if known. 2025-07-17T07:36:53.1278184Z Returns: 2025-07-17T07:36:53.1278265Z None 2025-07-17T07:36:53.1278359Z Example: 2025-07-17T07:36:53.1278484Z >>> # See DynamicRendezvousHandler class 2025-07-17T07:36:53.1278575Z >>> def _record( 2025-07-17T07:36:53.1278670Z ... self, 2025-07-17T07:36:53.1278760Z ... message: str, 2025-07-17T07:36:53.1278907Z ... node_state: NodeState = NodeState.RUNNING, 2025-07-17T07:36:53.1279011Z ... rank: Optional[int] = None, 2025-07-17T07:36:53.1279097Z ... ) -> None: 2025-07-17T07:36:53.1279227Z ... construct_and_record_rdzv_event( 2025-07-17T07:36:53.1279385Z ... name=f"{self.__class__.__name__}.{get_method_name()}", 2025-07-17T07:36:53.1279501Z ... run_id=self._settings.run_id, 2025-07-17T07:36:53.1279608Z ... message=message, 2025-07-17T07:36:53.1279708Z ... node_state=node_state, 2025-07-17T07:36:53.1279822Z ... hostname=self._this_node.addr, 2025-07-17T07:36:53.1279939Z ... pid=self._this_node.pid, 2025-07-17T07:36:53.1280058Z ... local_id=self._this_node.local_id, 2025-07-17T07:36:53.1280160Z ... rank=rank, 2025-07-17T07:36:53.1280238Z ... ) 2025-07-17T07:36:53.1280314Z 2025-07-17T07:36:53.1280579Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1280655Z 2025-07-17T07:36:53.1280748Z warnings.warn(msg) 2025-07-17T07:36:53.1280838Z 2025-07-17T07:36:53.1281026Z --- Parse Warning: 71 / 136 --- 2025-07-17T07:36:53.1281957Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MixedPrecision in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=114. 2025-07-17T07:36:53.1282227Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1282305Z 2025-07-17T07:36:53.1282480Z This configures FSDP-native mixed precision training. 2025-07-17T07:36:53.1282558Z 2025-07-17T07:36:53.1282644Z Attributes: 2025-07-17T07:36:53.1282931Z param_dtype (Optional[torch.dtype]): This specifies the dtype for model 2025-07-17T07:36:53.1283130Z parameters during forward and backward and thus the dtype for 2025-07-17T07:36:53.1283351Z forward and backward computation. Outside forward and backward, the 2025-07-17T07:36:53.1283579Z *sharded* parameters are kept in full precision (e.g. for the 2025-07-17T07:36:53.1283784Z optimizer step), and for model checkpointing, the parameters are 2025-07-17T07:36:53.1283949Z always saved in full precision. (Default: ``None``) 2025-07-17T07:36:53.1284162Z reduce_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-07-17T07:36:53.1284373Z gradient reduction (i.e. reduce-scatter or all-reduce). If this is 2025-07-17T07:36:53.1284555Z ``None`` but ``param_dtype`` is not ``None``, then this takes on 2025-07-17T07:36:53.1284749Z the ``param_dtype`` value, still running gradient reduction in low 2025-07-17T07:36:53.1284985Z precision. This is permitted to differ from ``param_dtype``, e.g. 2025-07-17T07:36:53.1285195Z to force gradient reduction to run in full precision. (Default: 2025-07-17T07:36:53.1285278Z ``None``) 2025-07-17T07:36:53.1285569Z buffer_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-07-17T07:36:53.1285766Z buffers. FSDP does not shard buffers. Rather, FSDP casts them to 2025-07-17T07:36:53.1285959Z ``buffer_dtype`` in the first forward pass and keeps them in that 2025-07-17T07:36:53.1286231Z dtype thereafter. For model checkpointing, the buffers are saved 2025-07-17T07:36:53.1286411Z in full precision except for ``LOCAL_STATE_DICT``. (Default: 2025-07-17T07:36:53.1286494Z ``None``) 2025-07-17T07:36:53.1286699Z keep_low_precision_grads (bool): If ``False``, then FSDP upcasts 2025-07-17T07:36:53.1286917Z gradients to full precision after the backward pass in preparation 2025-07-17T07:36:53.1287127Z for the optimizer step. If ``True``, then FSDP keeps the gradients 2025-07-17T07:36:53.1287320Z in the dtype used for gradient reduction, which can save memory if 2025-07-17T07:36:53.1287523Z using a custom optimizer that supports running in low precision. 2025-07-17T07:36:53.1287634Z (Default: ``False``) 2025-07-17T07:36:53.1287838Z cast_forward_inputs (bool): If ``True``, then this FSDP module casts 2025-07-17T07:36:53.1288037Z its forward args and kwargs to ``param_dtype``. This is to ensure 2025-07-17T07:36:53.1288265Z that parameter and input dtypes match for forward computation, as 2025-07-17T07:36:53.1288466Z required by many ops. This may need to be set to ``True`` when only 2025-07-17T07:36:53.1288695Z applying mixed precision to some but not all FSDP modules, in which 2025-07-17T07:36:53.1288903Z case a mixed-precision FSDP submodule needs to recast its inputs. 2025-07-17T07:36:53.1289004Z (Default: ``False``) 2025-07-17T07:36:53.1289233Z cast_root_forward_inputs (bool): If ``True``, then the root FSDP module 2025-07-17T07:36:53.1289429Z casts its forward args and kwargs to ``param_dtype``, overriding 2025-07-17T07:36:53.1289614Z the value of ``cast_forward_inputs``. For non-root FSDP modules, 2025-07-17T07:36:53.1289767Z this does not do anything. (Default: ``True``) 2025-07-17T07:36:53.1289979Z _module_classes_to_ignore: (Sequence[Type[nn.Module]]): This specifies 2025-07-17T07:36:53.1290174Z module classes to ignore for mixed precision when using an 2025-07-17T07:36:53.1290351Z ``auto_wrap_policy``: Modules of these classes will have FSDP 2025-07-17T07:36:53.1290558Z applied to them separately with mixed precision disabled (meaning 2025-07-17T07:36:53.1290773Z that the final FSDP construction would deviate from the specified 2025-07-17T07:36:53.1290961Z policy). If ``auto_wrap_policy`` is not specified, then this does 2025-07-17T07:36:53.1291156Z not do anything. This API is experimental and subject to change. 2025-07-17T07:36:53.1291277Z (Default: ``(_BatchNorm,)``) 2025-07-17T07:36:53.1291355Z 2025-07-17T07:36:53.1291565Z .. note:: This API is experimental and subject to change. 2025-07-17T07:36:53.1291645Z 2025-07-17T07:36:53.1291863Z .. note:: Only floating point tensors are cast to their specified dtypes. 2025-07-17T07:36:53.1291955Z 2025-07-17T07:36:53.1292137Z .. note:: In ``summon_full_params``, parameters are forced to full 2025-07-17T07:36:53.1292245Z precision, but buffers are not. 2025-07-17T07:36:53.1292334Z 2025-07-17T07:36:53.1292531Z .. note:: Layer norm and batch norm accumulate in ``float32`` even when 2025-07-17T07:36:53.1292737Z their inputs are in a low precision like ``float16`` or ``bfloat16``. 2025-07-17T07:36:53.1293003Z Disabling FSDP's mixed precision for those norm modules only means that 2025-07-17T07:36:53.1293211Z the affine parameters are kept in ``float32``. However, this incurs 2025-07-17T07:36:53.1293456Z separate all-gathers and reduce-scatters for those norm modules, which 2025-07-17T07:36:53.1293670Z may be inefficient, so if the workload permits, the user should prefer 2025-07-17T07:36:53.1293813Z to still apply mixed precision to those modules. 2025-07-17T07:36:53.1293904Z 2025-07-17T07:36:53.1294107Z .. note:: By default, if the user passes a model with any ``_BatchNorm`` 2025-07-17T07:36:53.1294377Z modules and specifies an ``auto_wrap_policy``, then the batch norm 2025-07-17T07:36:53.1294601Z modules will have FSDP applied to them separately with mixed precision 2025-07-17T07:36:53.1294772Z disabled. See the ``_module_classes_to_ignore`` argument. 2025-07-17T07:36:53.1294870Z 2025-07-17T07:36:53.1295075Z .. note:: ``MixedPrecision`` has ``cast_root_forward_inputs=True`` and 2025-07-17T07:36:53.1295286Z ``cast_forward_inputs=False`` by default. For the root FSDP instance, 2025-07-17T07:36:53.1295467Z its ``cast_root_forward_inputs`` takes precedence over its 2025-07-17T07:36:53.1295639Z ``cast_forward_inputs``. For non-root FSDP instances, their 2025-07-17T07:36:53.1295862Z ``cast_root_forward_inputs`` values are ignored. The default setting is 2025-07-17T07:36:53.1296077Z sufficient for the typical case where each FSDP instance has the same 2025-07-17T07:36:53.1296298Z ``MixedPrecision`` configuration and only needs to cast inputs to the 2025-07-17T07:36:53.1296488Z ``param_dtype`` at the beginning of the model's forward pass. 2025-07-17T07:36:53.1296564Z 2025-07-17T07:36:53.1296763Z .. note:: For nested FSDP instances with different ``MixedPrecision`` 2025-07-17T07:36:53.1297007Z configurations, we recommend setting individual ``cast_forward_inputs`` 2025-07-17T07:36:53.1297214Z values to configure casting inputs or not before each instance's 2025-07-17T07:36:53.1297415Z forward. In such a case, since the casts happen before each FSDP 2025-07-17T07:36:53.1297625Z instance's forward, a parent FSDP instance should have its non-FSDP 2025-07-17T07:36:53.1297855Z submodules run before its FSDP submodules to avoid the activation dtype 2025-07-17T07:36:53.1298069Z being changed due to a different ``MixedPrecision`` configuration. 2025-07-17T07:36:53.1298146Z 2025-07-17T07:36:53.1298235Z Example:: 2025-07-17T07:36:53.1298323Z 2025-07-17T07:36:53.1298456Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.1298618Z >>> model = nn.Sequential(nn.Linear(3, 3), nn.Linear(3, 3)) 2025-07-17T07:36:53.1298721Z >>> model[1] = FSDP( 2025-07-17T07:36:53.1298810Z >>> model[1], 2025-07-17T07:36:53.1299127Z >>> mixed_precision=MixedPrecision(param_dtype=torch.float16, cast_forward_inputs=True), 2025-07-17T07:36:53.1299209Z >>> ) 2025-07-17T07:36:53.1299298Z >>> model = FSDP( 2025-07-17T07:36:53.1299396Z >>> model, 2025-07-17T07:36:53.1299698Z >>> mixed_precision=MixedPrecision(param_dtype=torch.bfloat16, cast_forward_inputs=True), 2025-07-17T07:36:53.1299805Z >>> ) 2025-07-17T07:36:53.1299893Z 2025-07-17T07:36:53.1300100Z The above shows a working example. On the other hand, if ``model[1]`` 2025-07-17T07:36:53.1300298Z were replaced with ``model[0]``, meaning that the submodule using 2025-07-17T07:36:53.1300537Z different ``MixedPrecision`` ran its forward first, then ``model[1]`` 2025-07-17T07:36:53.1300754Z would incorrectly see ``float16`` activations instead of ``bfloat16`` 2025-07-17T07:36:53.1300846Z ones. 2025-07-17T07:36:53.1300923Z 2025-07-17T07:36:53.1300998Z 2025-07-17T07:36:53.1301285Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1301361Z 2025-07-17T07:36:53.1301453Z warnings.warn(msg) 2025-07-17T07:36:53.1301540Z 2025-07-17T07:36:53.1301741Z --- Parse Warning: 72 / 136 --- 2025-07-17T07:36:53.1302745Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullStateDictConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=295. 2025-07-17T07:36:53.1303020Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1303096Z 2025-07-17T07:36:53.1303360Z ``FullStateDictConfig`` is a config class meant to be used with 2025-07-17T07:36:53.1303558Z ``StateDictType.FULL_STATE_DICT``. We recommend enabling both 2025-07-17T07:36:53.1303756Z ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state 2025-07-17T07:36:53.1304011Z dicts to save GPU memory and CPU memory, respectively. This config class 2025-07-17T07:36:53.1304203Z is meant to be used via the :func:`state_dict_type` context manager as 2025-07-17T07:36:53.1304284Z follows: 2025-07-17T07:36:53.1304372Z 2025-07-17T07:36:53.1304499Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.1304748Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-07-17T07:36:53.1304872Z >>> fsdp = FSDP(model, auto_wrap_policy=...) 2025-07-17T07:36:53.1305070Z >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True) 2025-07-17T07:36:53.1305301Z >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg): 2025-07-17T07:36:53.1305472Z >>> state = fsdp.state_dict() 2025-07-17T07:36:53.1305679Z >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0. 2025-07-17T07:36:53.1305929Z >>> # To reload checkpoint for inference, finetuning, transfer learning, etc: 2025-07-17T07:36:53.1306161Z >>> model = model_fn() # Initialize model in preparation for wrapping with FSDP 2025-07-17T07:36:53.1306273Z >>> if dist.get_rank() == 0: 2025-07-17T07:36:53.1306450Z >>> # Load checkpoint only on rank 0 to avoid memory redundancy 2025-07-17T07:36:53.1306589Z >>> state_dict = torch.load("my_checkpoint.pt") 2025-07-17T07:36:53.1306720Z >>> model.load_state_dict(state_dict) 2025-07-17T07:36:53.1306950Z >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument 2025-07-17T07:36:53.1307186Z >>> # communicates loaded checkpoint states from rank 0 to rest of the world. 2025-07-17T07:36:53.1307289Z >>> fsdp = FSDP( 2025-07-17T07:36:53.1307371Z ... model, 2025-07-17T07:36:53.1307513Z ... device_id=torch.cuda.current_device(), 2025-07-17T07:36:53.1307617Z ... auto_wrap_policy=..., 2025-07-17T07:36:53.1307717Z ... sync_module_states=True, 2025-07-17T07:36:53.1307809Z ... ) 2025-07-17T07:36:53.1308016Z >>> # After this point, all ranks have FSDP model with loaded checkpoint. 2025-07-17T07:36:53.1308092Z 2025-07-17T07:36:53.1308188Z Attributes: 2025-07-17T07:36:53.1308379Z rank0_only (bool): If ``True``, then only rank 0 saves the full state 2025-07-17T07:36:53.1308601Z dict, and nonzero ranks save an empty dict. If ``False``, then all 2025-07-17T07:36:53.1308764Z ranks save the full state dict. (Default: ``False``) 2025-07-17T07:36:53.1308842Z 2025-07-17T07:36:53.1309104Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1309184Z 2025-07-17T07:36:53.1309278Z warnings.warn(msg) 2025-07-17T07:36:53.1309369Z 2025-07-17T07:36:53.1309552Z --- Parse Warning: 73 / 136 --- 2025-07-17T07:36:53.1310751Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.set_state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=637. 2025-07-17T07:36:53.1311052Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1311294Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-07-17T07:36:53.1311385Z 2025-07-17T07:36:53.1311644Z Also takes (optional) configuration for the model's and optimizer's state dict. 2025-07-17T07:36:53.1311843Z The target module does not have to be a FSDP module. If the target 2025-07-17T07:36:53.1312113Z module is a FSDP module, its ``state_dict_type`` will also be changed. 2025-07-17T07:36:53.1312190Z 2025-07-17T07:36:53.1312381Z .. note:: This API should be called for only the top-level (root) 2025-07-17T07:36:53.1312476Z module. 2025-07-17T07:36:53.1312554Z 2025-07-17T07:36:53.1312769Z .. note:: This API enables users to transparently use the conventional 2025-07-17T07:36:53.1312952Z ``state_dict`` API to take model checkpoints in cases where the 2025-07-17T07:36:53.1313153Z root FSDP module is wrapped by another ``nn.Module``. For example, 2025-07-17T07:36:53.1313371Z the following will ensure ``state_dict`` is called on all non-FSDP 2025-07-17T07:36:53.1313600Z instances, while dispatching into `sharded_state_dict` implementation 2025-07-17T07:36:53.1313688Z for FSDP: 2025-07-17T07:36:53.1313775Z 2025-07-17T07:36:53.1313861Z Example:: 2025-07-17T07:36:53.1313939Z 2025-07-17T07:36:53.1314082Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.1314185Z >>> model = DDP(FSDP(...)) 2025-07-17T07:36:53.1314304Z >>> FSDP.set_state_dict_type( 2025-07-17T07:36:53.1314392Z >>> model, 2025-07-17T07:36:53.1314521Z >>> StateDictType.SHARDED_STATE_DICT, 2025-07-17T07:36:53.1314743Z >>> state_dict_config = ShardedStateDictConfig(offload_to_cpu=True), 2025-07-17T07:36:53.1314963Z >>> optim_state_dict_config = OptimStateDictConfig(offload_to_cpu=True), 2025-07-17T07:36:53.1315047Z >>> ) 2025-07-17T07:36:53.1315181Z >>> param_state_dict = model.state_dict() 2025-07-17T07:36:53.1315347Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-07-17T07:36:53.1315424Z 2025-07-17T07:36:53.1315517Z Args: 2025-07-17T07:36:53.1315642Z module (torch.nn.Module): Root module. 2025-07-17T07:36:53.1315881Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-07-17T07:36:53.1316119Z state_dict_config (Optional[StateDictConfig]): the configuration for the 2025-07-17T07:36:53.1316230Z target ``state_dict_type``. 2025-07-17T07:36:53.1316496Z optim_state_dict_config (Optional[OptimStateDictConfig]): the configuration 2025-07-17T07:36:53.1316611Z for the optimizer state dict. 2025-07-17T07:36:53.1316688Z 2025-07-17T07:36:53.1316783Z Returns: 2025-07-17T07:36:53.1317002Z A StateDictSettings that include the previous state_dict type and 2025-07-17T07:36:53.1317157Z configuration for the module. 2025-07-17T07:36:53.1317236Z 2025-07-17T07:36:53.1317484Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1317571Z 2025-07-17T07:36:53.1317667Z warnings.warn(msg) 2025-07-17T07:36:53.1317744Z 2025-07-17T07:36:53.1317984Z --- Parse Warning: 74 / 136 --- 2025-07-17T07:36:53.1319171Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=795. 2025-07-17T07:36:53.1319468Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1319711Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-07-17T07:36:53.1319790Z 2025-07-17T07:36:53.1320118Z This context manager has the same functions as :meth:`set_state_dict_type`. Read the document of 2025-07-17T07:36:53.1320245Z :meth:`set_state_dict_type` for the detail. 2025-07-17T07:36:53.1320321Z 2025-07-17T07:36:53.1320422Z Example:: 2025-07-17T07:36:53.1320543Z 2025-07-17T07:36:53.1320675Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.1320790Z >>> model = DDP(FSDP(...)) 2025-07-17T07:36:53.1320900Z >>> with FSDP.state_dict_type( 2025-07-17T07:36:53.1321249Z >>> model, 2025-07-17T07:36:53.1321430Z >>> StateDictType.SHARDED_STATE_DICT, 2025-07-17T07:36:53.1321618Z >>> ): 2025-07-17T07:36:53.1321772Z >>> checkpoint = model.state_dict() 2025-07-17T07:36:53.1321919Z 2025-07-17T07:36:53.1322063Z Args: 2025-07-17T07:36:53.1322257Z module (torch.nn.Module): Root module. 2025-07-17T07:36:53.1322581Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-07-17T07:36:53.1322840Z state_dict_config (Optional[StateDictConfig]): the model ``state_dict`` 2025-07-17T07:36:53.1323029Z configuration for the target ``state_dict_type``. 2025-07-17T07:36:53.1323359Z optim_state_dict_config (Optional[OptimStateDictConfig]): the optimizer 2025-07-17T07:36:53.1323564Z ``state_dict`` configuration for the target ``state_dict_type``. 2025-07-17T07:36:53.1323768Z 2025-07-17T07:36:53.1324061Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1324170Z 2025-07-17T07:36:53.1324337Z warnings.warn(msg) 2025-07-17T07:36:53.1324455Z 2025-07-17T07:36:53.1324656Z --- Parse Warning: 75 / 136 --- 2025-07-17T07:36:53.1326097Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.optim_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1808. 2025-07-17T07:36:53.1326399Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1326552Z 2025-07-17T07:36:53.1326832Z Transform the state-dict of an optimizer corresponding to a sharded model. 2025-07-17T07:36:53.1326939Z 2025-07-17T07:36:53.1327219Z The given state-dict can be transformed to one of three types: 2025-07-17T07:36:53.1327565Z 1) full optimizer state_dict, 2) sharded optimizer state_dict, 3) local optimizer state_dict. 2025-07-17T07:36:53.1327702Z 2025-07-17T07:36:53.1328007Z For full optimizer state_dict, all states are unflattened and not sharded. 2025-07-17T07:36:53.1328259Z Rank0 only and CPU only can be specified via :meth:`state_dict_type` to 2025-07-17T07:36:53.1328442Z avoid OOM. 2025-07-17T07:36:53.1328586Z 2025-07-17T07:36:53.1328865Z For sharded optimizer state_dict, all states are unflattened but sharded. 2025-07-17T07:36:53.1329140Z CPU only can be specified via :meth:`state_dict_type` to further save 2025-07-17T07:36:53.1329262Z memory. 2025-07-17T07:36:53.1329372Z 2025-07-17T07:36:53.1329649Z For local state_dict, no transformation will be performed. But a state 2025-07-17T07:36:53.1329955Z will be converted from nn.Tensor to ShardedTensor to represent its sharding 2025-07-17T07:36:53.1330121Z nature (this is not supported yet). 2025-07-17T07:36:53.1330312Z 2025-07-17T07:36:53.1330433Z Example:: 2025-07-17T07:36:53.1330581Z 2025-07-17T07:36:53.1330722Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.1331020Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-07-17T07:36:53.1331274Z >>> from torch.distributed.fsdp import StateDictType 2025-07-17T07:36:53.1331483Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-07-17T07:36:53.1331712Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-07-17T07:36:53.1331882Z >>> # Save a checkpoint 2025-07-17T07:36:53.1331990Z >>> model, optim = ... 2025-07-17T07:36:53.1332312Z >>> FSDP.set_state_dict_type( 2025-07-17T07:36:53.1332429Z >>> model, 2025-07-17T07:36:53.1332578Z >>> StateDictType.FULL_STATE_DICT, 2025-07-17T07:36:53.1332779Z >>> FullStateDictConfig(rank0_only=False), 2025-07-17T07:36:53.1332953Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-07-17T07:36:53.1333045Z >>> ) 2025-07-17T07:36:53.1333287Z >>> state_dict = model.state_dict() 2025-07-17T07:36:53.1333483Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-07-17T07:36:53.1333657Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-07-17T07:36:53.1333826Z >>> # Load a checkpoint 2025-07-17T07:36:53.1333956Z >>> model, optim = ... 2025-07-17T07:36:53.1334198Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-07-17T07:36:53.1334347Z >>> FSDP.set_state_dict_type( 2025-07-17T07:36:53.1334469Z >>> model, 2025-07-17T07:36:53.1334662Z >>> StateDictType.FULL_STATE_DICT, 2025-07-17T07:36:53.1334820Z >>> FullStateDictConfig(rank0_only=False), 2025-07-17T07:36:53.1334991Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-07-17T07:36:53.1335162Z >>> ) 2025-07-17T07:36:53.1335324Z >>> model.load_state_dict(state_dict) 2025-07-17T07:36:53.1335547Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-07-17T07:36:53.1335690Z >>> model, optim, optim_state_dict 2025-07-17T07:36:53.1335799Z >>> ) 2025-07-17T07:36:53.1336007Z >>> optim.load_state_dict(optim_state_dict) 2025-07-17T07:36:53.1336143Z 2025-07-17T07:36:53.1336270Z Args: 2025-07-17T07:36:53.1336543Z model (torch.nn.Module): Root module (which may or may not be a 2025-07-17T07:36:53.1336773Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-07-17T07:36:53.1336935Z were passed into the optimizer ``optim``. 2025-07-17T07:36:53.1337178Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-07-17T07:36:53.1337334Z parameters. 2025-07-17T07:36:53.1337631Z optim_state_dict (Dict[str, Any]): the target optimizer state_dict to 2025-07-17T07:36:53.1337870Z transform. If the value is None, optim.state_dict() will be used. ( 2025-07-17T07:36:53.1337996Z Default: ``None``) 2025-07-17T07:36:53.1338313Z group (dist.ProcessGroup): Model's process group across which parameters 2025-07-17T07:36:53.1338507Z are sharded or ``None`` if using the default process group. ( 2025-07-17T07:36:53.1338671Z Default: ``None``) 2025-07-17T07:36:53.1338835Z 2025-07-17T07:36:53.1338985Z Returns: 2025-07-17T07:36:53.1339251Z Dict[str, Any]: A :class:`dict` containing the optimizer state for 2025-07-17T07:36:53.1339447Z ``model``. The sharding of the optimizer state is based on 2025-07-17T07:36:53.1339553Z ``state_dict_type``. 2025-07-17T07:36:53.1339755Z 2025-07-17T07:36:53.1340042Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1340153Z 2025-07-17T07:36:53.1340331Z warnings.warn(msg) 2025-07-17T07:36:53.1340468Z 2025-07-17T07:36:53.1340696Z --- Parse Warning: 76 / 136 --- 2025-07-17T07:36:53.1342089Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.optim_state_dict_to_load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1906. 2025-07-17T07:36:53.1342383Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1342548Z 2025-07-17T07:36:53.1342932Z Convert an optimizer state-dict so that it can be loaded into the optimizer associated with the FSDP model. 2025-07-17T07:36:53.1343041Z 2025-07-17T07:36:53.1343328Z Given a ``optim_state_dict`` that is transformed through 2025-07-17T07:36:53.1343638Z :meth:`optim_state_dict`, it gets converted to the flattened optimizer 2025-07-17T07:36:53.1343937Z state_dict that can be loaded to ``optim`` which is the optimizer for 2025-07-17T07:36:53.1344154Z ``model``. ``model`` must be sharded by FullyShardedDataParallel. 2025-07-17T07:36:53.1344264Z 2025-07-17T07:36:53.1344446Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.1344749Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-07-17T07:36:53.1344962Z >>> from torch.distributed.fsdp import StateDictType 2025-07-17T07:36:53.1345214Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-07-17T07:36:53.1345446Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-07-17T07:36:53.1345613Z >>> # Save a checkpoint 2025-07-17T07:36:53.1345719Z >>> model, optim = ... 2025-07-17T07:36:53.1345897Z >>> FSDP.set_state_dict_type( 2025-07-17T07:36:53.1346082Z >>> model, 2025-07-17T07:36:53.1346230Z >>> StateDictType.FULL_STATE_DICT, 2025-07-17T07:36:53.1346419Z >>> FullStateDictConfig(rank0_only=False), 2025-07-17T07:36:53.1346637Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-07-17T07:36:53.1346729Z >>> ) 2025-07-17T07:36:53.1346981Z >>> state_dict = model.state_dict() 2025-07-17T07:36:53.1347126Z >>> original_osd = optim.state_dict() 2025-07-17T07:36:53.1347284Z >>> optim_state_dict = FSDP.optim_state_dict( 2025-07-17T07:36:53.1347443Z >>> model, 2025-07-17T07:36:53.1347560Z >>> optim, 2025-07-17T07:36:53.1347685Z >>> optim_state_dict=original_osd 2025-07-17T07:36:53.1347893Z >>> ) 2025-07-17T07:36:53.1348065Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-07-17T07:36:53.1348191Z >>> # Load a checkpoint 2025-07-17T07:36:53.1348359Z >>> model, optim = ... 2025-07-17T07:36:53.1348546Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-07-17T07:36:53.1348740Z >>> FSDP.set_state_dict_type( 2025-07-17T07:36:53.1348871Z >>> model, 2025-07-17T07:36:53.1349017Z >>> StateDictType.FULL_STATE_DICT, 2025-07-17T07:36:53.1349214Z >>> FullStateDictConfig(rank0_only=False), 2025-07-17T07:36:53.1349389Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-07-17T07:36:53.1349500Z >>> ) 2025-07-17T07:36:53.1349703Z >>> model.load_state_dict(state_dict) 2025-07-17T07:36:53.1349896Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-07-17T07:36:53.1350040Z >>> model, optim, optim_state_dict 2025-07-17T07:36:53.1350248Z >>> ) 2025-07-17T07:36:53.1350403Z >>> optim.load_state_dict(optim_state_dict) 2025-07-17T07:36:53.1350544Z 2025-07-17T07:36:53.1350685Z Args: 2025-07-17T07:36:53.1350926Z model (torch.nn.Module): Root module (which may or may not be a 2025-07-17T07:36:53.1351201Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-07-17T07:36:53.1351362Z were passed into the optimizer ``optim``. 2025-07-17T07:36:53.1351579Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-07-17T07:36:53.1351724Z parameters. 2025-07-17T07:36:53.1352024Z optim_state_dict (Dict[str, Any]): The optimizer states to be loaded. 2025-07-17T07:36:53.1352309Z is_named_optimizer (bool): Is this optimizer a NamedOptimizer or 2025-07-17T07:36:53.1352530Z KeyedOptimizer. Only set to True if ``optim`` is TorchRec's 2025-07-17T07:36:53.1352743Z KeyedOptimizer or torch.distributed's NamedOptimizer. 2025-07-17T07:36:53.1353010Z load_directly (bool): If this is set to True, this API will also 2025-07-17T07:36:53.1353219Z call optim.load_state_dict(result) before returning the result. 2025-07-17T07:36:53.1353551Z Otherwise, users are responsible to call ``optim.load_state_dict()`` 2025-07-17T07:36:53.1353739Z (Default: ``False``) 2025-07-17T07:36:53.1354016Z group (dist.ProcessGroup): Model's process group across which parameters 2025-07-17T07:36:53.1354270Z are sharded or ``None`` if using the default process group. ( 2025-07-17T07:36:53.1354397Z Default: ``None``) 2025-07-17T07:36:53.1354485Z 2025-07-17T07:36:53.1354885Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1355001Z 2025-07-17T07:36:53.1355126Z warnings.warn(msg) 2025-07-17T07:36:53.1355275Z 2025-07-17T07:36:53.1355508Z --- Parse Warning: 77 / 136 --- 2025-07-17T07:36:53.1356617Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_RemoteModule.__init__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=129. 2025-07-17T07:36:53.1356935Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1357052Z 2025-07-17T07:36:53.1357348Z RemoteModule instance can only be created after RPC initialization. 2025-07-17T07:36:53.1357456Z 2025-07-17T07:36:53.1357676Z It creates a user-specified module on a specified remote node. 2025-07-17T07:36:53.1357994Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-07-17T07:36:53.1358151Z executed on the remote node. 2025-07-17T07:36:53.1358454Z It takes care of autograd recording to ensure the backward pass propagates 2025-07-17T07:36:53.1358638Z gradients back to the corresponding remote module. 2025-07-17T07:36:53.1359030Z It can be shared across processors using `RPC framework `__, 2025-07-17T07:36:53.1359276Z without incurring any overheads of copying the actual module, 2025-07-17T07:36:53.1359545Z which is equivalent to an :class:`~torch.distributed.rpc.RRef` 2025-07-17T07:36:53.1384479Z pointing to the remote module. 2025-07-17T07:36:53.1384558Z 2025-07-17T07:36:53.1384788Z The arguments of ``forward_async`` and ``forward`` are the same as 2025-07-17T07:36:53.1384991Z the ``forward`` method of the module returned by the ``module_cls``. 2025-07-17T07:36:53.1385073Z 2025-07-17T07:36:53.1385402Z Apart from ``forward_async`` and ``forward``, no other methods are supported from nn.Module for now. 2025-07-17T07:36:53.1385480Z 2025-07-17T07:36:53.1385730Z Particularly, to create a hybrid model, typically the local modules should be 2025-07-17T07:36:53.1386117Z created outside of remote modules, rather than as submodules of any remote module (by calling ``add_module``). 2025-07-17T07:36:53.1386333Z Hybrid Example: 2025-07-17T07:36:53.1386465Z >>> class HybridModel(nn.Module): 2025-07-17T07:36:53.1386580Z >>> def __init__(self) -> None: 2025-07-17T07:36:53.1386695Z >>> nn.Module.__init__(self) 2025-07-17T07:36:53.1386850Z >>> self.remote_embedding = RemoteModule(...) 2025-07-17T07:36:53.1386973Z >>> self.local_linear = nn.Linear(...) 2025-07-17T07:36:53.1387052Z 2025-07-17T07:36:53.1387266Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-07-17T07:36:53.1387560Z that has ``forward`` method signature, ``def forward(input: Tensor) -> Tensor:``, 2025-07-17T07:36:53.1387767Z the generated ``RemoteModule`` will have 2 methods in signature of 2025-07-17T07:36:53.1387908Z ``def forward(input: Tensor) -> Tensor:`` and 2025-07-17T07:36:53.1388068Z ``def forward_async(input: Tensor) -> Future[Tensor]:``. 2025-07-17T07:36:53.1388161Z 2025-07-17T07:36:53.1388257Z .. note:: 2025-07-17T07:36:53.1388398Z If the remote module is placed on a cuda device, 2025-07-17T07:36:53.1388644Z any input CPU tensors will be automatically moved to the same cuda device, 2025-07-17T07:36:53.1389123Z and GPU tensors are returned over the wire according to the device map of the remote worker on TensorPipe RPC backend. 2025-07-17T07:36:53.1389203Z 2025-07-17T07:36:53.1389300Z Args: 2025-07-17T07:36:53.1389594Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-07-17T07:36:53.1389895Z The device can be a local device or a remote device specified by one of the following remote 2025-07-17T07:36:53.1389981Z formats: 2025-07-17T07:36:53.1390058Z 2025-07-17T07:36:53.1390210Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-07-17T07:36:53.1390358Z 2. "/" (ex: "trainer0/cuda:0"). 2025-07-17T07:36:53.1390440Z 2025-07-17T07:36:53.1390698Z In addition, the device field can be optional and the default value is "cpu". 2025-07-17T07:36:53.1390813Z module_cls (nn.Module): For example, 2025-07-17T07:36:53.1390926Z >>> class MyModule(nn.Module): 2025-07-17T07:36:53.1391042Z >>> def forward(input): 2025-07-17T07:36:53.1391141Z >>> return input + 1 2025-07-17T07:36:53.1391235Z >>> 2025-07-17T07:36:53.1391332Z >>> module_cls = MyModule 2025-07-17T07:36:53.1391527Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-07-17T07:36:53.1391732Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-07-17T07:36:53.1392009Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-07-17T07:36:53.1392241Z to be created. The type object should be decorated by @torch.jit.interface. 2025-07-17T07:36:53.1392476Z If not provided, the generated RemoteModule is not torchscript-able. 2025-07-17T07:36:53.1392706Z Warning, this is an experimental API and susceptible to frequent changes. 2025-07-17T07:36:53.1392797Z 2025-07-17T07:36:53.1392876Z Returns: 2025-07-17T07:36:53.1393121Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-07-17T07:36:53.1393361Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-07-17T07:36:53.1393631Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-07-17T07:36:53.1393771Z on the user-provided module on the remote side. 2025-07-17T07:36:53.1393864Z 2025-07-17T07:36:53.1393948Z Example:: 2025-07-17T07:36:53.1394097Z Run the following code in two different processes: 2025-07-17T07:36:53.1394191Z 2025-07-17T07:36:53.1394304Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:53.1394434Z >>> # On worker 0: 2025-07-17T07:36:53.1394523Z >>> import torch 2025-07-17T07:36:53.1394648Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:53.1394763Z >>> from torch import nn, Tensor 2025-07-17T07:36:53.1394984Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-07-17T07:36:53.1395063Z >>> 2025-07-17T07:36:53.1395213Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-07-17T07:36:53.1395332Z >>> remote_linear_module = RemoteModule( 2025-07-17T07:36:53.1395458Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-07-17T07:36:53.1395576Z >>> ) 2025-07-17T07:36:53.1395680Z >>> input = torch.randn(128, 20) 2025-07-17T07:36:53.1395833Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-07-17T07:36:53.1395943Z >>> ret = ret_fut.wait() 2025-07-17T07:36:53.1396039Z >>> rpc.shutdown() 2025-07-17T07:36:53.1396130Z 2025-07-17T07:36:53.1396221Z >>> # On worker 1: 2025-07-17T07:36:53.1396308Z >>> import torch 2025-07-17T07:36:53.1396446Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:53.1396525Z >>> 2025-07-17T07:36:53.1396659Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-07-17T07:36:53.1396811Z >>> rpc.shutdown() 2025-07-17T07:36:53.1396888Z 2025-07-17T07:36:53.1397143Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1397233Z 2025-07-17T07:36:53.1397328Z warnings.warn(msg) 2025-07-17T07:36:53.1397407Z 2025-07-17T07:36:53.1397656Z --- Parse Warning: 78 / 136 --- 2025-07-17T07:36:53.1398740Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_RemoteModule.init_from_module_rref in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=506. 2025-07-17T07:36:53.1399020Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1399096Z 2025-07-17T07:36:53.1399421Z Besides the constructor, a RemoteModule instance can also be initialized given a module RRef. 2025-07-17T07:36:53.1399517Z 2025-07-17T07:36:53.1399874Z This alternate initialization method can be particularly useful if we want to create multiple 2025-07-17T07:36:53.1400203Z RemoteModule instances that share the same underlying module and reduce memory consumption. 2025-07-17T07:36:53.1400279Z 2025-07-17T07:36:53.1400553Z Moreover, this also provides a workaround for passing script RemoteModule over RPC, 2025-07-17T07:36:53.1400745Z which is not supported. The recommended way is as follows: 2025-07-17T07:36:53.1400821Z 2025-07-17T07:36:53.1400938Z 1. the sender creates a RemoteModule; 2025-07-17T07:36:53.1401089Z 2. the sender sends its ``module_rref`` over RPC; 2025-07-17T07:36:53.1401423Z 3. the receiver calls this method to initialize another RemoteModule using the same ``module_rref``. 2025-07-17T07:36:53.1401503Z 2025-07-17T07:36:53.1401602Z Example:: 2025-07-17T07:36:53.1401752Z Run the following code in two different processes: 2025-07-17T07:36:53.1401841Z 2025-07-17T07:36:53.1401958Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:53.1402048Z >>> # On worker 0: 2025-07-17T07:36:53.1402150Z >>> import torch 2025-07-17T07:36:53.1402274Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:53.1402379Z >>> from torch import nn, Tensor 2025-07-17T07:36:53.1402611Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-07-17T07:36:53.1402695Z >>> 2025-07-17T07:36:53.1402830Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-07-17T07:36:53.1402953Z >>> remote_module = RemoteModule( 2025-07-17T07:36:53.1403078Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-07-17T07:36:53.1403199Z >>> ) 2025-07-17T07:36:53.1403277Z >>> 2025-07-17T07:36:53.1403388Z >>> remote_module1 = rpc.rpc_sync( 2025-07-17T07:36:53.1403497Z >>> "worker1/cpu", 2025-07-17T07:36:53.1403620Z >>> RemoteModule.init_from_module_rref, 2025-07-17T07:36:53.1403774Z >>> ("worker1/cpu", remote_module1.get_module_rref()), 2025-07-17T07:36:53.1403866Z >>> ) 2025-07-17T07:36:53.1403960Z >>> rpc.shutdown() 2025-07-17T07:36:53.1404039Z 2025-07-17T07:36:53.1404140Z >>> # On worker 1: 2025-07-17T07:36:53.1404229Z >>> import torch 2025-07-17T07:36:53.1404381Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:53.1404474Z >>> 2025-07-17T07:36:53.1404607Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-07-17T07:36:53.1404712Z >>> rpc.shutdown() 2025-07-17T07:36:53.1404788Z 2025-07-17T07:36:53.1404872Z Args: 2025-07-17T07:36:53.1405180Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-07-17T07:36:53.1405545Z The device can be a local device or a remote device specified by one of the following remote 2025-07-17T07:36:53.1405632Z formats: 2025-07-17T07:36:53.1405723Z 2025-07-17T07:36:53.1405917Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-07-17T07:36:53.1406072Z 2. "/" (ex: "trainer0/cuda:0"). 2025-07-17T07:36:53.1406216Z 2025-07-17T07:36:53.1406460Z In addition, the device field can be optional and the default value is "cpu". 2025-07-17T07:36:53.1406721Z module_rref (RRef[nn.Module]): The module reference shared by both the caller and 2025-07-17T07:36:53.1406825Z the created remote module. 2025-07-17T07:36:53.1407102Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-07-17T07:36:53.1407343Z to be created. The type object should be decorated by @torch.jit.interface. 2025-07-17T07:36:53.1407559Z If not provided, the generated RemoteModule is not torchscript-able. 2025-07-17T07:36:53.1407788Z Warning, this is an experimental API and susceptible to frequent changes. 2025-07-17T07:36:53.1407876Z 2025-07-17T07:36:53.1407957Z Returns: 2025-07-17T07:36:53.1408200Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-07-17T07:36:53.1408443Z user-provided ``module_rref``, it has a blocking ``forward`` method and an 2025-07-17T07:36:53.1408711Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-07-17T07:36:53.1408868Z on the user-provided module on the remote side. 2025-07-17T07:36:53.1408946Z 2025-07-17T07:36:53.1409195Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1409287Z 2025-07-17T07:36:53.1409381Z warnings.warn(msg) 2025-07-17T07:36:53.1409460Z 2025-07-17T07:36:53.1409673Z --- Parse Warning: 79 / 136 --- 2025-07-17T07:36:53.1410662Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RemoteModule in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=598. 2025-07-17T07:36:53.1410940Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1411016Z 2025-07-17T07:36:53.1411242Z A RemoteModule instance can only be created after RPC initialization. 2025-07-17T07:36:53.1411334Z 2025-07-17T07:36:53.1411529Z It creates a user-specified module on a specified remote node. 2025-07-17T07:36:53.1411762Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-07-17T07:36:53.1411880Z executed on the remote node. 2025-07-17T07:36:53.1412114Z It takes care of autograd recording to ensure the backward pass propagates 2025-07-17T07:36:53.1412310Z gradients back to the corresponding remote module. 2025-07-17T07:36:53.1412388Z 2025-07-17T07:36:53.1412605Z It generates two methods ``forward_async`` and ``forward`` based on the 2025-07-17T07:36:53.1412832Z signature of the ``forward`` method of ``module_cls``. ``forward_async`` 2025-07-17T07:36:53.1413081Z runs asynchronously and returns a Future. The arguments of ``forward_async`` 2025-07-17T07:36:53.1413275Z and ``forward`` are the same as the ``forward`` method of the module 2025-07-17T07:36:53.1413397Z returned by the ``module_cls``. 2025-07-17T07:36:53.1413498Z 2025-07-17T07:36:53.1413697Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-07-17T07:36:53.1413958Z that has ``forward`` method signature: ``def forward(input: Tensor) -> Tensor:``, 2025-07-17T07:36:53.1414181Z the generated ``RemoteModule`` will have 2 methods with the signatures: 2025-07-17T07:36:53.1414275Z 2025-07-17T07:36:53.1414397Z | ``def forward(input: Tensor) -> Tensor:`` 2025-07-17T07:36:53.1414560Z | ``def forward_async(input: Tensor) -> Future[Tensor]:`` 2025-07-17T07:36:53.1414651Z 2025-07-17T07:36:53.1414731Z Args: 2025-07-17T07:36:53.1415089Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-07-17T07:36:53.1415447Z The format should be "/", where the device field can be parsed as torch.device type. 2025-07-17T07:36:53.1415585Z E.g., "trainer0/cpu", "trainer0", "ps0/cuda:0". 2025-07-17T07:36:53.1415842Z In addition, the device field can be optional and the default value is "cpu". 2025-07-17T07:36:53.1416085Z module_cls (nn.Module): Class for the module to be created remotely. For example, 2025-07-17T07:36:53.1416164Z 2025-07-17T07:36:53.1416286Z >>> class MyModule(nn.Module): 2025-07-17T07:36:53.1416387Z >>> def forward(input): 2025-07-17T07:36:53.1416487Z >>> return input + 1 2025-07-17T07:36:53.1416581Z >>> 2025-07-17T07:36:53.1416681Z >>> module_cls = MyModule 2025-07-17T07:36:53.1416756Z 2025-07-17T07:36:53.1416967Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-07-17T07:36:53.1417160Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-07-17T07:36:53.1417251Z 2025-07-17T07:36:53.1417332Z Returns: 2025-07-17T07:36:53.1417573Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-07-17T07:36:53.1417814Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-07-17T07:36:53.1418083Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-07-17T07:36:53.1418225Z on the user-provided module on the remote side. 2025-07-17T07:36:53.1418316Z 2025-07-17T07:36:53.1418404Z Example:: 2025-07-17T07:36:53.1418556Z Run the following code in two different processes: 2025-07-17T07:36:53.1418644Z 2025-07-17T07:36:53.1418759Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:53.1418862Z >>> # On worker 0: 2025-07-17T07:36:53.1418950Z >>> import torch 2025-07-17T07:36:53.1419076Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:53.1419194Z >>> from torch import nn, Tensor 2025-07-17T07:36:53.1419412Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-07-17T07:36:53.1419490Z >>> 2025-07-17T07:36:53.1419640Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-07-17T07:36:53.1419764Z >>> remote_linear_module = RemoteModule( 2025-07-17T07:36:53.1419886Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-07-17T07:36:53.1419979Z >>> ) 2025-07-17T07:36:53.1420084Z >>> input = torch.randn(128, 20) 2025-07-17T07:36:53.1420250Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-07-17T07:36:53.1420377Z >>> ret = ret_fut.wait() 2025-07-17T07:36:53.1420470Z >>> rpc.shutdown() 2025-07-17T07:36:53.1420562Z 2025-07-17T07:36:53.1420711Z >>> # On worker 1: 2025-07-17T07:36:53.1420799Z >>> import torch 2025-07-17T07:36:53.1420939Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:53.1421018Z >>> 2025-07-17T07:36:53.1421152Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-07-17T07:36:53.1421262Z >>> rpc.shutdown() 2025-07-17T07:36:53.1421337Z 2025-07-17T07:36:53.1421528Z Furthermore, a more practical example that is combined with 2025-07-17T07:36:53.1422054Z `DistributedDataParallel `__ (DDP) 2025-07-17T07:36:53.1422380Z can be found in this `tutorial `__. 2025-07-17T07:36:53.1422472Z 2025-07-17T07:36:53.1422727Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1422803Z 2025-07-17T07:36:53.1422909Z warnings.warn(msg) 2025-07-17T07:36:53.1422985Z 2025-07-17T07:36:53.1423174Z --- Parse Warning: 80 / 136 --- 2025-07-17T07:36:53.1424245Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/optimizer.py line=129. 2025-07-17T07:36:53.1424506Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1424598Z 2025-07-17T07:36:53.1424837Z DistributedOptimizer takes remote references to parameters scattered 2025-07-17T07:36:53.1425072Z across workers and applies the given optimizer locally for each parameter. 2025-07-17T07:36:53.1425160Z 2025-07-17T07:36:53.1425391Z This class uses :meth:`~torch.distributed.autograd.get_gradients` in order 2025-07-17T07:36:53.1425544Z to retrieve the gradients for specific parameters. 2025-07-17T07:36:53.1425633Z 2025-07-17T07:36:53.1425726Z Concurrent calls to 2025-07-17T07:36:53.1425933Z :meth:`~torch.distributed.optim.DistributedOptimizer.step`, 2025-07-17T07:36:53.1426088Z either from the same or different clients, will 2025-07-17T07:36:53.1426310Z be serialized on each worker -- as each worker's optimizer can only work 2025-07-17T07:36:53.1426526Z on one set of gradients at a time. However, there is no guarantee that 2025-07-17T07:36:53.1426767Z the full forward-backward-optimizer sequence will execute for one client 2025-07-17T07:36:53.1426981Z at a time. This means that the gradients being applied may not correspond 2025-07-17T07:36:53.1427213Z to the latest forward pass executed on a given worker. Also, there is no 2025-07-17T07:36:53.1427326Z guaranteed ordering across workers. 2025-07-17T07:36:53.1427404Z 2025-07-17T07:36:53.1427679Z `DistributedOptimizer` creates the local optimizer with TorchScript enabled 2025-07-17T07:36:53.1427905Z by default, so that optimizer updates are not blocked by the Python Global 2025-07-17T07:36:53.1428159Z Interpreter Lock (GIL) in the case of multithreaded training (e.g. Distributed 2025-07-17T07:36:53.1428398Z Model Parallel). This feature is currently enabled for most optimizers. You 2025-07-17T07:36:53.1428649Z can also follow `the recipe`__ in PyTorch tutorials to enable TorchScript support 2025-07-17T07:36:53.1428768Z for your own custom optimizers. 2025-07-17T07:36:53.1428845Z 2025-07-17T07:36:53.1428928Z Args: 2025-07-17T07:36:53.1429140Z optimizer_class (optim.Optimizer): the class of optimizer to 2025-07-17T07:36:53.1429247Z instantiate on each worker. 2025-07-17T07:36:53.1429463Z params_rref (list[RRef]): list of RRefs to local or remote parameters 2025-07-17T07:36:53.1429552Z to optimize. 2025-07-17T07:36:53.1429792Z args: arguments to pass to the optimizer constructor on each worker. 2025-07-17T07:36:53.1430024Z kwargs: arguments to pass to the optimizer constructor on each worker. 2025-07-17T07:36:53.1430100Z 2025-07-17T07:36:53.1430187Z Example:: 2025-07-17T07:36:53.1430314Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:53.1430476Z >>> import torch.distributed.autograd as dist_autograd 2025-07-17T07:36:53.1430603Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:53.1430724Z >>> from torch import optim 2025-07-17T07:36:53.1430906Z >>> from torch.distributed.optim import DistributedOptimizer 2025-07-17T07:36:53.1431010Z >>> 2025-07-17T07:36:53.1431154Z >>> with dist_autograd.context() as context_id: 2025-07-17T07:36:53.1431247Z >>> # Forward pass. 2025-07-17T07:36:53.1431455Z >>> rref1 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 3)) 2025-07-17T07:36:53.1431646Z >>> rref2 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 1)) 2025-07-17T07:36:53.1431784Z >>> loss = rref1.to_here() + rref2.to_here() 2025-07-17T07:36:53.1431876Z >>> 2025-07-17T07:36:53.1431971Z >>> # Backward pass. 2025-07-17T07:36:53.1432116Z >>> dist_autograd.backward(context_id, [loss.sum()]) 2025-07-17T07:36:53.1432260Z >>> 2025-07-17T07:36:53.1432350Z >>> # Optimizer. 2025-07-17T07:36:53.1432473Z >>> dist_optim = DistributedOptimizer( 2025-07-17T07:36:53.1432573Z >>> optim.SGD, 2025-07-17T07:36:53.1432663Z >>> [rref1, rref2], 2025-07-17T07:36:53.1432761Z >>> lr=0.05, 2025-07-17T07:36:53.1432841Z >>> ) 2025-07-17T07:36:53.1432947Z >>> dist_optim.step(context_id) 2025-07-17T07:36:53.1433036Z 2025-07-17T07:36:53.1433187Z __ https://github.com/pytorch/tutorials/pull/1465 2025-07-17T07:36:53.1433264Z 2025-07-17T07:36:53.1433526Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1433603Z 2025-07-17T07:36:53.1433694Z warnings.warn(msg) 2025-07-17T07:36:53.1433782Z 2025-07-17T07:36:53.1433966Z --- Parse Warning: 81 / 136 --- 2025-07-17T07:36:53.1435043Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PostLocalSGDOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/post_localSGD_optimizer.py line=9. 2025-07-17T07:36:53.1435314Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1435390Z 2025-07-17T07:36:53.1435786Z Wraps an arbitrary :class:`torch.optim.Optimizer` and runs `post-local SGD `_, 2025-07-17T07:36:53.1435935Z This optimizer runs local optimizer at every step. 2025-07-17T07:36:53.1436268Z After the warm-up stage, it averages parameters periodically after the local optimizer is applied. 2025-07-17T07:36:53.1436358Z 2025-07-17T07:36:53.1436436Z Args: 2025-07-17T07:36:53.1436539Z optim: The local optimizer. 2025-07-17T07:36:53.1436770Z averager: A model averager instance to run post-localSGD algorithm. 2025-07-17T07:36:53.1436847Z 2025-07-17T07:36:53.1436943Z Example:: 2025-07-17T07:36:53.1437024Z 2025-07-17T07:36:53.1437151Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.1437252Z >>> import torch 2025-07-17T07:36:53.1437369Z >>> import torch.distributed as dist 2025-07-17T07:36:53.1437640Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-07-17T07:36:53.1437756Z >>> import torch.nn as nn 2025-07-17T07:36:53.1437945Z >>> from torch.distributed.optim import PostLocalSGDOptimizer 2025-07-17T07:36:53.1438216Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-07-17T07:36:53.1438328Z >>> PostLocalSGDState, 2025-07-17T07:36:53.1438456Z >>> post_localSGD_hook, 2025-07-17T07:36:53.1438543Z >>> ) 2025-07-17T07:36:53.1438622Z >>> 2025-07-17T07:36:53.1438771Z >>> model = nn.parallel.DistributedDataParallel( 2025-07-17T07:36:53.1438921Z >>> module, device_ids=[rank], output_device=rank 2025-07-17T07:36:53.1439002Z >>> ) 2025-07-17T07:36:53.1439079Z >>> 2025-07-17T07:36:53.1439232Z >>> # Register a post-localSGD communication hook. 2025-07-17T07:36:53.1439525Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-07-17T07:36:53.1439710Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-07-17T07:36:53.1439802Z >>> 2025-07-17T07:36:53.1440003Z >>> # Create a post-localSGD optimizer that wraps a local optimizer. 2025-07-17T07:36:53.1440261Z >>> # Note that ``warmup_steps`` used in ``PostLocalSGDOptimizer`` must be the same as 2025-07-17T07:36:53.1440428Z >>> # ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-07-17T07:36:53.1440639Z >>> local_optim = torch.optim.SGD(params=model.parameters(), lr=0.01) 2025-07-17T07:36:53.1440767Z >>> opt = PostLocalSGDOptimizer( 2025-07-17T07:36:53.1440863Z >>> optim=local_optim, 2025-07-17T07:36:53.1441157Z >>> averager=averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-07-17T07:36:53.1441249Z >>> ) 2025-07-17T07:36:53.1441328Z >>> 2025-07-17T07:36:53.1441547Z >>> # In the first 100 steps, DDP runs global gradient averaging at every step. 2025-07-17T07:36:53.1441858Z >>> # After 100 steps, DDP runs gradient averaging within each subgroup (intra-node by default), 2025-07-17T07:36:53.1442235Z >>> # and post-localSGD optimizer runs global model averaging every 4 steps after applying the local optimizer. 2025-07-17T07:36:53.1442349Z >>> for step in range(0, 200): 2025-07-17T07:36:53.1442443Z >>> opt.zero_grad() 2025-07-17T07:36:53.1442552Z >>> loss = loss_fn(output, labels) 2025-07-17T07:36:53.1442658Z >>> loss.backward() 2025-07-17T07:36:53.1442745Z >>> opt.step() 2025-07-17T07:36:53.1442823Z 2025-07-17T07:36:53.1443087Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1443169Z 2025-07-17T07:36:53.1443274Z warnings.warn(msg) 2025-07-17T07:36:53.1443392Z 2025-07-17T07:36:53.1443577Z --- Parse Warning: 82 / 136 --- 2025-07-17T07:36:53.1444700Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ZeroRedundancyOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/zero_redundancy_optimizer.py line=284. 2025-07-17T07:36:53.1444961Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1445037Z 2025-07-17T07:36:53.1445531Z Wrap an arbitrary :class:`optim.Optimizer ` and shards its states across ranks in the group. 2025-07-17T07:36:53.1445613Z 2025-07-17T07:36:53.1445868Z The sharing is done as described by `ZeRO `_. 2025-07-17T07:36:53.1445948Z 2025-07-17T07:36:53.1446095Z The local optimizer instance in each rank is only 2025-07-17T07:36:53.1446353Z responsible for updating approximately ``1 / world_size`` parameters and 2025-07-17T07:36:53.1446549Z hence only needs to keep ``1 / world_size`` optimizer states. After 2025-07-17T07:36:53.1446791Z parameters are updated locally, each rank will broadcast its parameters to 2025-07-17T07:36:53.1446987Z all other peers to keep all model replicas in the same state. 2025-07-17T07:36:53.1447179Z ``ZeroRedundancyOptimizer`` can be used in conjunction with 2025-07-17T07:36:53.1447446Z :class:`torch.nn.parallel.DistributedDataParallel` to reduce per-rank peak 2025-07-17T07:36:53.1447548Z memory consumption. 2025-07-17T07:36:53.1447661Z 2025-07-17T07:36:53.1447926Z ``ZeroRedundancyOptimizer`` uses a sorted-greedy algorithm to pack a number 2025-07-17T07:36:53.1448156Z of parameters at each rank. Each parameter belongs to a single rank and is 2025-07-17T07:36:53.1448407Z not divided among ranks. The partition is arbitrary and might not match the 2025-07-17T07:36:53.1448532Z the parameter registration or usage order. 2025-07-17T07:36:53.1448610Z 2025-07-17T07:36:53.1448703Z Arguments: 2025-07-17T07:36:53.1448893Z params (``Iterable``): an ``Iterable`` of :class:`torch.Tensor` s 2025-07-17T07:36:53.1449112Z or :class:`dict` s giving all parameters, which will be sharded 2025-07-17T07:36:53.1449208Z across ranks. 2025-07-17T07:36:53.1449284Z 2025-07-17T07:36:53.1449369Z Keyword Args: 2025-07-17T07:36:53.1449593Z optimizer_class (:class:`torch.nn.Optimizer`): the class of the local 2025-07-17T07:36:53.1449678Z optimizer. 2025-07-17T07:36:53.1449900Z process_group (``ProcessGroup``, optional): ``torch.distributed`` 2025-07-17T07:36:53.1450094Z ``ProcessGroup`` (default: ``dist.group.WORLD`` initialized by 2025-07-17T07:36:53.1450240Z :meth:`torch.distributed.init_process_group`). 2025-07-17T07:36:53.1450525Z parameters_as_bucket_view (bool, optional): if ``True``, parameters are 2025-07-17T07:36:53.1450736Z packed into buckets to speed up communication, and ``param.data`` 2025-07-17T07:36:53.1450932Z fields point to bucket views at different offsets; if ``False``, 2025-07-17T07:36:53.1451141Z each individual parameter is communicated separately, and each 2025-07-17T07:36:53.1451286Z ``params.data`` stays intact (default: ``False``). 2025-07-17T07:36:53.1451487Z overlap_with_ddp (bool, optional): if ``True``, :meth:`step` is 2025-07-17T07:36:53.1451684Z overlapped with :class:`DistributedDataParallel` 's gradient 2025-07-17T07:36:53.1451896Z synchronization; this requires (1) either a functional optimizer 2025-07-17T07:36:53.1452084Z for the ``optimizer_class`` argument or one with a functional 2025-07-17T07:36:53.1452256Z equivalent and (2) registering a DDP communication hook 2025-07-17T07:36:53.1452457Z constructed from one of the functions in ``ddp_zero_hook.py``; 2025-07-17T07:36:53.1452633Z parameters are packed into buckets matching those in 2025-07-17T07:36:53.1452785Z :class:`DistributedDataParallel`, meaning that the 2025-07-17T07:36:53.1452942Z ``parameters_as_bucket_view`` argument is ignored. 2025-07-17T07:36:53.1453127Z If ``False``, :meth:`step` runs disjointly after the backward pass 2025-07-17T07:36:53.1453217Z (per normal). 2025-07-17T07:36:53.1453325Z (default: ``False``) 2025-07-17T07:36:53.1453532Z **defaults: any trailing arguments, which are forwarded to the local 2025-07-17T07:36:53.1453620Z optimizer. 2025-07-17T07:36:53.1453712Z 2025-07-17T07:36:53.1453798Z Example:: 2025-07-17T07:36:53.1453873Z 2025-07-17T07:36:53.1453980Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1454079Z >>> import torch.nn as nn 2025-07-17T07:36:53.1454282Z >>> from torch.distributed.optim import ZeroRedundancyOptimizer 2025-07-17T07:36:53.1454489Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-07-17T07:36:53.1454716Z >>> model = nn.Sequential(*[nn.Linear(2000, 2000).to(rank) for _ in range(20)]) 2025-07-17T07:36:53.1454840Z >>> ddp = DDP(model, device_ids=[rank]) 2025-07-17T07:36:53.1454961Z >>> opt = ZeroRedundancyOptimizer( 2025-07-17T07:36:53.1455059Z >>> ddp.parameters(), 2025-07-17T07:36:53.1455185Z >>> optimizer_class=torch.optim.Adam, 2025-07-17T07:36:53.1455266Z >>> lr=0.01 2025-07-17T07:36:53.1455343Z >>> ) 2025-07-17T07:36:53.1455457Z >>> ddp(inputs).sum().backward() 2025-07-17T07:36:53.1455570Z >>> opt.step() 2025-07-17T07:36:53.1455644Z 2025-07-17T07:36:53.1455737Z .. warning:: 2025-07-17T07:36:53.1455942Z Currently, ``ZeroRedundancyOptimizer`` requires that all of the 2025-07-17T07:36:53.1456091Z passed-in parameters are the same dense type. 2025-07-17T07:36:53.1456168Z 2025-07-17T07:36:53.1456250Z .. warning:: 2025-07-17T07:36:53.1456462Z If you pass ``overlap_with_ddp=True``, be wary of the following: Given 2025-07-17T07:36:53.1456656Z the way that overlapping :class:`DistributedDataParallel` with 2025-07-17T07:36:53.1456910Z :class:`ZeroRedundancyOptimizer` is currently implemented, the first 2025-07-17T07:36:53.1457132Z two or three training iterations do not perform parameter updates in 2025-07-17T07:36:53.1457316Z the optimizer step, depending on if ``static_graph=False`` or 2025-07-17T07:36:53.1457505Z ``static_graph=True``, respectively. This is because it needs 2025-07-17T07:36:53.1457686Z information about the gradient bucketing strategy used by 2025-07-17T07:36:53.1457901Z :class:`DistributedDataParallel`, which is not finalized until the 2025-07-17T07:36:53.1458100Z second forward pass if ``static_graph=False`` or until the third 2025-07-17T07:36:53.1458351Z forward pass if ``static_graph=True``. To adjust for this, one option 2025-07-17T07:36:53.1458458Z is to prepend dummy inputs. 2025-07-17T07:36:53.1458545Z 2025-07-17T07:36:53.1458795Z .. warning:: ZeroRedundancyOptimizer is experimental and subject to change. 2025-07-17T07:36:53.1458888Z 2025-07-17T07:36:53.1459138Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1459214Z 2025-07-17T07:36:53.1459315Z warnings.warn(msg) 2025-07-17T07:36:53.1459387Z 2025-07-17T07:36:53.1459584Z --- Parse Warning: 83 / 136 --- 2025-07-17T07:36:53.1460589Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_CustomReducer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py line=29. 2025-07-17T07:36:53.1460850Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1460929Z 2025-07-17T07:36:53.1461163Z Custom reducer class that can be used to specify a custom operation that 2025-07-17T07:36:53.1461332Z reduces losses of multiple microbatches into one value. 2025-07-17T07:36:53.1461420Z 2025-07-17T07:36:53.1461497Z Example: 2025-07-17T07:36:53.1461592Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1461710Z >>> sum_reducer = _CustomReducer( 2025-07-17T07:36:53.1461804Z >>> torch.tensor(0.0), 2025-07-17T07:36:53.1461896Z >>> lambda a, b: a + b 2025-07-17T07:36:53.1461982Z >>> ) 2025-07-17T07:36:53.1462056Z 2025-07-17T07:36:53.1462306Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1462391Z 2025-07-17T07:36:53.1462483Z warnings.warn(msg) 2025-07-17T07:36:53.1462558Z 2025-07-17T07:36:53.1462741Z --- Parse Warning: 84 / 136 --- 2025-07-17T07:36:53.1463676Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=async_execution in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/functions.py line=6. 2025-07-17T07:36:53.1463946Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1464022Z 2025-07-17T07:36:53.1464260Z A decorator for a function indicating that the return value of the function 2025-07-17T07:36:53.1464476Z is guaranteed to be a :class:`~torch.futures.Future` object and this 2025-07-17T07:36:53.1464716Z function can run asynchronously on the RPC callee. More specifically, the 2025-07-17T07:36:53.1464960Z callee extracts the :class:`~torch.futures.Future` returned by the wrapped 2025-07-17T07:36:53.1465218Z function and installs subsequent processing steps as a callback to that 2025-07-17T07:36:53.1465448Z :class:`~torch.futures.Future`. The installed callback will read the value 2025-07-17T07:36:53.1465661Z from the :class:`~torch.futures.Future` when completed and send the 2025-07-17T07:36:53.1465836Z value back as the RPC response. That also means the returned 2025-07-17T07:36:53.1466061Z :class:`~torch.futures.Future` only exists on the callee side and is never 2025-07-17T07:36:53.1466287Z sent through RPC. This decorator is useful when the wrapped function's 2025-07-17T07:36:53.1466506Z (``fn``) execution needs to pause and resume due to, e.g., containing 2025-07-17T07:36:53.1466742Z :meth:`~torch.distributed.rpc.rpc_async` or waiting for other signals. 2025-07-17T07:36:53.1466818Z 2025-07-17T07:36:53.1467027Z .. note:: To enable asynchronous execution, applications must pass the 2025-07-17T07:36:53.1467270Z function object returned by this decorator to RPC APIs. If RPC detected 2025-07-17T07:36:53.1467481Z attributes installed by this decorator, it knows that this function 2025-07-17T07:36:53.1467661Z returns a ``Future`` object and will handle that accordingly. 2025-07-17T07:36:53.1467928Z However, this does not mean this decorator has to be outmost one when 2025-07-17T07:36:53.1468152Z defining a function. For example, when combined with ``@staticmethod`` 2025-07-17T07:36:53.1468369Z or ``@classmethod``, ``@rpc.functions.async_execution`` needs to be the 2025-07-17T07:36:53.1468585Z inner decorator to allow the target function be recognized as a static 2025-07-17T07:36:53.1468809Z or class function. This target function can still execute asynchronously 2025-07-17T07:36:53.1469042Z because, when accessed, the static or class method preserves attributes 2025-07-17T07:36:53.1469193Z installed by ``@rpc.functions.async_execution``. 2025-07-17T07:36:53.1469270Z 2025-07-17T07:36:53.1469357Z 2025-07-17T07:36:53.1469441Z Example:: 2025-07-17T07:36:53.1469639Z The returned :class:`~torch.futures.Future` object can come from 2025-07-17T07:36:53.1469781Z :meth:`~torch.distributed.rpc.rpc_async`, 2025-07-17T07:36:53.1470269Z :meth:`~torch.futures.Future.then`, or :class:`~torch.futures.Future` 2025-07-17T07:36:53.1470462Z constructor. The example below shows directly using the 2025-07-17T07:36:53.1470590Z :class:`~torch.futures.Future` returned by 2025-07-17T07:36:53.1470708Z :meth:`~torch.futures.Future.then`. 2025-07-17T07:36:53.1470798Z 2025-07-17T07:36:53.1470913Z >>> from torch.distributed import rpc 2025-07-17T07:36:53.1470990Z >>> 2025-07-17T07:36:53.1471113Z >>> # omitting setup and shutdown RPC 2025-07-17T07:36:53.1471191Z >>> 2025-07-17T07:36:53.1471282Z >>> # On all workers 2025-07-17T07:36:53.1471404Z >>> @rpc.functions.async_execution 2025-07-17T07:36:53.1471513Z >>> def async_add_chained(to, x, y, z): 2025-07-17T07:36:53.1471714Z >>> # This function runs on "worker1" and returns immediately when 2025-07-17T07:36:53.1471894Z >>> # the callback is installed through the `then(cb)` API. In the 2025-07-17T07:36:53.1472075Z >>> # mean time, the `rpc_async` to "worker2" can run concurrently. 2025-07-17T07:36:53.1472239Z >>> # When the return value of that `rpc_async` arrives at 2025-07-17T07:36:53.1472420Z >>> # "worker1", "worker1" will run the lambda function accordingly 2025-07-17T07:36:53.1472603Z >>> # and set the value for the previously returned `Future`, which 2025-07-17T07:36:53.1472789Z >>> # will then trigger RPC to send the result back to "worker0". 2025-07-17T07:36:53.1472950Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-07-17T07:36:53.1473069Z >>> lambda fut: fut.wait() + z 2025-07-17T07:36:53.1473229Z >>> ) 2025-07-17T07:36:53.1473309Z >>> 2025-07-17T07:36:53.1473406Z >>> # On worker0 2025-07-17T07:36:53.1473501Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1473598Z >>> ret = rpc.rpc_sync( 2025-07-17T07:36:53.1473697Z >>> "worker1", 2025-07-17T07:36:53.1473792Z >>> async_add_chained, 2025-07-17T07:36:53.1473910Z >>> args=("worker2", torch.ones(2), 1, 1) 2025-07-17T07:36:53.1473998Z >>> ) 2025-07-17T07:36:53.1474110Z >>> print(ret) # prints tensor([3., 3.]) 2025-07-17T07:36:53.1474234Z 2025-07-17T07:36:53.1474456Z When combined with TorchScript decorators, this decorator must be the 2025-07-17T07:36:53.1474538Z outmost one. 2025-07-17T07:36:53.1474623Z 2025-07-17T07:36:53.1474718Z >>> from torch import Tensor 2025-07-17T07:36:53.1474830Z >>> from torch.futures import Future 2025-07-17T07:36:53.1474957Z >>> from torch.distributed import rpc 2025-07-17T07:36:53.1475037Z >>> 2025-07-17T07:36:53.1475148Z >>> # omitting setup and shutdown RPC 2025-07-17T07:36:53.1475238Z >>> 2025-07-17T07:36:53.1475328Z >>> # On all workers 2025-07-17T07:36:53.1475423Z >>> @torch.jit.script 2025-07-17T07:36:53.1475639Z >>> def script_add(x: Tensor, y: Tensor) -> Tensor: 2025-07-17T07:36:53.1475730Z >>> return x + y 2025-07-17T07:36:53.1475819Z >>> 2025-07-17T07:36:53.1475931Z >>> @rpc.functions.async_execution 2025-07-17T07:36:53.1476025Z >>> @torch.jit.script 2025-07-17T07:36:53.1476216Z >>> def async_add(to: str, x: Tensor, y: Tensor) -> Future[Tensor]: 2025-07-17T07:36:53.1476351Z >>> return rpc.rpc_async(to, script_add, (x, y)) 2025-07-17T07:36:53.1476429Z >>> 2025-07-17T07:36:53.1476521Z >>> # On worker0 2025-07-17T07:36:53.1476612Z >>> ret = rpc.rpc_sync( 2025-07-17T07:36:53.1476700Z >>> "worker1", 2025-07-17T07:36:53.1476795Z >>> async_add, 2025-07-17T07:36:53.1476910Z >>> args=("worker2", torch.ones(2), 1) 2025-07-17T07:36:53.1476988Z >>> ) 2025-07-17T07:36:53.1477112Z >>> print(ret) # prints tensor([2., 2.]) 2025-07-17T07:36:53.1477188Z 2025-07-17T07:36:53.1477415Z When combined with static or class method, this decorator must be the 2025-07-17T07:36:53.1477496Z inner one. 2025-07-17T07:36:53.1477573Z 2025-07-17T07:36:53.1477703Z >>> from torch.distributed import rpc 2025-07-17T07:36:53.1477782Z >>> 2025-07-17T07:36:53.1477896Z >>> # omitting setup and shutdown RPC 2025-07-17T07:36:53.1477984Z >>> 2025-07-17T07:36:53.1478074Z >>> # On all workers 2025-07-17T07:36:53.1478184Z >>> class AsyncExecutionClass: 2025-07-17T07:36:53.1478271Z >>> 2025-07-17T07:36:53.1478362Z >>> @staticmethod 2025-07-17T07:36:53.1478476Z >>> @rpc.functions.async_execution 2025-07-17T07:36:53.1478600Z >>> def static_async_add(to, x, y, z): 2025-07-17T07:36:53.1478765Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-07-17T07:36:53.1478888Z >>> lambda fut: fut.wait() + z 2025-07-17T07:36:53.1478970Z >>> ) 2025-07-17T07:36:53.1479053Z >>> 2025-07-17T07:36:53.1479152Z >>> @classmethod 2025-07-17T07:36:53.1479267Z >>> @rpc.functions.async_execution 2025-07-17T07:36:53.1479386Z >>> def class_async_add(cls, to, x, y, z): 2025-07-17T07:36:53.1479520Z >>> ret_fut = torch.futures.Future() 2025-07-17T07:36:53.1479666Z >>> rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-07-17T07:36:53.1479813Z >>> lambda fut: ret_fut.set_result(fut.wait() + z) 2025-07-17T07:36:53.1479908Z >>> ) 2025-07-17T07:36:53.1480003Z >>> return ret_fut 2025-07-17T07:36:53.1480094Z >>> 2025-07-17T07:36:53.1480253Z >>> @rpc.functions.async_execution 2025-07-17T07:36:53.1480371Z >>> def bound_async_add(self, to, x, y, z): 2025-07-17T07:36:53.1480541Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-07-17T07:36:53.1480649Z >>> lambda fut: fut.wait() + z 2025-07-17T07:36:53.1480731Z >>> ) 2025-07-17T07:36:53.1480824Z >>> 2025-07-17T07:36:53.1480910Z >>> # On worker0 2025-07-17T07:36:53.1481000Z >>> ret = rpc.rpc_sync( 2025-07-17T07:36:53.1481099Z >>> "worker1", 2025-07-17T07:36:53.1481227Z >>> AsyncExecutionClass.static_async_add, 2025-07-17T07:36:53.1481380Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-07-17T07:36:53.1481460Z >>> ) 2025-07-17T07:36:53.1481573Z >>> print(ret) # prints tensor([4., 4.]) 2025-07-17T07:36:53.1481664Z >>> 2025-07-17T07:36:53.1481760Z >>> ret = rpc.rpc_sync( 2025-07-17T07:36:53.1481843Z >>> "worker1", 2025-07-17T07:36:53.1481986Z >>> AsyncExecutionClass.class_async_add, 2025-07-17T07:36:53.1482099Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-07-17T07:36:53.1482175Z >>> ) 2025-07-17T07:36:53.1482300Z >>> print(ret) # prints tensor([4., 4.]) 2025-07-17T07:36:53.1482376Z 2025-07-17T07:36:53.1482581Z This decorator also works with RRef helpers, i.e., . 2025-07-17T07:36:53.1482736Z :meth:`torch.distributed.rpc.RRef.rpc_sync`, 2025-07-17T07:36:53.1482884Z :meth:`torch.distributed.rpc.RRef.rpc_async`, and 2025-07-17T07:36:53.1483034Z :meth:`torch.distributed.rpc.RRef.remote`. 2025-07-17T07:36:53.1483109Z 2025-07-17T07:36:53.1483223Z >>> from torch.distributed import rpc 2025-07-17T07:36:53.1483313Z >>> 2025-07-17T07:36:53.1483442Z >>> # reuse the AsyncExecutionClass class above 2025-07-17T07:36:53.1483590Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-07-17T07:36:53.1483813Z >>> ret = rref.rpc_sync().static_async_add("worker2", torch.ones(2), 1, 2) 2025-07-17T07:36:53.1483924Z >>> print(ret) # prints tensor([4., 4.]) 2025-07-17T07:36:53.1484004Z >>> 2025-07-17T07:36:53.1484165Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-07-17T07:36:53.1484399Z >>> ret = rref.rpc_async().static_async_add("worker2", torch.ones(2), 1, 2).wait() 2025-07-17T07:36:53.1484524Z >>> print(ret) # prints tensor([4., 4.]) 2025-07-17T07:36:53.1484600Z >>> 2025-07-17T07:36:53.1484745Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-07-17T07:36:53.1484986Z >>> ret = rref.remote().static_async_add("worker2", torch.ones(2), 1, 2).to_here() 2025-07-17T07:36:53.1485096Z >>> print(ret) # prints tensor([4., 4.]) 2025-07-17T07:36:53.1485170Z 2025-07-17T07:36:53.1485518Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1485593Z 2025-07-17T07:36:53.1485685Z warnings.warn(msg) 2025-07-17T07:36:53.1485778Z 2025-07-17T07:36:53.1485987Z --- Parse Warning: 85 / 136 --- 2025-07-17T07:36:53.1487089Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=TensorPipeRpcBackendOptions.set_device_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/options.py line=113. 2025-07-17T07:36:53.1487345Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1487421Z 2025-07-17T07:36:53.1487635Z Set device mapping between each RPC caller and callee pair. This 2025-07-17T07:36:53.1487814Z function can be called multiple times to incrementally add 2025-07-17T07:36:53.1487922Z device placement configurations. 2025-07-17T07:36:53.1488013Z 2025-07-17T07:36:53.1488089Z Args: 2025-07-17T07:36:53.1488196Z to (str): Callee name. 2025-07-17T07:36:53.1488389Z device_map (Dict of int, str, or torch.device): Device placement 2025-07-17T07:36:53.1488594Z mappings from this worker to the callee. This map must be 2025-07-17T07:36:53.1488691Z invertible. 2025-07-17T07:36:53.1488763Z 2025-07-17T07:36:53.1488844Z Example: 2025-07-17T07:36:53.1488968Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:53.1489050Z >>> # both workers 2025-07-17T07:36:53.1489136Z >>> def add(x, y): 2025-07-17T07:36:53.1489282Z >>> print(x) # tensor([1., 1.], device='cuda:1') 2025-07-17T07:36:53.1489381Z >>> return x + y, (x + y).to(2) 2025-07-17T07:36:53.1489485Z >>> 2025-07-17T07:36:53.1489587Z >>> # on worker 0 2025-07-17T07:36:53.1489719Z >>> options = TensorPipeRpcBackendOptions( 2025-07-17T07:36:53.1489835Z >>> num_worker_threads=8, 2025-07-17T07:36:53.1489945Z >>> device_maps={"worker1": {0: 1}} 2025-07-17T07:36:53.1490071Z >>> # maps worker0's cuda:0 to worker1's cuda:1 2025-07-17T07:36:53.1490165Z >>> ) 2025-07-17T07:36:53.1490289Z >>> options.set_device_map("worker1", {1: 2}) 2025-07-17T07:36:53.1490412Z >>> # maps worker0's cuda:1 to worker1's cuda:2 2025-07-17T07:36:53.1490500Z >>> 2025-07-17T07:36:53.1490593Z >>> rpc.init_rpc( 2025-07-17T07:36:53.1490729Z >>> "worker0", 2025-07-17T07:36:53.1490823Z >>> rank=0, 2025-07-17T07:36:53.1490912Z >>> world_size=2, 2025-07-17T07:36:53.1491048Z >>> backend=rpc.BackendType.TENSORPIPE, 2025-07-17T07:36:53.1491152Z >>> rpc_backend_options=options 2025-07-17T07:36:53.1491232Z >>> ) 2025-07-17T07:36:53.1491325Z >>> 2025-07-17T07:36:53.1491412Z >>> x = torch.ones(2) 2025-07-17T07:36:53.1491570Z >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1)) 2025-07-17T07:36:53.1491757Z >>> # The first argument will be moved to cuda:1 on worker1. When 2025-07-17T07:36:53.1491935Z >>> # sending the return value back, it will follow the invert of 2025-07-17T07:36:53.1492108Z >>> # the device map, and hence will be moved back to cuda:0 and 2025-07-17T07:36:53.1492214Z >>> # cuda:1 on worker0 2025-07-17T07:36:53.1492354Z >>> print(rets[0]) # tensor([2., 2.], device='cuda:0') 2025-07-17T07:36:53.1492507Z >>> print(rets[1]) # tensor([2., 2.], device='cuda:1') 2025-07-17T07:36:53.1492581Z 2025-07-17T07:36:53.1492830Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1492920Z 2025-07-17T07:36:53.1493011Z warnings.warn(msg) 2025-07-17T07:36:53.1493088Z 2025-07-17T07:36:53.1493283Z --- Parse Warning: 86 / 136 --- 2025-07-17T07:36:53.1494400Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_server_process_global_profile in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/server_process_global_profiler.py line=19. 2025-07-17T07:36:53.1494674Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1494748Z 2025-07-17T07:36:53.1494943Z It has the same API as ``torch.autograd.profiler.profile`` class, 2025-07-17T07:36:53.1495235Z except that it enables profiling on all threads running RPC server request callbacks. 2025-07-17T07:36:53.1495309Z 2025-07-17T07:36:53.1495586Z Context manager that manages autograd profiler state and holds a summary of results. 2025-07-17T07:36:53.1495824Z Under the hood it just records events of functions being executed in C++ and 2025-07-17T07:36:53.1496053Z exposes those events to Python. You can wrap any code into it and it will 2025-07-17T07:36:53.1496173Z only report runtime of PyTorch functions. 2025-07-17T07:36:53.1496451Z Note: profiler is thread local and is automatically propagated into the async tasks 2025-07-17T07:36:53.1496528Z 2025-07-17T07:36:53.1496649Z Args: 2025-07-17T07:36:53.1496912Z enabled (bool, optional): Setting this to False makes this context manager a no-op. 2025-07-17T07:36:53.1497012Z Default: ``True``. 2025-07-17T07:36:53.1497094Z 2025-07-17T07:36:53.1497374Z use_cuda (bool, optional): Enables timing of CUDA events as well using the cudaEvent API. 2025-07-17T07:36:53.1497574Z Adds approximately 4us of overhead to each tensor operation. 2025-07-17T07:36:53.1497680Z Default: ``False`` 2025-07-17T07:36:53.1497755Z 2025-07-17T07:36:53.1497979Z record_shapes (bool, optional): If shapes recording is set, information 2025-07-17T07:36:53.1498236Z about input dimensions will be collected. This allows one to see which 2025-07-17T07:36:53.1498442Z dimensions have been used under the hood and further group by them 2025-07-17T07:36:53.1498661Z using prof.key_averages(group_by_input_shape=True). Please note that 2025-07-17T07:36:53.1498882Z shape recording might skew your profiling data. It is recommended to 2025-07-17T07:36:53.1499119Z use separate runs with and without shape recording to validate the timing. 2025-07-17T07:36:53.1499348Z Most likely the skew will be negligible for bottom most events (in a case 2025-07-17T07:36:53.1499604Z of nested function calls). But for higher level functions the total 2025-07-17T07:36:53.1499817Z self cpu time might be artificially increased because of the shape 2025-07-17T07:36:53.1499902Z collection. 2025-07-17T07:36:53.1499977Z 2025-07-17T07:36:53.1500252Z profile_memory (bool, optional): Whether to report memory usage, default: ``False`` 2025-07-17T07:36:53.1500328Z 2025-07-17T07:36:53.1500415Z .. warning:: 2025-07-17T07:36:53.1500624Z Enabling memory profiling incurs additional profiler overhead 2025-07-17T07:36:53.1500698Z 2025-07-17T07:36:53.1500780Z .. warning:: 2025-07-17T07:36:53.1501077Z Due to some CUDA multiprocessing limitations (see :ref:`multiprocessing-cuda-note`), 2025-07-17T07:36:53.1501272Z one cannot use the profiler with ``use_cuda = True`` to benchmark 2025-07-17T07:36:53.1501517Z DataLoaders with ``num_workers > 0``. If you wish to benchmark data loading, 2025-07-17T07:36:53.1501678Z please use ``use_cuda = False`` or ``num_workers = 0``. 2025-07-17T07:36:53.1501754Z 2025-07-17T07:36:53.1501847Z Example: 2025-07-17T07:36:53.1501938Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1502026Z >>> # On worker 0: 2025-07-17T07:36:53.1502125Z >>> import torch 2025-07-17T07:36:53.1502249Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:53.1502384Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-07-17T07:36:53.1502510Z >>> x, y = torch.tensor(1), torch.tensor(2) 2025-07-17T07:36:53.1502622Z >>> outer_profile_rref = rpc.remote( 2025-07-17T07:36:53.1502790Z ... dst_worker_name, rpc._server_process_global_profile 2025-07-17T07:36:53.1502868Z ... ) 2025-07-17T07:36:53.1502992Z >>> outer_profile_rref.rpc_sync().__enter__() 2025-07-17T07:36:53.1503141Z >>> rpc.rpc_sync(dst_worker_name, torch.add, (x, y)) 2025-07-17T07:36:53.1503250Z >>> inner_profile_rref = rpc.remote( 2025-07-17T07:36:53.1503407Z ... dst_worker_name, rpc._server_process_global_profile 2025-07-17T07:36:53.1503495Z ... ) 2025-07-17T07:36:53.1503619Z >>> inner_profile_rref.rpc_sync().__enter__() 2025-07-17T07:36:53.1503760Z >>> rpc.rpc_sync(dst_worker_name, torch.sub, (x, y)) 2025-07-17T07:36:53.1503939Z >>> inner_profile_rref.rpc_sync().__exit__(None, None, None) 2025-07-17T07:36:53.1504103Z >>> outer_profile_rref.rpc_sync().__exit__(None, None, None) 2025-07-17T07:36:53.1504267Z >>> print(inner_profile_rref.rpc_sync().key_averages()) 2025-07-17T07:36:53.1504499Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:53.1504833Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-07-17T07:36:53.1505073Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:53.1505259Z sub 85.06% 76.275us 100.00% 89.667us 89.667us 1 2025-07-17T07:36:53.1505457Z empty 14.94% 13.392us 14.94% 13.392us 13.392us 1 2025-07-17T07:36:53.1505704Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:53.1505811Z Self CPU time total: 89.667us 2025-07-17T07:36:53.1505982Z >>> print(outer_profile_rref.rpc_sync().key_averages()) 2025-07-17T07:36:53.1506199Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:53.1506504Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-07-17T07:36:53.1506733Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:53.1506965Z sub 35.65% 76.275us 41.91% 89.667us 89.667us 1 2025-07-17T07:36:53.1507160Z empty 12.67% 27.101us 12.67% 27.101us 13.551us 2 2025-07-17T07:36:53.1507338Z add 51.68% 110.550us 58.09% 124.259us 124.259us 1 2025-07-17T07:36:53.1507557Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-07-17T07:36:53.1507677Z Self CPU time total: 213.926us 2025-07-17T07:36:53.1507774Z >>> rpc.shutdown() 2025-07-17T07:36:53.1507866Z 2025-07-17T07:36:53.1507956Z >>> # On worker 1: 2025-07-17T07:36:53.1508082Z >>> import torch.distributed.rpc as rpc 2025-07-17T07:36:53.1508230Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-07-17T07:36:53.1508388Z >>> # wait for worker 0 to finish work, and then shutdown. 2025-07-17T07:36:53.1508483Z >>> rpc.shutdown() 2025-07-17T07:36:53.1508574Z 2025-07-17T07:36:53.1508827Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1508906Z 2025-07-17T07:36:53.1509016Z warnings.warn(msg) 2025-07-17T07:36:53.1509096Z 2025-07-17T07:36:53.1509289Z --- Parse Warning: 87 / 136 --- 2025-07-17T07:36:53.1510310Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=local_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_func_map.py line=35. 2025-07-17T07:36:53.1510573Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1510664Z 2025-07-17T07:36:53.1510928Z :meth:`local_map` is an experimental API that allows users to pass :class:`DTensor` s 2025-07-17T07:36:53.1511207Z to a function that is written to be applied on ``torch.Tensor`` s. It is done by extracting 2025-07-17T07:36:53.1511483Z the local components of :class:`DTensor`, call the function, and wrap the outputs to 2025-07-17T07:36:53.1511640Z :class:`DTensor` according to the ``out_placements``. 2025-07-17T07:36:53.1511734Z 2025-07-17T07:36:53.1511817Z Args: 2025-07-17T07:36:53.1512019Z func (Callable): the function to be applied on each local shard of 2025-07-17T07:36:53.1512128Z :class:`DTensor` s. 2025-07-17T07:36:53.1512353Z out_placements (Union[`PlacementType`, Tuple[`PlacementType`, ...]]): 2025-07-17T07:36:53.1512605Z the desired placements of the :class:`DTensor` s in ``func``'s flattened output. 2025-07-17T07:36:53.1512885Z If the flattened ``output`` is a single value, the ``out_placements`` should be 2025-07-17T07:36:53.1513123Z of type `PlacementType`. Otherwise if the flattened ``output`` has multiple 2025-07-17T07:36:53.1513383Z values, the ``out_placements`` should be a tuple of `PlacementType` values 1:1 2025-07-17T07:36:53.1513502Z mapping to the flattened ``output``. 2025-07-17T07:36:53.1513703Z Besides, for :class:`Tensor` output, we use `PlacementType` as its 2025-07-17T07:36:53.1513989Z placements (a `Tuple[Placement]` value). For non-Tensor output, the `PlacementType` 2025-07-17T07:36:53.1514109Z should be `None`. 2025-07-17T07:36:53.1514341Z Note that the only exception is when no :class:`DTensor` argument is passed 2025-07-17T07:36:53.1514569Z in. In this case, even if `out_placements` is not `None`, the result function 2025-07-17T07:36:53.1514822Z should ignore the desired placements because the function is not running with 2025-07-17T07:36:53.1514929Z :class:`DTensor` s. 2025-07-17T07:36:53.1515092Z in_placements (Tuple[`PlacementType`, ...], optional): 2025-07-17T07:36:53.1515413Z the required placements of the :class:`DTensor` s in the flattened inputs of ``func``. 2025-07-17T07:36:53.1515658Z If ``in_placements`` is specified, :meth:`local_map` would examine whether the 2025-07-17T07:36:53.1515881Z placements of each :class:`DTensor` argument is the same as the required 2025-07-17T07:36:53.1516061Z placements or not. If the placements are not the same and 2025-07-17T07:36:53.1516314Z ``redistribute_inputs`` is ``False``, an exception will be raised. Otherwise if 2025-07-17T07:36:53.1516553Z ``redistribute_inputs`` is ``True``, the argument will be first redistributed to 2025-07-17T07:36:53.1516818Z the required sharding placements before passing its local tensor to ``func``. 2025-07-17T07:36:53.1517038Z The only exception is when required placements are not ``None`` and the 2025-07-17T07:36:53.1517273Z argument is a :class:`torch.Tensor`. In this case, the placements examination 2025-07-17T07:36:53.1517499Z will be skipped and the argument will be directly passed to ``func``. 2025-07-17T07:36:53.1517715Z If ``in_placements`` is ``None``, no placements examination will be performed. 2025-07-17T07:36:53.1517818Z Default: None 2025-07-17T07:36:53.1517997Z in_grad_placements (Tuple[`PlacementType`, ...], optional): 2025-07-17T07:36:53.1518204Z the placements hint of the :class:`DTensor` s gradient corresponds 2025-07-17T07:36:53.1518422Z to the flattened input DTensor. This argument is the hint that user 2025-07-17T07:36:53.1518601Z can give to :meth:`to_local` in case the gradient layout of the 2025-07-17T07:36:53.1518813Z local tensor input does not match its :class:`DTensor` input layout. 2025-07-17T07:36:53.1519024Z If not specified, we will assume the gradient layout of the local 2025-07-17T07:36:53.1519236Z tensor input remains the same as the original :class:`DTensor` input 2025-07-17T07:36:53.1519417Z and use that for gradient computation. Default: None. 2025-07-17T07:36:53.1519551Z device_mesh (:class:`DeviceMesh`, optional): 2025-07-17T07:36:53.1519769Z the device mesh that the output :class:`DTensor` s are placed on. If not 2025-07-17T07:36:53.1520030Z specified, this will be inferred from the first input :class:`DTensor`'s device 2025-07-17T07:36:53.1520130Z mesh. Default: None. 2025-07-17T07:36:53.1520207Z 2025-07-17T07:36:53.1520307Z Keyword Args: 2025-07-17T07:36:53.1520427Z redistribute_inputs (bool, optional): 2025-07-17T07:36:53.1520676Z the bool value indicating whether to reshard the input :class:`DTensor` s when 2025-07-17T07:36:53.1520961Z their placements are different from the required input placements. If this 2025-07-17T07:36:53.1521182Z value is ``False`` and some :class:`DTensor` input has a different placement, 2025-07-17T07:36:53.1521327Z an exception will be raised. Default: False. 2025-07-17T07:36:53.1521408Z 2025-07-17T07:36:53.1521489Z Returns: 2025-07-17T07:36:53.1521753Z A ``Callable`` that applies ``func`` to each local shard of the input :class:`DTensor` 2025-07-17T07:36:53.1521987Z and returns a :class:`DTensor` constructed from the return value of ``func``. 2025-07-17T07:36:53.1522089Z 2025-07-17T07:36:53.1522181Z Raises: 2025-07-17T07:36:53.1522420Z AssertionError: For any non-DTensor output, we require its corresponding 2025-07-17T07:36:53.1522685Z output placement in ``out_placements`` be None. An AssertionError will be raised 2025-07-17T07:36:53.1522783Z if this is not the case. 2025-07-17T07:36:53.1522861Z 2025-07-17T07:36:53.1523134Z ValueError: If ``redistribute_inputs=False`` but the input :class:`DTensor` needs 2025-07-17T07:36:53.1523284Z a redistribution according to ``in_placements``. 2025-07-17T07:36:53.1523363Z 2025-07-17T07:36:53.1523456Z Example: 2025-07-17T07:36:53.1523616Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:53.1523755Z >>> def mm_allreduce_forward(device_mesh, W, X): 2025-07-17T07:36:53.1523887Z >>> partial_sum_tensor = torch.mm(W, X) 2025-07-17T07:36:53.1524124Z >>> reduced_tensor = funcol.all_reduce(partial_sum_tensor, "sum", device_mesh) 2025-07-17T07:36:53.1524239Z >>> return reduced_tensor 2025-07-17T07:36:53.1524319Z >>> 2025-07-17T07:36:53.1524444Z >>> W = torch.randn(12, 8, requires_grad=False) 2025-07-17T07:36:53.1524576Z >>> X = torch.randn(8, 16, requires_grad=False) 2025-07-17T07:36:53.1524667Z >>> Y = torch.mm(W, X) 2025-07-17T07:36:53.1524852Z >>> row_wise = [Shard(0)] # row-wise sharding placements on 1-d mesh 2025-07-17T07:36:53.1525042Z >>> col_wise = [Shard(1)] # col-wise sharding placements on 1-d mesh 2025-07-17T07:36:53.1525120Z >>> 2025-07-17T07:36:53.1525466Z >>> # local_mm_allreduce_forward is the function wrapped with DTensor/Tensor convertion 2025-07-17T07:36:53.1525606Z >>> local_mm_allreduce_forward = local_map( 2025-07-17T07:36:53.1525710Z >>> mm_allreduce_forward, 2025-07-17T07:36:53.1525835Z >>> out_placements=[Replicate()], 2025-07-17T07:36:53.1525951Z >>> in_placements=[col_wise, row_wise], 2025-07-17T07:36:53.1526058Z >>> device_mesh=device_mesh, 2025-07-17T07:36:53.1526152Z >>> ) 2025-07-17T07:36:53.1526234Z >>> 2025-07-17T07:36:53.1526335Z >>> W_dt = distribute_tensor( 2025-07-17T07:36:53.1526451Z ... W, device_mesh, (col_wise) 2025-07-17T07:36:53.1526559Z ... ) # col-wisely sharded W tensor 2025-07-17T07:36:53.1526660Z >>> X_dt = distribute_tensor( 2025-07-17T07:36:53.1526775Z ... X, device_mesh, (row_wise) 2025-07-17T07:36:53.1526881Z ... ) # row-wisely sharded X tensor 2025-07-17T07:36:53.1527007Z >>> Y_dt = local_mm_allreduce_forward( 2025-07-17T07:36:53.1527109Z ... device_mesh, W_dt, X_dt 2025-07-17T07:36:53.1527253Z ... ) # apply local_mm_allreduce_forward to DTensors 2025-07-17T07:36:53.1527343Z 2025-07-17T07:36:53.1527538Z .. note:: This API is currently experimental and subject to change 2025-07-17T07:36:53.1527612Z 2025-07-17T07:36:53.1527876Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1527952Z 2025-07-17T07:36:53.1528047Z warnings.warn(msg) 2025-07-17T07:36:53.1528134Z 2025-07-17T07:36:53.1528338Z --- Parse Warning: 88 / 136 --- 2025-07-17T07:36:53.1529717Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_sharding in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_register_sharding.py line=25. 2025-07-17T07:36:53.1530263Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1530396Z 2025-07-17T07:36:53.1530888Z :meth:`register_sharding` is an experimental API that allows users to register sharding 2025-07-17T07:36:53.1531265Z strategies for an operator when the tensor inputs and outputs are DTensor. 2025-07-17T07:36:53.1531576Z It can be useful when: (1) there doesn't exist a default sharding strategy for ``op``, 2025-07-17T07:36:53.1531884Z e.g. when ``op`` is a custom operator that is not supported by :class:`DTensor`; (2) 2025-07-17T07:36:53.1532157Z when users would like to overwrite default sharding strategies of existing operators. 2025-07-17T07:36:53.1532247Z 2025-07-17T07:36:53.1532330Z Args: 2025-07-17T07:36:53.1532458Z op (Union[OpOverload, List[OpOverload]]): 2025-07-17T07:36:53.1532659Z An op or a list of ops to register the customized sharding function. 2025-07-17T07:36:53.1532736Z 2025-07-17T07:36:53.1532817Z Returns: 2025-07-17T07:36:53.1533153Z A function decorator which can be used to wrap a function that defines the sharding 2025-07-17T07:36:53.1533428Z strategy for the operator specified in ``op``. The defined sharding strategy will be 2025-07-17T07:36:53.1533709Z registered to DTensor and will override the default sharding strategy if DTensor has 2025-07-17T07:36:53.1534013Z already implemented the operator. The customized sharding function takes the same inputs 2025-07-17T07:36:53.1534251Z as the original op (except that if an arg is a :class:`torch.Tensor`, it will be 2025-07-17T07:36:53.1534530Z replaced by a tensor-like object that DTensor uses internally). The function should 2025-07-17T07:36:53.1534801Z return a sequence of 2-tuples, each specifying acceptable output placements and its 2025-07-17T07:36:53.1534917Z corresponding intput placements. 2025-07-17T07:36:53.1535005Z 2025-07-17T07:36:53.1535088Z Example: 2025-07-17T07:36:53.1535214Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:53.1535351Z >>> @register_sharding(aten._softmax.default) 2025-07-17T07:36:53.1535503Z >>> def custom_softmax_sharding(x, dim, half_to_float): 2025-07-17T07:36:53.1535657Z >>> softmax_dim = dim if dim >= 0 else dim + x.ndim 2025-07-17T07:36:53.1535769Z >>> acceptable_shardings = [] 2025-07-17T07:36:53.1535851Z >>> 2025-07-17T07:36:53.1536039Z >>> all_replicate = ([Replicate()], [Replicate(), None, None]) 2025-07-17T07:36:53.1536180Z >>> acceptable_shardings.append(all_replicate) 2025-07-17T07:36:53.1536259Z >>> 2025-07-17T07:36:53.1536386Z >>> for sharding_dim in range(x.ndim): 2025-07-17T07:36:53.1536504Z >>> if sharding_dim != softmax_dim: 2025-07-17T07:36:53.1536609Z >>> all_sharded = ( 2025-07-17T07:36:53.1536715Z >>> [Shard(sharding_dim)], 2025-07-17T07:36:53.1536836Z >>> [Shard(sharding_dim), None, None], 2025-07-17T07:36:53.1536935Z >>> ) 2025-07-17T07:36:53.1537070Z >>> acceptable_shardings.append(all_sharded) 2025-07-17T07:36:53.1537150Z >>> 2025-07-17T07:36:53.1537266Z >>> return acceptable_shardings 2025-07-17T07:36:53.1537341Z 2025-07-17T07:36:53.1537536Z .. note:: This API is currently experimental and subject to change 2025-07-17T07:36:53.1537627Z 2025-07-17T07:36:53.1537878Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1537966Z 2025-07-17T07:36:53.1538061Z warnings.warn(msg) 2025-07-17T07:36:53.1538135Z 2025-07-17T07:36:53.1538371Z --- Parse Warning: 89 / 136 --- 2025-07-17T07:36:53.1539442Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleInput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=428. 2025-07-17T07:36:53.1539706Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1539797Z 2025-07-17T07:36:53.1540177Z Configure the nn.Module's inputs to convert the input tensors of the nn.Module to DTensors at runtime according to 2025-07-17T07:36:53.1540510Z ``input_layouts``, and perform layout redistribution according to the ``desired_input_layouts``. 2025-07-17T07:36:53.1540617Z 2025-07-17T07:36:53.1540705Z Keyword Args: 2025-07-17T07:36:53.1540918Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-07-17T07:36:53.1541243Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-07-17T07:36:53.1541602Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-07-17T07:36:53.1541734Z as a placeholder. default: None. 2025-07-17T07:36:53.1542027Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-07-17T07:36:53.1542416Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-07-17T07:36:53.1542809Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-07-17T07:36:53.1542943Z input_kwarg_layouts (Dict[str, Placement]): 2025-07-17T07:36:53.1543331Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-07-17T07:36:53.1543424Z default: None 2025-07-17T07:36:53.1543584Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-07-17T07:36:53.1543962Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-07-17T07:36:53.1544106Z have the desired DTensor layouts. default: None. 2025-07-17T07:36:53.1544233Z use_local_output (bool, optional): 2025-07-17T07:36:53.1544595Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-07-17T07:36:53.1544679Z Returns: 2025-07-17T07:36:53.1545006Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs. 2025-07-17T07:36:53.1545086Z 2025-07-17T07:36:53.1545173Z Example:: 2025-07-17T07:36:53.1545294Z >>> # xdoctest: +SKIP(failing) 2025-07-17T07:36:53.1545605Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInput 2025-07-17T07:36:53.1545811Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-07-17T07:36:53.1545894Z >>> ... 2025-07-17T07:36:53.1546198Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-07-17T07:36:53.1546335Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-07-17T07:36:53.1546415Z >>> 2025-07-17T07:36:53.1546750Z >>> # According to the style specified below, the first input of attn will be annotated to Sharded DTensor 2025-07-17T07:36:53.1546909Z >>> # and then redistributed to Replicated DTensor. 2025-07-17T07:36:53.1547010Z >>> parallelize_module( 2025-07-17T07:36:53.1547154Z >>> block, # this can be a submodule or module 2025-07-17T07:36:53.1547243Z >>> tp_mesh, 2025-07-17T07:36:53.1547345Z >>> parallelize_plan={ 2025-07-17T07:36:53.1547480Z >>> "attn": PrepareModuleInput( 2025-07-17T07:36:53.1547616Z >>> input_layouts=(Shard(0), None, None, ...), 2025-07-17T07:36:53.1547809Z >>> desired_input_layouts=(Replicate(), None, None, ...) 2025-07-17T07:36:53.1547901Z >>> ), 2025-07-17T07:36:53.1547980Z >>> } 2025-07-17T07:36:53.1548057Z >>> ) 2025-07-17T07:36:53.1548149Z 2025-07-17T07:36:53.1548404Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1548482Z 2025-07-17T07:36:53.1548587Z warnings.warn(msg) 2025-07-17T07:36:53.1548662Z 2025-07-17T07:36:53.1548862Z --- Parse Warning: 90 / 136 --- 2025-07-17T07:36:53.1549900Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=597. 2025-07-17T07:36:53.1550190Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1550277Z 2025-07-17T07:36:53.1550672Z Configure the nn.Module's outputs to convert the output tensors of the nn.Module to DTensors at runtime according to 2025-07-17T07:36:53.1551011Z ``output_layouts``, and perform layout redistribution according to the ``desired_output_layouts``. 2025-07-17T07:36:53.1551087Z 2025-07-17T07:36:53.1551171Z Keyword Args: 2025-07-17T07:36:53.1551397Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-07-17T07:36:53.1551735Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-07-17T07:36:53.1552114Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-07-17T07:36:53.1552267Z ``None`` need to be specified as a placeholder. 2025-07-17T07:36:53.1552460Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-07-17T07:36:53.1552859Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-07-17T07:36:53.1552972Z have the desired DTensor layouts. 2025-07-17T07:36:53.1553086Z use_local_output (bool, optional): 2025-07-17T07:36:53.1553461Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-07-17T07:36:53.1553570Z Returns: 2025-07-17T07:36:53.1553861Z A ParallelStyle object that prepares the sharding layouts of the nn.Module's outputs. 2025-07-17T07:36:53.1553951Z 2025-07-17T07:36:53.1554036Z Example:: 2025-07-17T07:36:53.1554143Z >>> # xdoctest: +SKIP(failing) 2025-07-17T07:36:53.1554472Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleOutput 2025-07-17T07:36:53.1554664Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-07-17T07:36:53.1554753Z >>> ... 2025-07-17T07:36:53.1555054Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-07-17T07:36:53.1555183Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-07-17T07:36:53.1555278Z >>> 2025-07-17T07:36:53.1555676Z >>> # According to the style specified below, the output of the TransformerBlock will be converted to Replicated DTensor 2025-07-17T07:36:53.1555812Z >>> # and then redistributed to Sharded DTensor. 2025-07-17T07:36:53.1555922Z >>> parallelize_module( 2025-07-17T07:36:53.1556051Z >>> block, # this can be a submodule or module 2025-07-17T07:36:53.1556149Z >>> tp_mesh, 2025-07-17T07:36:53.1556284Z >>> parallelize_plan = PrepareModuleOutput( 2025-07-17T07:36:53.1556398Z >>> output_layouts=Replicate(), 2025-07-17T07:36:53.1556524Z >>> desired_output_layouts=Shard(0) 2025-07-17T07:36:53.1556604Z >>> ) 2025-07-17T07:36:53.1556682Z >>> ) 2025-07-17T07:36:53.1556769Z 2025-07-17T07:36:53.1557018Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1557122Z 2025-07-17T07:36:53.1557228Z warnings.warn(msg) 2025-07-17T07:36:53.1557303Z 2025-07-17T07:36:53.1557488Z --- Parse Warning: 91 / 136 --- 2025-07-17T07:36:53.1558565Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleInputOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=705. 2025-07-17T07:36:53.1558828Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1558943Z 2025-07-17T07:36:53.1559374Z Configure the nn.Module's inputs (and outputs) to convert the input tensors (and output tensors, respectively) of the nn.Module 2025-07-17T07:36:53.1559794Z to DTensors at runtime according to ``input_layouts`` (and output_layouts, respectively), and perform layout redistribution 2025-07-17T07:36:53.1560184Z according to the ``desired_input_layouts`` (and ``desired_output_layouts``, respectively). This is a combination of 2025-07-17T07:36:53.1560390Z :class:`PrepareModuleInput` and :class:`PrepareModuleOutput`. 2025-07-17T07:36:53.1560481Z 2025-07-17T07:36:53.1560567Z Keyword Args: 2025-07-17T07:36:53.1560812Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-07-17T07:36:53.1561151Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-07-17T07:36:53.1561505Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-07-17T07:36:53.1561624Z as a placeholder. default: None. 2025-07-17T07:36:53.1561863Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-07-17T07:36:53.1562240Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-07-17T07:36:53.1562644Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-07-17T07:36:53.1562771Z input_kwarg_layouts (Dict[str, Placement]): 2025-07-17T07:36:53.1563148Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-07-17T07:36:53.1563249Z default: None 2025-07-17T07:36:53.1563407Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-07-17T07:36:53.1563784Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-07-17T07:36:53.1563929Z have the desired DTensor layouts. default: None. 2025-07-17T07:36:53.1564039Z use_local_input (bool, optional): 2025-07-17T07:36:53.1564404Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-07-17T07:36:53.1564563Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-07-17T07:36:53.1564899Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-07-17T07:36:53.1565288Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-07-17T07:36:53.1565513Z ``None`` need to be specified as a placeholder. 2025-07-17T07:36:53.1565725Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-07-17T07:36:53.1566110Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-07-17T07:36:53.1566226Z have the desired DTensor layouts. 2025-07-17T07:36:53.1566351Z use_local_output (bool, optional): 2025-07-17T07:36:53.1566706Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-07-17T07:36:53.1566833Z Returns: 2025-07-17T07:36:53.1567197Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs and outputs. 2025-07-17T07:36:53.1567275Z 2025-07-17T07:36:53.1567375Z Example:: 2025-07-17T07:36:53.1567477Z >>> # xdoctest: +SKIP(failing) 2025-07-17T07:36:53.1567819Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInputOutput 2025-07-17T07:36:53.1568021Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-07-17T07:36:53.1568100Z >>> ... 2025-07-17T07:36:53.1568429Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-07-17T07:36:53.1568567Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-07-17T07:36:53.1568647Z >>> 2025-07-17T07:36:53.1568992Z >>> # According to the style specified below, the first input of attn will be annotated as Sharded DTensor 2025-07-17T07:36:53.1569349Z >>> # and then redistributed to Replicated DTensor, and the output of the TransformerBlock will be annotated 2025-07-17T07:36:53.1569555Z >>> # as Replicated DTensor and then redistributed to Sharded DTensor. 2025-07-17T07:36:53.1569672Z >>> parallelize_module( 2025-07-17T07:36:53.1569849Z >>> block, # this can be a submodule or module 2025-07-17T07:36:53.1570090Z >>> tp_mesh, 2025-07-17T07:36:53.1570244Z >>> parallelize_plan={ 2025-07-17T07:36:53.1570377Z >>> "attn": PrepareModuleInputOutput( 2025-07-17T07:36:53.1570524Z >>> input_layouts=(Shard(0), None, None, ...), 2025-07-17T07:36:53.1570698Z >>> desired_input_layouts=(Replicate(), None, None, ...), 2025-07-17T07:36:53.1570812Z >>> output_layouts=Replicate(), 2025-07-17T07:36:53.1570944Z >>> desired_output_layouts=Shard(0), 2025-07-17T07:36:53.1571026Z >>> ), 2025-07-17T07:36:53.1571106Z >>> } 2025-07-17T07:36:53.1571198Z >>> ) 2025-07-17T07:36:53.1571274Z 2025-07-17T07:36:53.1571525Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1571614Z 2025-07-17T07:36:53.1571707Z warnings.warn(msg) 2025-07-17T07:36:53.1571784Z 2025-07-17T07:36:53.1572002Z --- Parse Warning: 92 / 136 --- 2025-07-17T07:36:53.1573106Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LowRankMultivariateNormal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lowrank_multivariate_normal.py line=56. 2025-07-17T07:36:53.1573383Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1573461Z 2025-07-17T07:36:53.1573769Z Creates a multivariate normal distribution with covariance matrix having a low-rank form 2025-07-17T07:36:53.1573974Z parameterized by :attr:`cov_factor` and :attr:`cov_diag`:: 2025-07-17T07:36:53.1574051Z 2025-07-17T07:36:53.1574235Z covariance_matrix = cov_factor @ cov_factor.T + cov_diag 2025-07-17T07:36:53.1574314Z 2025-07-17T07:36:53.1574396Z Example: 2025-07-17T07:36:53.1574551Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-07-17T07:36:53.1574714Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-07-17T07:36:53.1574831Z >>> m = LowRankMultivariateNormal( 2025-07-17T07:36:53.1575018Z ... torch.zeros(2), torch.tensor([[1.0], [0.0]]), torch.ones(2) 2025-07-17T07:36:53.1575099Z ... ) 2025-07-17T07:36:53.1575386Z >>> m.sample() # normally distributed with mean=`[0,0]`, cov_factor=`[[1],[0]]`, cov_diag=`[1,1]` 2025-07-17T07:36:53.1575492Z tensor([-0.2102, -0.5429]) 2025-07-17T07:36:53.1575567Z 2025-07-17T07:36:53.1575658Z Args: 2025-07-17T07:36:53.1575887Z loc (Tensor): mean of the distribution with shape `batch_shape + event_shape` 2025-07-17T07:36:53.1576226Z cov_factor (Tensor): factor part of low-rank form of covariance matrix with shape 2025-07-17T07:36:53.1576356Z `batch_shape + event_shape + (rank,)` 2025-07-17T07:36:53.1576609Z cov_diag (Tensor): diagonal part of low-rank form of covariance matrix with shape 2025-07-17T07:36:53.1576715Z `batch_shape + event_shape` 2025-07-17T07:36:53.1576804Z 2025-07-17T07:36:53.1576884Z Note: 2025-07-17T07:36:53.1577149Z The computation for determinant and inverse of covariance matrix is avoided when 2025-07-17T07:36:53.1577397Z `cov_factor.shape[1] << cov_factor.shape[0]` thanks to `Woodbury matrix identity 2025-07-17T07:36:53.1577654Z `_ and 2025-07-17T07:36:53.1577963Z `matrix determinant lemma `_. 2025-07-17T07:36:53.1578211Z Thanks to these formulas, we just need to compute the determinant and inverse of 2025-07-17T07:36:53.1578336Z the small size "capacitance" matrix:: 2025-07-17T07:36:53.1578431Z 2025-07-17T07:36:53.1578610Z capacitance = I + cov_factor.T @ inv(cov_diag) @ cov_factor 2025-07-17T07:36:53.1578688Z 2025-07-17T07:36:53.1579018Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1579096Z 2025-07-17T07:36:53.1579208Z warnings.warn(msg) 2025-07-17T07:36:53.1579286Z 2025-07-17T07:36:53.1579476Z --- Parse Warning: 93 / 136 --- 2025-07-17T07:36:53.1580510Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MixtureSameFamily in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/mixture_same_family.py line=15. 2025-07-17T07:36:53.1580776Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1580854Z 2025-07-17T07:36:53.1581101Z The `MixtureSameFamily` distribution implements a (batch of) mixture 2025-07-17T07:36:53.1581400Z distribution where all component are from different parameterizations of 2025-07-17T07:36:53.1581627Z the same distribution type. It is parameterized by a `Categorical` 2025-07-17T07:36:53.1581827Z "selecting distribution" (over `k` component) and a component 2025-07-17T07:36:53.1582034Z distribution, i.e., a `Distribution` with a rightmost batch shape 2025-07-17T07:36:53.1582204Z (equal to `[k]`) which indexes each (batch of) component. 2025-07-17T07:36:53.1582289Z 2025-07-17T07:36:53.1582380Z Examples:: 2025-07-17T07:36:53.1582473Z 2025-07-17T07:36:53.1582591Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:53.1582793Z >>> # Construct Gaussian Mixture Model in 1D consisting of 5 equally 2025-07-17T07:36:53.1582923Z >>> # weighted normal distributions 2025-07-17T07:36:53.1583043Z >>> mix = D.Categorical(torch.ones(5,)) 2025-07-17T07:36:53.1583204Z >>> comp = D.Normal(torch.randn(5,), torch.rand(5,)) 2025-07-17T07:36:53.1583324Z >>> gmm = MixtureSameFamily(mix, comp) 2025-07-17T07:36:53.1583404Z 2025-07-17T07:36:53.1583617Z >>> # Construct Gaussian Mixture Model in 2D consisting of 5 equally 2025-07-17T07:36:53.1583749Z >>> # weighted bivariate normal distributions 2025-07-17T07:36:53.1583866Z >>> mix = D.Categorical(torch.ones(5,)) 2025-07-17T07:36:53.1583991Z >>> comp = D.Independent(D.Normal( 2025-07-17T07:36:53.1584119Z ... torch.randn(5,2), torch.rand(5,2)), 1) 2025-07-17T07:36:53.1584240Z >>> gmm = MixtureSameFamily(mix, comp) 2025-07-17T07:36:53.1584332Z 2025-07-17T07:36:53.1584513Z >>> # Construct a batch of 3 Gaussian Mixture Models in 2D each 2025-07-17T07:36:53.1584725Z >>> # consisting of 5 random weighted bivariate normal distributions 2025-07-17T07:36:53.1584844Z >>> mix = D.Categorical(torch.rand(3,5)) 2025-07-17T07:36:53.1584988Z >>> comp = D.Independent(D.Normal( 2025-07-17T07:36:53.1585133Z ... torch.randn(3,5,2), torch.rand(3,5,2)), 1) 2025-07-17T07:36:53.1585253Z >>> gmm = MixtureSameFamily(mix, comp) 2025-07-17T07:36:53.1585331Z 2025-07-17T07:36:53.1585422Z Args: 2025-07-17T07:36:53.1585627Z mixture_distribution: `torch.distributions.Categorical`-like 2025-07-17T07:36:53.1585810Z instance. Manages the probability of selecting component. 2025-07-17T07:36:53.1585988Z The number of categories must match the rightmost batch 2025-07-17T07:36:53.1586172Z dimension of the `component_distribution`. Must have either 2025-07-17T07:36:53.1586352Z scalar `batch_shape` or `batch_shape` matching 2025-07-17T07:36:53.1586485Z `component_distribution.batch_shape[:-1]` 2025-07-17T07:36:53.1586700Z component_distribution: `torch.distributions.Distribution`-like 2025-07-17T07:36:53.1586886Z instance. Right-most batch dimension indexes component. 2025-07-17T07:36:53.1586965Z 2025-07-17T07:36:53.1587215Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1587304Z 2025-07-17T07:36:53.1587398Z warnings.warn(msg) 2025-07-17T07:36:53.1587474Z 2025-07-17T07:36:53.1587719Z --- Parse Warning: 94 / 136 --- 2025-07-17T07:36:53.1588722Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RelaxedBernoulli in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_bernoulli.py line=120. 2025-07-17T07:36:53.1589003Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1589080Z 2025-07-17T07:36:53.1589286Z Creates a RelaxedBernoulli distribution, parametrized by 2025-07-17T07:36:53.1589487Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits` 2025-07-17T07:36:53.1589704Z (but not both). This is a relaxed version of the `Bernoulli` distribution, 2025-07-17T07:36:53.1589899Z so the values are in (0, 1), and has reparametrizable samples. 2025-07-17T07:36:53.1589976Z 2025-07-17T07:36:53.1590064Z Example:: 2025-07-17T07:36:53.1590153Z 2025-07-17T07:36:53.1590293Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-07-17T07:36:53.1590422Z >>> m = RelaxedBernoulli(torch.tensor([2.2]), 2025-07-17T07:36:53.1590559Z ... torch.tensor([0.1, 0.2, 0.3, 0.99])) 2025-07-17T07:36:53.1590645Z >>> m.sample() 2025-07-17T07:36:53.1590759Z tensor([ 0.2951, 0.3442, 0.8918, 0.9021]) 2025-07-17T07:36:53.1590850Z 2025-07-17T07:36:53.1590931Z Args: 2025-07-17T07:36:53.1591067Z temperature (Tensor): relaxation temperature 2025-07-17T07:36:53.1591245Z probs (Number, Tensor): the probability of sampling `1` 2025-07-17T07:36:53.1591403Z logits (Number, Tensor): the log-odds of sampling `1` 2025-07-17T07:36:53.1591494Z 2025-07-17T07:36:53.1591745Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1591820Z 2025-07-17T07:36:53.1591928Z warnings.warn(msg) 2025-07-17T07:36:53.1592004Z 2025-07-17T07:36:53.1592189Z --- Parse Warning: 95 / 136 --- 2025-07-17T07:36:53.1593262Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RelaxedOneHotCategorical in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_categorical.py line=109. 2025-07-17T07:36:53.1593521Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1593609Z 2025-07-17T07:36:53.1593822Z Creates a RelaxedOneHotCategorical distribution parametrized by 2025-07-17T07:36:53.1594014Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits`. 2025-07-17T07:36:53.1594289Z This is a relaxed version of the :class:`OneHotCategorical` distribution, so 2025-07-17T07:36:53.1594448Z its samples are on simplex, and are reparametrizable. 2025-07-17T07:36:53.1594523Z 2025-07-17T07:36:53.1594620Z Example:: 2025-07-17T07:36:53.1594697Z 2025-07-17T07:36:53.1594836Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-07-17T07:36:53.1595003Z >>> m = RelaxedOneHotCategorical(torch.tensor([2.2]), 2025-07-17T07:36:53.1595128Z ... torch.tensor([0.1, 0.2, 0.3, 0.4])) 2025-07-17T07:36:53.1595227Z >>> m.sample() 2025-07-17T07:36:53.1595340Z tensor([ 0.1294, 0.2324, 0.3859, 0.2523]) 2025-07-17T07:36:53.1595447Z 2025-07-17T07:36:53.1595542Z Args: 2025-07-17T07:36:53.1595680Z temperature (Tensor): relaxation temperature 2025-07-17T07:36:53.1595794Z probs (Tensor): event probabilities 2025-07-17T07:36:53.1595990Z logits (Tensor): unnormalized log probability for each event 2025-07-17T07:36:53.1596069Z 2025-07-17T07:36:53.1596318Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1596407Z 2025-07-17T07:36:53.1596502Z warnings.warn(msg) 2025-07-17T07:36:53.1596577Z 2025-07-17T07:36:53.1596767Z --- Parse Warning: 96 / 136 --- 2025-07-17T07:36:53.1597855Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assoc_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=245. 2025-07-17T07:36:53.1598137Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1598324Z Return a new dict with new, potentially nested, key value pair 2025-07-17T07:36:53.1598402Z 2025-07-17T07:36:53.1598506Z >>> purchase = { 2025-07-17T07:36:53.1598599Z ... "name": "Alice", 2025-07-17T07:36:53.1598770Z ... "order": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-07-17T07:36:53.1598898Z ... "credit card": "5555-1234-1234-1234", 2025-07-17T07:36:53.1598978Z ... } 2025-07-17T07:36:53.1599193Z >>> assoc_in(purchase, ["order", "costs"], [0.25, 1.00]) # doctest: +SKIP 2025-07-17T07:36:53.1599302Z {'credit card': '5555-1234-1234-1234', 2025-07-17T07:36:53.1599392Z 'name': 'Alice', 2025-07-17T07:36:53.1599565Z 'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}} 2025-07-17T07:36:53.1599646Z 2025-07-17T07:36:53.1599897Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1599988Z 2025-07-17T07:36:53.1600082Z warnings.warn(msg) 2025-07-17T07:36:53.1600160Z 2025-07-17T07:36:53.1600351Z --- Parse Warning: 97 / 136 --- 2025-07-17T07:36:53.1601385Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=update_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=261. 2025-07-17T07:36:53.1601660Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1601809Z Update value in a (potentially) nested dictionary 2025-07-17T07:36:53.1601889Z 2025-07-17T07:36:53.1601984Z inputs: 2025-07-17T07:36:53.1602097Z d - dictionary on which to operate 2025-07-17T07:36:53.1602311Z keys - list or tuple giving the location of the value to be changed in d 2025-07-17T07:36:53.1602444Z func - function to operate on that value 2025-07-17T07:36:53.1602523Z 2025-07-17T07:36:53.1602719Z If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the 2025-07-17T07:36:53.1602951Z original dictionary with v replaced by func(v), but does not mutate the 2025-07-17T07:36:53.1603051Z original dictionary. 2025-07-17T07:36:53.1603167Z 2025-07-17T07:36:53.1603372Z If k0 is not a key in d, update_in creates nested dictionaries to the depth 2025-07-17T07:36:53.1603583Z specified by the keys, with the innermost value set to func(default). 2025-07-17T07:36:53.1603673Z 2025-07-17T07:36:53.1603770Z >>> inc = lambda x: x + 1 2025-07-17T07:36:53.1603877Z >>> update_in({"a": 0}, ["a"], inc) 2025-07-17T07:36:53.1603968Z {'a': 1} 2025-07-17T07:36:53.1604044Z 2025-07-17T07:36:53.1604148Z >>> transaction = { 2025-07-17T07:36:53.1604272Z ... "name": "Alice", 2025-07-17T07:36:53.1604455Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-07-17T07:36:53.1604606Z ... "credit card": "5555-1234-1234-1234", 2025-07-17T07:36:53.1604684Z ... } 2025-07-17T07:36:53.1604897Z >>> update_in(transaction, ["purchase", "costs"], sum) # doctest: +SKIP 2025-07-17T07:36:53.1605014Z {'credit card': '5555-1234-1234-1234', 2025-07-17T07:36:53.1605105Z 'name': 'Alice', 2025-07-17T07:36:53.1605271Z 'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}} 2025-07-17T07:36:53.1605436Z 2025-07-17T07:36:53.1605556Z >>> # updating a value when k0 is not in d 2025-07-17T07:36:53.1605697Z >>> update_in({}, [1, 2, 3], str, default="bar") 2025-07-17T07:36:53.1605840Z {1: {2: {3: 'bar'}}} 2025-07-17T07:36:53.1605955Z >>> update_in({1: "foo"}, [2, 3, 4], inc, 0) 2025-07-17T07:36:53.1606062Z {1: 'foo', 2: {3: {4: 1}}} 2025-07-17T07:36:53.1606144Z 2025-07-17T07:36:53.1606395Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1606491Z 2025-07-17T07:36:53.1606586Z warnings.warn(msg) 2025-07-17T07:36:53.1606661Z 2025-07-17T07:36:53.1606861Z --- Parse Warning: 98 / 136 --- 2025-07-17T07:36:53.1607873Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=320. 2025-07-17T07:36:53.1608147Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1608307Z Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys. 2025-07-17T07:36:53.1608387Z 2025-07-17T07:36:53.1608577Z If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless 2025-07-17T07:36:53.1608775Z ``no_default`` is specified, then it raises KeyError or IndexError. 2025-07-17T07:36:53.1608851Z 2025-07-17T07:36:53.1609068Z ``get_in`` is a generalization of ``operator.getitem`` for nested data 2025-07-17T07:36:53.1609196Z structures such as dictionaries and lists. 2025-07-17T07:36:53.1609287Z 2025-07-17T07:36:53.1609379Z >>> transaction = { 2025-07-17T07:36:53.1609470Z ... "name": "Alice", 2025-07-17T07:36:53.1609665Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-07-17T07:36:53.1609779Z ... "credit card": "5555-1234-1234-1234", 2025-07-17T07:36:53.1609859Z ... } 2025-07-17T07:36:53.1610006Z >>> get_in(["purchase", "items", 0], transaction) 2025-07-17T07:36:53.1610088Z 'Apple' 2025-07-17T07:36:53.1610197Z >>> get_in(["name"], transaction) 2025-07-17T07:36:53.1610292Z 'Alice' 2025-07-17T07:36:53.1610418Z >>> get_in(["purchase", "total"], transaction) 2025-07-17T07:36:53.1610566Z >>> get_in(["purchase", "items", "apple"], transaction) 2025-07-17T07:36:53.1610711Z >>> get_in(["purchase", "items", 10], transaction) 2025-07-17T07:36:53.1610848Z >>> get_in(["purchase", "total"], transaction, 0) 2025-07-17T07:36:53.1610941Z 0 2025-07-17T07:36:53.1611050Z >>> get_in(["y"], {}, no_default=True) 2025-07-17T07:36:53.1611162Z Traceback (most recent call last): 2025-07-17T07:36:53.1611258Z ... 2025-07-17T07:36:53.1611390Z KeyError: 'y' 2025-07-17T07:36:53.1611466Z 2025-07-17T07:36:53.1611563Z See Also: 2025-07-17T07:36:53.1611655Z itertoolz.get 2025-07-17T07:36:53.1611751Z operator.getitem 2025-07-17T07:36:53.1611846Z 2025-07-17T07:36:53.1612104Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1612182Z 2025-07-17T07:36:53.1612291Z warnings.warn(msg) 2025-07-17T07:36:53.1612369Z 2025-07-17T07:36:53.1612564Z --- Parse Warning: 99 / 136 --- 2025-07-17T07:36:53.1613595Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=groupby in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=373. 2025-07-17T07:36:53.1613901Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1614030Z Group a collection by a key function 2025-07-17T07:36:53.1614111Z 2025-07-17T07:36:53.1614275Z >>> names = ["Alice", "Bob", "Charlie", "Dan", "Edith", "Frank"] 2025-07-17T07:36:53.1614407Z >>> groupby(len, names) # doctest: +SKIP 2025-07-17T07:36:53.1614564Z {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']} 2025-07-17T07:36:53.1614709Z 2025-07-17T07:36:53.1614816Z >>> iseven = lambda x: x % 2 == 0 2025-07-17T07:36:53.1614980Z >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8]) # doctest: +SKIP 2025-07-17T07:36:53.1615100Z {False: [1, 3, 5, 7], True: [2, 4, 6, 8]} 2025-07-17T07:36:53.1615192Z 2025-07-17T07:36:53.1615329Z Non-callable keys imply grouping on a member. 2025-07-17T07:36:53.1615419Z 2025-07-17T07:36:53.1615505Z >>> groupby( 2025-07-17T07:36:53.1615592Z ... "gender", 2025-07-17T07:36:53.1615683Z ... [ 2025-07-17T07:36:53.1615800Z ... {"name": "Alice", "gender": "F"}, 2025-07-17T07:36:53.1615926Z ... {"name": "Bob", "gender": "M"}, 2025-07-17T07:36:53.1616046Z ... {"name": "Charlie", "gender": "M"}, 2025-07-17T07:36:53.1616126Z ... ], 2025-07-17T07:36:53.1616233Z ... ) # doctest:+SKIP 2025-07-17T07:36:53.1616343Z {'F': [{'gender': 'F', 'name': 'Alice'}], 2025-07-17T07:36:53.1616451Z 'M': [{'gender': 'M', 'name': 'Bob'}, 2025-07-17T07:36:53.1616575Z {'gender': 'M', 'name': 'Charlie'}]} 2025-07-17T07:36:53.1616651Z 2025-07-17T07:36:53.1616790Z Not to be confused with ``itertools.groupby`` 2025-07-17T07:36:53.1616881Z 2025-07-17T07:36:53.1616962Z See Also: 2025-07-17T07:36:53.1617043Z countby 2025-07-17T07:36:53.1617134Z 2025-07-17T07:36:53.1617386Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1617474Z 2025-07-17T07:36:53.1617566Z warnings.warn(msg) 2025-07-17T07:36:53.1617641Z 2025-07-17T07:36:53.1617835Z --- Parse Warning: 100 / 136 --- 2025-07-17T07:36:53.1618688Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=calculate_gain in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py line=142. 2025-07-17T07:36:53.1618952Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1619188Z Return the recommended gain value for the given nonlinearity function. 2025-07-17T07:36:53.1619285Z 2025-07-17T07:36:53.1619390Z The values are as follows: 2025-07-17T07:36:53.1619480Z 2025-07-17T07:36:53.1619591Z ================= ==================================================== 2025-07-17T07:36:53.1619701Z nonlinearity gain 2025-07-17T07:36:53.1619811Z ================= ==================================================== 2025-07-17T07:36:53.1619912Z Linear / Identity :math:`1` 2025-07-17T07:36:53.1620052Z Conv{1,2,3}D :math:`1` 2025-07-17T07:36:53.1620146Z Sigmoid :math:`1` 2025-07-17T07:36:53.1620251Z Tanh :math:`\frac{5}{3}` 2025-07-17T07:36:53.1620362Z ReLU :math:`\sqrt{2}` 2025-07-17T07:36:53.1620554Z Leaky Relu :math:`\sqrt{\frac{2}{1 + \text{negative\_slope}^2}}` 2025-07-17T07:36:53.1620671Z SELU :math:`\frac{3}{4}` 2025-07-17T07:36:53.1620779Z ================= ==================================================== 2025-07-17T07:36:53.1620856Z 2025-07-17T07:36:53.1620957Z .. warning:: 2025-07-17T07:36:53.1621165Z In order to implement `Self-Normalizing Neural Networks`_ , 2025-07-17T07:36:53.1621405Z you should use ``nonlinearity='linear'`` instead of ``nonlinearity='selu'``. 2025-07-17T07:36:53.1621582Z This gives the initial weights a variance of ``1 / N``, 2025-07-17T07:36:53.1621801Z which is necessary to induce a stable fixed point in the forward pass. 2025-07-17T07:36:53.1622022Z In contrast, the default gain for ``SELU`` sacrifices the normalization 2025-07-17T07:36:53.1622217Z effect for more stable gradient flow in rectangular layers. 2025-07-17T07:36:53.1622305Z 2025-07-17T07:36:53.1622395Z Args: 2025-07-17T07:36:53.1622641Z nonlinearity: the non-linear function (`nn.functional` name) 2025-07-17T07:36:53.1622809Z param: optional parameter for the non-linear function 2025-07-17T07:36:53.1622896Z 2025-07-17T07:36:53.1622979Z Examples: 2025-07-17T07:36:53.1623091Z >>> gain = nn.init.calculate_gain( 2025-07-17T07:36:53.1623203Z ... "leaky_relu", 0.2 2025-07-17T07:36:53.1623326Z ... ) # leaky_relu with negative_slope=0.2 2025-07-17T07:36:53.1623402Z 2025-07-17T07:36:53.1623891Z .. _Self-Normalizing Neural Networks: https://papers.nips.cc/paper/2017/hash/5d44ee6f2c3f71b73125876103c8f6c4-Abstract.html 2025-07-17T07:36:53.1623973Z 2025-07-17T07:36:53.1624237Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1624315Z 2025-07-17T07:36:53.1624409Z warnings.warn(msg) 2025-07-17T07:36:53.1624497Z 2025-07-17T07:36:53.1624684Z --- Parse Warning: 101 / 136 --- 2025-07-17T07:36:53.1625604Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyncBatchNorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=601. 2025-07-17T07:36:53.1625878Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1626052Z Applies Batch Normalization over a N-Dimensional input. 2025-07-17T07:36:53.1626141Z 2025-07-17T07:36:53.1626481Z The N-D input is a mini-batch of [N-2]D inputs with additional channel dimension) as described in the paper 2025-07-17T07:36:53.1626709Z `Batch Normalization: Accelerating Deep Network Training by Reducing 2025-07-17T07:36:53.1626931Z Internal Covariate Shift `__ . 2025-07-17T07:36:53.1627007Z 2025-07-17T07:36:53.1627091Z .. math:: 2025-07-17T07:36:53.1627179Z 2025-07-17T07:36:53.1627392Z y = \frac{x - \mathrm{E}[x]}{ \sqrt{\mathrm{Var}[x] + \epsilon}} * \gamma + \beta 2025-07-17T07:36:53.1627469Z 2025-07-17T07:36:53.1627703Z The mean and standard-deviation are calculated per-dimension over all 2025-07-17T07:36:53.1627932Z mini-batches of the same process groups. :math:`\gamma` and :math:`\beta` 2025-07-17T07:36:53.1628184Z are learnable parameter vectors of size `C` (where `C` is the input size). 2025-07-17T07:36:53.1628357Z By default, the elements of :math:`\gamma` are sampled from 2025-07-17T07:36:53.1628553Z :math:`\mathcal{U}(0, 1)` and the elements of :math:`\beta` are set to 0. 2025-07-17T07:36:53.1628888Z The standard-deviation is calculated via the biased estimator, equivalent to 2025-07-17T07:36:53.1629003Z `torch.var(input, unbiased=False)`. 2025-07-17T07:36:53.1629081Z 2025-07-17T07:36:53.1629325Z Also by default, during training this layer keeps running estimates of its 2025-07-17T07:36:53.1629557Z computed mean and variance, which are then used for normalization during 2025-07-17T07:36:53.1629810Z evaluation. The running estimates are kept with a default :attr:`momentum` 2025-07-17T07:36:53.1629890Z of 0.1. 2025-07-17T07:36:53.1629969Z 2025-07-17T07:36:53.1630203Z If :attr:`track_running_stats` is set to ``False``, this layer then does not 2025-07-17T07:36:53.1630449Z keep running estimates, and batch statistics are instead used during 2025-07-17T07:36:53.1630550Z evaluation time as well. 2025-07-17T07:36:53.1630638Z 2025-07-17T07:36:53.1630724Z .. note:: 2025-07-17T07:36:53.1630941Z This :attr:`momentum` argument is different from one used in optimizer 2025-07-17T07:36:53.1631177Z classes and the conventional notion of momentum. Mathematically, the 2025-07-17T07:36:53.1631306Z update rule for running statistics here is 2025-07-17T07:36:53.1631630Z :math:`\hat{x}_\text{new} = (1 - \text{momentum}) \times \hat{x} + \text{momentum} \times x_t`, 2025-07-17T07:36:53.1631834Z where :math:`\hat{x}` is the estimated statistic and :math:`x_t` is the 2025-07-17T07:36:53.1631930Z new observed value. 2025-07-17T07:36:53.1632019Z 2025-07-17T07:36:53.1632317Z Because the Batch Normalization is done for each channel in the ``C`` dimension, computing 2025-07-17T07:36:53.1632563Z statistics on ``(N, +)`` slices, it's common terminology to call this Volumetric Batch 2025-07-17T07:36:53.1632749Z Normalization or Spatio-temporal Batch Normalization. 2025-07-17T07:36:53.1632826Z 2025-07-17T07:36:53.1632979Z Currently :class:`SyncBatchNorm` only supports 2025-07-17T07:36:53.1633261Z :class:`~torch.nn.DistributedDataParallel` (DDP) with single GPU per process. Use 2025-07-17T07:36:53.1633469Z :meth:`torch.nn.SyncBatchNorm.convert_sync_batchnorm()` to convert 2025-07-17T07:36:53.1633684Z :attr:`BatchNorm*D` layer to :class:`SyncBatchNorm` before wrapping 2025-07-17T07:36:53.1633778Z Network with DDP. 2025-07-17T07:36:53.1633855Z 2025-07-17T07:36:53.1633946Z Args: 2025-07-17T07:36:53.1634107Z num_features: :math:`C` from an expected input of size 2025-07-17T07:36:53.1634201Z :math:`(N, C, +)` 2025-07-17T07:36:53.1634397Z eps: a value added to the denominator for numerical stability. 2025-07-17T07:36:53.1634490Z Default: ``1e-5`` 2025-07-17T07:36:53.1634690Z momentum: the value used for the running_mean and running_var 2025-07-17T07:36:53.1634896Z computation. Can be set to ``None`` for cumulative moving average 2025-07-17T07:36:53.1635014Z (i.e. simple average). Default: 0.1 2025-07-17T07:36:53.1635222Z affine: a boolean value that when set to ``True``, this module has 2025-07-17T07:36:53.1635369Z learnable affine parameters. Default: ``True`` 2025-07-17T07:36:53.1635582Z track_running_stats: a boolean value that when set to ``True``, this 2025-07-17T07:36:53.1635818Z module tracks the running mean and variance, and when set to ``False``, 2025-07-17T07:36:53.1636035Z this module does not track such statistics, and initializes statistics 2025-07-17T07:36:53.1636246Z buffers :attr:`running_mean` and :attr:`running_var` as ``None``. 2025-07-17T07:36:53.1636471Z When these buffers are ``None``, this module always uses batch statistics. 2025-07-17T07:36:53.1636620Z in both training and eval modes. Default: ``True`` 2025-07-17T07:36:53.1636879Z process_group: synchronization of stats happen within each process group 2025-07-17T07:36:53.1637130Z individually. Default behavior is synchronization across the whole 2025-07-17T07:36:53.1637228Z world 2025-07-17T07:36:53.1637305Z 2025-07-17T07:36:53.1637390Z Shape: 2025-07-17T07:36:53.1637511Z - Input: :math:`(N, C, +)` 2025-07-17T07:36:53.1637653Z - Output: :math:`(N, C, +)` (same shape as input) 2025-07-17T07:36:53.1637730Z 2025-07-17T07:36:53.1637827Z .. note:: 2025-07-17T07:36:53.1638067Z Synchronization of batchnorm statistics occurs only while training, i.e. 2025-07-17T07:36:53.1638293Z synchronization is disabled when ``model.eval()`` is set or if 2025-07-17T07:36:53.1638431Z ``self.training`` is otherwise ``False``. 2025-07-17T07:36:53.1638507Z 2025-07-17T07:36:53.1638596Z Examples:: 2025-07-17T07:36:53.1638685Z 2025-07-17T07:36:53.1638780Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1638903Z >>> # With Learnable Parameters 2025-07-17T07:36:53.1639007Z >>> m = nn.SyncBatchNorm(100) 2025-07-17T07:36:53.1639127Z >>> # creating process group (optional) 2025-07-17T07:36:53.1639274Z >>> # ranks is a list of int identifying rank ids. 2025-07-17T07:36:53.1639436Z >>> ranks = list(range(8)) 2025-07-17T07:36:53.1639542Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-07-17T07:36:53.1639696Z >>> # Note: every rank calls into new_group for every 2025-07-17T07:36:53.1639841Z >>> # process group created, even if that rank is not 2025-07-17T07:36:53.1639953Z >>> # part of the group. 2025-07-17T07:36:53.1640209Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-07-17T07:36:53.1640409Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-07-17T07:36:53.1640537Z >>> # Without Learnable Parameters 2025-07-17T07:36:53.1640741Z >>> m = nn.BatchNorm3d(100, affine=False, process_group=process_group) 2025-07-17T07:36:53.1640863Z >>> input = torch.randn(20, 100, 35, 45, 10) 2025-07-17T07:36:53.1640976Z >>> output = m(input) 2025-07-17T07:36:53.1641055Z 2025-07-17T07:36:53.1641172Z >>> # network is nn.BatchNorm layer 2025-07-17T07:36:53.1641455Z >>> sync_bn_network = nn.SyncBatchNorm.convert_sync_batchnorm(network, process_group) 2025-07-17T07:36:53.1641612Z >>> # only single gpu per process is currently supported 2025-07-17T07:36:53.1641842Z >>> ddp_sync_bn_network = torch.nn.parallel.DistributedDataParallel( 2025-07-17T07:36:53.1641954Z >>> sync_bn_network, 2025-07-17T07:36:53.1642078Z >>> device_ids=[args.local_rank], 2025-07-17T07:36:53.1642219Z >>> output_device=args.local_rank) 2025-07-17T07:36:53.1642301Z 2025-07-17T07:36:53.1642556Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1642648Z 2025-07-17T07:36:53.1642743Z warnings.warn(msg) 2025-07-17T07:36:53.1642820Z 2025-07-17T07:36:53.1643026Z --- Parse Warning: 102 / 136 --- 2025-07-17T07:36:53.1644067Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyncBatchNorm.convert_sync_batchnorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=825. 2025-07-17T07:36:53.1644342Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1644652Z Converts all :attr:`BatchNorm*D` layers in the model to :class:`torch.nn.SyncBatchNorm` layers. 2025-07-17T07:36:53.1644731Z 2025-07-17T07:36:53.1644828Z Args: 2025-07-17T07:36:53.1645070Z module (nn.Module): module containing one or more :attr:`BatchNorm*D` layers 2025-07-17T07:36:53.1645397Z process_group (optional): process group to scope synchronization, 2025-07-17T07:36:53.1645510Z default is the whole world 2025-07-17T07:36:53.1645589Z 2025-07-17T07:36:53.1645686Z Returns: 2025-07-17T07:36:53.1645939Z The original :attr:`module` with the converted :class:`torch.nn.SyncBatchNorm` 2025-07-17T07:36:53.1646148Z layers. If the original :attr:`module` is a :attr:`BatchNorm*D` layer, 2025-07-17T07:36:53.1646366Z a new :class:`torch.nn.SyncBatchNorm` layer object will be returned 2025-07-17T07:36:53.1646484Z instead. 2025-07-17T07:36:53.1646562Z 2025-07-17T07:36:53.1646663Z Example:: 2025-07-17T07:36:53.1646741Z 2025-07-17T07:36:53.1646872Z >>> # Network with nn.BatchNorm layer 2025-07-17T07:36:53.1647009Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:53.1647124Z >>> module = torch.nn.Sequential( 2025-07-17T07:36:53.1647251Z >>> torch.nn.Linear(20, 100), 2025-07-17T07:36:53.1647367Z >>> torch.nn.BatchNorm1d(100), 2025-07-17T07:36:53.1647456Z >>> ).cuda() 2025-07-17T07:36:53.1647636Z >>> # creating process group (optional) 2025-07-17T07:36:53.1647777Z >>> # ranks is a list of int identifying rank ids. 2025-07-17T07:36:53.1647883Z >>> ranks = list(range(8)) 2025-07-17T07:36:53.1648000Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-07-17T07:36:53.1648145Z >>> # Note: every rank calls into new_group for every 2025-07-17T07:36:53.1648304Z >>> # process group created, even if that rank is not 2025-07-17T07:36:53.1648403Z >>> # part of the group. 2025-07-17T07:36:53.1648519Z >>> # xdoctest: +SKIP("distributed") 2025-07-17T07:36:53.1648778Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-07-17T07:36:53.1648979Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-07-17T07:36:53.1649274Z >>> sync_bn_module = torch.nn.SyncBatchNorm.convert_sync_batchnorm(module, process_group) 2025-07-17T07:36:53.1649358Z 2025-07-17T07:36:53.1649441Z 2025-07-17T07:36:53.1649701Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1649777Z 2025-07-17T07:36:53.1649870Z warnings.warn(msg) 2025-07-17T07:36:53.1649954Z 2025-07-17T07:36:53.1650147Z --- Parse Warning: 103 / 136 --- 2025-07-17T07:36:53.1651033Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Unflatten in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py line=60. 2025-07-17T07:36:53.1651301Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1651377Z 2025-07-17T07:36:53.1651690Z Unflattens a tensor dim expanding it to a desired shape. For use with :class:`~nn.Sequential`. 2025-07-17T07:36:53.1651764Z 2025-07-17T07:36:53.1652027Z * :attr:`dim` specifies the dimension of the input tensor to be unflattened, and it can 2025-07-17T07:36:53.1652257Z be either `int` or `str` when `Tensor` or `NamedTensor` is used, respectively. 2025-07-17T07:36:53.1652332Z 2025-07-17T07:36:53.1652643Z * :attr:`unflattened_size` is the new shape of the unflattened dimension of the tensor and it can be 2025-07-17T07:36:53.1652901Z a `tuple` of ints or a `list` of ints or `torch.Size` for `Tensor` input; a `NamedShape` 2025-07-17T07:36:53.1653066Z (tuple of `(name, size)` tuples) for `NamedTensor` input. 2025-07-17T07:36:53.1653142Z 2025-07-17T07:36:53.1653232Z Shape: 2025-07-17T07:36:53.1653443Z - Input: :math:`(*, S_{\text{dim}}, *)`, where :math:`S_{\text{dim}}` is the size at 2025-07-17T07:36:53.1653736Z dimension :attr:`dim` and :math:`*` means any number of dimensions including none. 2025-07-17T07:36:53.1653945Z - Output: :math:`(*, U_1, ..., U_n, *)`, where :math:`U` = :attr:`unflattened_size` and 2025-07-17T07:36:53.1654066Z :math:`\prod_{i=1}^n U_i = S_{\text{dim}}`. 2025-07-17T07:36:53.1654157Z 2025-07-17T07:36:53.1654236Z Args: 2025-07-17T07:36:53.1654381Z dim (Union[int, str]): Dimension to be unflattened 2025-07-17T07:36:53.1654734Z unflattened_size (Union[torch.Size, Tuple, List, NamedShape]): New shape of the unflattened dimension 2025-07-17T07:36:53.1654839Z 2025-07-17T07:36:53.1654936Z Examples: 2025-07-17T07:36:53.1655040Z >>> input = torch.randn(2, 50) 2025-07-17T07:36:53.1655135Z >>> # With tuple of ints 2025-07-17T07:36:53.1655241Z >>> m = nn.Sequential( 2025-07-17T07:36:53.1655331Z >>> nn.Linear(50, 50), 2025-07-17T07:36:53.1655432Z >>> nn.Unflatten(1, (2, 5, 5)) 2025-07-17T07:36:53.1655523Z >>> ) 2025-07-17T07:36:53.1655614Z >>> output = m(input) 2025-07-17T07:36:53.1655704Z >>> output.size() 2025-07-17T07:36:53.1655810Z torch.Size([2, 2, 5, 5]) 2025-07-17T07:36:53.1655902Z >>> # With torch.Size 2025-07-17T07:36:53.1656043Z >>> m = nn.Sequential( 2025-07-17T07:36:53.1656151Z >>> nn.Linear(50, 50), 2025-07-17T07:36:53.1656272Z >>> nn.Unflatten(1, torch.Size([2, 5, 5])) 2025-07-17T07:36:53.1656360Z >>> ) 2025-07-17T07:36:53.1656451Z >>> output = m(input) 2025-07-17T07:36:53.1656545Z >>> output.size() 2025-07-17T07:36:53.1656650Z torch.Size([2, 2, 5, 5]) 2025-07-17T07:36:53.1656766Z >>> # With namedshape (tuple of tuples) 2025-07-17T07:36:53.1656911Z >>> input = torch.randn(2, 50, names=("N", "features")) 2025-07-17T07:36:53.1657122Z >>> unflatten = nn.Unflatten("features", (("C", 2), ("H", 5), ("W", 5))) 2025-07-17T07:36:53.1657229Z >>> output = unflatten(input) 2025-07-17T07:36:53.1657318Z >>> output.size() 2025-07-17T07:36:53.1657419Z torch.Size([2, 2, 5, 5]) 2025-07-17T07:36:53.1657494Z 2025-07-17T07:36:53.1657741Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1657825Z 2025-07-17T07:36:53.1657924Z warnings.warn(msg) 2025-07-17T07:36:53.1658012Z 2025-07-17T07:36:53.1658197Z --- Parse Warning: 104 / 136 --- 2025-07-17T07:36:53.1659193Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=TripletMarginWithDistanceLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1718. 2025-07-17T07:36:53.1659466Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1659659Z Creates a criterion that measures the triplet loss given input 2025-07-17T07:36:53.1659852Z tensors :math:`a`, :math:`p`, and :math:`n` (representing anchor, 2025-07-17T07:36:53.1660068Z positive, and negative examples, respectively), and a nonnegative, 2025-07-17T07:36:53.1660313Z real-valued function ("distance function") used to compute the relationship 2025-07-17T07:36:53.1660546Z between the anchor and positive example ("positive distance") and the 2025-07-17T07:36:53.1660693Z anchor and negative example ("negative distance"). 2025-07-17T07:36:53.1660770Z 2025-07-17T07:36:53.1660981Z The unreduced loss (i.e., with :attr:`reduction` set to ``'none'``) 2025-07-17T07:36:53.1661080Z can be described as: 2025-07-17T07:36:53.1661157Z 2025-07-17T07:36:53.1661252Z .. math:: 2025-07-17T07:36:53.1661385Z \ell(a, p, n) = L = \{l_1,\dots,l_N\}^\top, \quad 2025-07-17T07:36:53.1661548Z l_i = \max \{d(a_i, p_i) - d(a_i, n_i) + {\rm margin}, 0\} 2025-07-17T07:36:53.1661628Z 2025-07-17T07:36:53.1661900Z where :math:`N` is the batch size; :math:`d` is a nonnegative, real-valued function 2025-07-17T07:36:53.1662201Z quantifying the closeness of two tensors, referred to as the :attr:`distance_function`; 2025-07-17T07:36:53.1662434Z and :math:`margin` is a nonnegative margin representing the minimum difference 2025-07-17T07:36:53.1662678Z between the positive and negative distances that is required for the loss to 2025-07-17T07:36:53.1662910Z be 0. The input tensors have :math:`N` elements each and can be of any shape 2025-07-17T07:36:53.1663028Z that the distance function can handle. 2025-07-17T07:36:53.1663142Z 2025-07-17T07:36:53.1663253Z If :attr:`reduction` is not ``'none'`` 2025-07-17T07:36:53.1663349Z (default ``'mean'``), then: 2025-07-17T07:36:53.1663435Z 2025-07-17T07:36:53.1663516Z .. math:: 2025-07-17T07:36:53.1663601Z \ell(x, y) = 2025-07-17T07:36:53.1663699Z \begin{cases} 2025-07-17T07:36:53.1663897Z \operatorname{mean}(L), & \text{if reduction} = \text{`mean';}\\ 2025-07-17T07:36:53.1664081Z \operatorname{sum}(L), & \text{if reduction} = \text{`sum'.} 2025-07-17T07:36:53.1664174Z \end{cases} 2025-07-17T07:36:53.1664252Z 2025-07-17T07:36:53.1664528Z See also :class:`~torch.nn.TripletMarginLoss`, which computes the triplet 2025-07-17T07:36:53.1664784Z loss for input tensors using the :math:`l_p` distance as the distance function. 2025-07-17T07:36:53.1664862Z 2025-07-17T07:36:53.1664951Z Args: 2025-07-17T07:36:53.1665222Z distance_function (Callable, optional): A nonnegative, real-valued function that 2025-07-17T07:36:53.1665409Z quantifies the closeness of two tensors. If not specified, 2025-07-17T07:36:53.1665580Z `nn.PairwiseDistance` will be used. Default: ``None`` 2025-07-17T07:36:53.1665844Z margin (float, optional): A nonnegative margin representing the minimum difference 2025-07-17T07:36:53.1666112Z between the positive and negative distances required for the loss to be 0. Larger 2025-07-17T07:36:53.1666395Z margins penalize cases where the negative examples are not distant enough from the 2025-07-17T07:36:53.1666569Z anchors, relative to the positives. Default: :math:`1`. 2025-07-17T07:36:53.1666824Z swap (bool, optional): Whether to use the distance swap described in the paper 2025-07-17T07:36:53.1667077Z `Learning shallow convolutional feature descriptors with triplet losses` by 2025-07-17T07:36:53.1667305Z V. Balntas, E. Riba et al. If True, and if the positive example is closer to the 2025-07-17T07:36:53.1667580Z negative example than the anchor is, swaps the positive example and the anchor in 2025-07-17T07:36:53.1667711Z the loss computation. Default: ``False``. 2025-07-17T07:36:53.1668008Z reduction (str, optional): Specifies the (optional) reduction to apply to the output: 2025-07-17T07:36:53.1668191Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-07-17T07:36:53.1668368Z ``'mean'``: the sum of the output will be divided by the number of 2025-07-17T07:36:53.1668612Z elements in the output, ``'sum'``: the output will be summed. Default: ``'mean'`` 2025-07-17T07:36:53.1668691Z 2025-07-17T07:36:53.1668766Z 2025-07-17T07:36:53.1668858Z Shape: 2025-07-17T07:36:53.1669092Z - Input: :math:`(N, *)` where :math:`*` represents any number of additional dimensions 2025-07-17T07:36:53.1669231Z as supported by the distance function. 2025-07-17T07:36:53.1669476Z - Output: A Tensor of shape :math:`(N)` if :attr:`reduction` is ``'none'``, or a scalar 2025-07-17T07:36:53.1669578Z otherwise. 2025-07-17T07:36:53.1669665Z 2025-07-17T07:36:53.1674616Z Examples: 2025-07-17T07:36:53.1674861Z 2025-07-17T07:36:53.1674978Z >>> # Initialize embeddings 2025-07-17T07:36:53.1675111Z >>> embedding = nn.Embedding(1000, 128) 2025-07-17T07:36:53.1675241Z >>> anchor_ids = torch.randint(0, 1000, (1,)) 2025-07-17T07:36:53.1675386Z >>> positive_ids = torch.randint(0, 1000, (1,)) 2025-07-17T07:36:53.1675517Z >>> negative_ids = torch.randint(0, 1000, (1,)) 2025-07-17T07:36:53.1675630Z >>> anchor = embedding(anchor_ids) 2025-07-17T07:36:53.1675764Z >>> positive = embedding(positive_ids) 2025-07-17T07:36:53.1675877Z >>> negative = embedding(negative_ids) 2025-07-17T07:36:53.1676000Z >>> 2025-07-17T07:36:53.1676119Z >>> # Built-in Distance Function 2025-07-17T07:36:53.1676215Z >>> triplet_loss = \ 2025-07-17T07:36:53.1676503Z >>> nn.TripletMarginWithDistanceLoss(distance_function=nn.PairwiseDistance()) 2025-07-17T07:36:53.1676673Z >>> output = triplet_loss(anchor, positive, negative) 2025-07-17T07:36:53.1676775Z >>> output.backward() 2025-07-17T07:36:53.1676868Z >>> 2025-07-17T07:36:53.1676971Z >>> # Custom Distance Function 2025-07-17T07:36:53.1677069Z >>> def l_infinity(x1, x2): 2025-07-17T07:36:53.1677235Z >>> return torch.max(torch.abs(x1 - x2), dim=1).values 2025-07-17T07:36:53.1677402Z >>> 2025-07-17T07:36:53.1677589Z >>> # xdoctest: +SKIP("FIXME: Would call backwards a second time") 2025-07-17T07:36:53.1677698Z >>> triplet_loss = ( 2025-07-17T07:36:53.1677979Z >>> nn.TripletMarginWithDistanceLoss(distance_function=l_infinity, margin=1.5)) 2025-07-17T07:36:53.1678147Z >>> output = triplet_loss(anchor, positive, negative) 2025-07-17T07:36:53.1678247Z >>> output.backward() 2025-07-17T07:36:53.1678327Z >>> 2025-07-17T07:36:53.1678457Z >>> # Custom Distance Function (Lambda) 2025-07-17T07:36:53.1678549Z >>> triplet_loss = ( 2025-07-17T07:36:53.1678680Z >>> nn.TripletMarginWithDistanceLoss( 2025-07-17T07:36:53.1678910Z >>> distance_function=lambda x, y: 1.0 - F.cosine_similarity(x, y))) 2025-07-17T07:36:53.1679060Z >>> output = triplet_loss(anchor, positive, negative) 2025-07-17T07:36:53.1679158Z >>> output.backward() 2025-07-17T07:36:53.1679249Z 2025-07-17T07:36:53.1679340Z Reference: 2025-07-17T07:36:53.1679646Z V. Balntas, et al.: Learning shallow convolutional feature descriptors with triplet losses: 2025-07-17T07:36:53.1679877Z https://bmva-archive.org.uk/bmvc/2016/papers/paper119/index.html 2025-07-17T07:36:53.1679957Z 2025-07-17T07:36:53.1680229Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 17)) 2025-07-17T07:36:53.1680309Z 2025-07-17T07:36:53.1680403Z warnings.warn(msg) 2025-07-17T07:36:53.1680493Z 2025-07-17T07:36:53.1680726Z --- Parse Warning: 105 / 136 --- 2025-07-17T07:36:53.1681600Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CTCLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1852. 2025-07-17T07:36:53.1681890Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1682037Z The Connectionist Temporal Classification loss. 2025-07-17T07:36:53.1682124Z 2025-07-17T07:36:53.1682503Z Calculates loss between a continuous (unsegmented) time series and a target sequence. CTCLoss sums over the 2025-07-17T07:36:53.1682853Z probability of possible alignments of input to target, producing a loss value which is differentiable 2025-07-17T07:36:53.1683203Z with respect to each input node. The alignment of input to target is assumed to be "many-to-one", which 2025-07-17T07:36:53.1683495Z limits the length of the target sequence such that it must be :math:`\leq` the input length. 2025-07-17T07:36:53.1683571Z 2025-07-17T07:36:53.1683698Z Args: 2025-07-17T07:36:53.1683862Z blank (int, optional): blank label. Default :math:`0`. 2025-07-17T07:36:53.1684114Z reduction (str, optional): Specifies the reduction to apply to the output: 2025-07-17T07:36:53.1684295Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-07-17T07:36:53.1684496Z ``'mean'``: the output losses will be divided by the target lengths and 2025-07-17T07:36:53.1684747Z then the mean over the batch is taken, ``'sum'``: the output losses will be summed. 2025-07-17T07:36:53.1684842Z Default: ``'mean'`` 2025-07-17T07:36:53.1684983Z zero_infinity (bool, optional): 2025-07-17T07:36:53.1685188Z Whether to zero infinite losses and the associated gradients. 2025-07-17T07:36:53.1685282Z Default: ``False`` 2025-07-17T07:36:53.1685573Z Infinite losses mainly occur when the inputs are too short 2025-07-17T07:36:53.1685687Z to be aligned to the targets. 2025-07-17T07:36:53.1685762Z 2025-07-17T07:36:53.1685857Z Shape: 2025-07-17T07:36:53.1686039Z - Log_probs: Tensor of size :math:`(T, N, C)` or :math:`(T, C)`, 2025-07-17T07:36:53.1686162Z where :math:`T = \text{input length}`, 2025-07-17T07:36:53.1686344Z :math:`N = \text{batch size}`, and 2025-07-17T07:36:53.1686502Z :math:`C = \text{number of classes (including blank)}`. 2025-07-17T07:36:53.1686741Z The logarithmized probabilities of the outputs (e.g. obtained with 2025-07-17T07:36:53.1686874Z :func:`torch.nn.functional.log_softmax`). 2025-07-17T07:36:53.1687005Z - Targets: Tensor of size :math:`(N, S)` or 2025-07-17T07:36:53.1687175Z :math:`(\operatorname{sum}(\text{target\_lengths}))`, 2025-07-17T07:36:53.1687293Z where :math:`N = \text{batch size}` and 2025-07-17T07:36:53.1687450Z :math:`S = \text{max target length, if shape is } (N, S)`. 2025-07-17T07:36:53.1687661Z It represents the target sequences. Each element in the target 2025-07-17T07:36:53.1687896Z sequence is a class index. And the target index cannot be blank (default=0). 2025-07-17T07:36:53.1688063Z In the :math:`(N, S)` form, targets are padded to the 2025-07-17T07:36:53.1688199Z length of the longest sequence, and stacked. 2025-07-17T07:36:53.1688382Z In the :math:`(\operatorname{sum}(\text{target\_lengths}))` form, 2025-07-17T07:36:53.1688530Z the targets are assumed to be un-padded and 2025-07-17T07:36:53.1688648Z concatenated within 1 dimension. 2025-07-17T07:36:53.1688851Z - Input_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-07-17T07:36:53.1689062Z where :math:`N = \text{batch size}`. It represents the lengths of the 2025-07-17T07:36:53.1689261Z inputs (must each be :math:`\leq T`). And the lengths are specified 2025-07-17T07:36:53.1689502Z for each sequence to achieve masking under the assumption that sequences 2025-07-17T07:36:53.1689615Z are padded to equal lengths. 2025-07-17T07:36:53.1689820Z - Target_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-07-17T07:36:53.1690045Z where :math:`N = \text{batch size}`. It represents lengths of the targets. 2025-07-17T07:36:53.1690263Z Lengths are specified for each sequence to achieve masking under the 2025-07-17T07:36:53.1690503Z assumption that sequences are padded to equal lengths. If target shape is 2025-07-17T07:36:53.1690685Z :math:`(N,S)`, target_lengths are effectively the stop index 2025-07-17T07:36:53.1690931Z :math:`s_n` for each target sequence, such that ``target_n = targets[n,0:s_n]`` for 2025-07-17T07:36:53.1691114Z each target in a batch. Lengths must each be :math:`\leq S` 2025-07-17T07:36:53.1691380Z If the targets are given as a 1d tensor that is the concatenation of individual 2025-07-17T07:36:53.1691611Z targets, the target_lengths must add up to the total length of the tensor. 2025-07-17T07:36:53.1691808Z - Output: scalar if :attr:`reduction` is ``'mean'`` (default) or 2025-07-17T07:36:53.1692036Z ``'sum'``. If :attr:`reduction` is ``'none'``, then :math:`(N)` if input is batched or 2025-07-17T07:36:53.1692230Z :math:`()` if input is unbatched, where :math:`N = \text{batch size}`. 2025-07-17T07:36:53.1692319Z 2025-07-17T07:36:53.1692427Z Examples: 2025-07-17T07:36:53.1692514Z 2025-07-17T07:36:53.1692622Z >>> # Target are to be padded 2025-07-17T07:36:53.1692729Z >>> T = 50 # Input sequence length 2025-07-17T07:36:53.1692875Z >>> C = 20 # Number of classes (including blank) 2025-07-17T07:36:53.1692970Z >>> N = 16 # Batch size 2025-07-17T07:36:53.1693193Z >>> S = 30 # Target sequence length of longest target in batch (padding length) 2025-07-17T07:36:53.1693386Z >>> S_min = 10 # Minimum target length, for demonstration purposes 2025-07-17T07:36:53.1693466Z >>> 2025-07-17T07:36:53.1693707Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-07-17T07:36:53.1693926Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-07-17T07:36:53.1694005Z >>> 2025-07-17T07:36:53.1694207Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-07-17T07:36:53.1694422Z >>> target = torch.randint(low=1, high=C, size=(N, S), dtype=torch.long) 2025-07-17T07:36:53.1694501Z >>> 2025-07-17T07:36:53.1694728Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-07-17T07:36:53.1694843Z >>> target_lengths = torch.randint( 2025-07-17T07:36:53.1694936Z ... low=S_min, 2025-07-17T07:36:53.1695034Z ... high=S, 2025-07-17T07:36:53.1695122Z ... size=(N,), 2025-07-17T07:36:53.1695234Z ... dtype=torch.long, 2025-07-17T07:36:53.1695315Z ... ) 2025-07-17T07:36:53.1695416Z >>> ctc_loss = nn.CTCLoss() 2025-07-17T07:36:53.1695610Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-07-17T07:36:53.1695707Z >>> loss.backward() 2025-07-17T07:36:53.1695786Z >>> 2025-07-17T07:36:53.1695878Z >>> 2025-07-17T07:36:53.1695990Z >>> # Target are to be un-padded 2025-07-17T07:36:53.1696100Z >>> T = 50 # Input sequence length 2025-07-17T07:36:53.1696244Z >>> C = 20 # Number of classes (including blank) 2025-07-17T07:36:53.1696338Z >>> N = 16 # Batch size 2025-07-17T07:36:53.1696416Z >>> 2025-07-17T07:36:53.1696623Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-07-17T07:36:53.1696829Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-07-17T07:36:53.1697052Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-07-17T07:36:53.1697131Z >>> 2025-07-17T07:36:53.1697324Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-07-17T07:36:53.1697567Z >>> target_lengths = torch.randint(low=1, high=T, size=(N,), dtype=torch.long) 2025-07-17T07:36:53.1697667Z >>> target = torch.randint( 2025-07-17T07:36:53.1697758Z ... low=1, 2025-07-17T07:36:53.1697857Z ... high=C, 2025-07-17T07:36:53.1697966Z ... size=(sum(target_lengths),), 2025-07-17T07:36:53.1698071Z ... dtype=torch.long, 2025-07-17T07:36:53.1698148Z ... ) 2025-07-17T07:36:53.1698246Z >>> ctc_loss = nn.CTCLoss() 2025-07-17T07:36:53.1698438Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-07-17T07:36:53.1698559Z >>> loss.backward() 2025-07-17T07:36:53.1698636Z >>> 2025-07-17T07:36:53.1698727Z >>> 2025-07-17T07:36:53.1698907Z >>> # Target are to be un-padded and unbatched (effectively N=1) 2025-07-17T07:36:53.1699021Z >>> T = 50 # Input sequence length 2025-07-17T07:36:53.1699167Z >>> C = 20 # Number of classes (including blank) 2025-07-17T07:36:53.1699245Z >>> 2025-07-17T07:36:53.1699447Z >>> # Initialize random batch of input vectors, for *size = (T,C) 2025-07-17T07:36:53.1699605Z >>> # xdoctest: +SKIP("FIXME: error in doctest") 2025-07-17T07:36:53.1699802Z >>> input = torch.randn(T, C).log_softmax(1).detach().requires_grad_() 2025-07-17T07:36:53.1699964Z >>> input_lengths = torch.tensor(T, dtype=torch.long) 2025-07-17T07:36:53.1700044Z >>> 2025-07-17T07:36:53.1700233Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-07-17T07:36:53.1700473Z >>> target_lengths = torch.randint(low=1, high=T, size=(), dtype=torch.long) 2025-07-17T07:36:53.1700575Z >>> target = torch.randint( 2025-07-17T07:36:53.1700660Z ... low=1, 2025-07-17T07:36:53.1700757Z ... high=C, 2025-07-17T07:36:53.1700909Z ... size=(target_lengths,), 2025-07-17T07:36:53.1701022Z ... dtype=torch.long, 2025-07-17T07:36:53.1701101Z ... ) 2025-07-17T07:36:53.1701201Z >>> ctc_loss = nn.CTCLoss() 2025-07-17T07:36:53.1701392Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-07-17T07:36:53.1701489Z >>> loss.backward() 2025-07-17T07:36:53.1701563Z 2025-07-17T07:36:53.1701659Z Reference: 2025-07-17T07:36:53.1701831Z A. Graves et al.: Connectionist Temporal Classification: 2025-07-17T07:36:53.1702057Z Labelling Unsegmented Sequence Data with Recurrent Neural Networks: 2025-07-17T07:36:53.1702228Z https://www.cs.toronto.edu/~graves/icml_2006.pdf 2025-07-17T07:36:53.1702311Z 2025-07-17T07:36:53.1702403Z Note: 2025-07-17T07:36:53.1702641Z In order to use CuDNN, the following must be satisfied: :attr:`targets` must be 2025-07-17T07:36:53.1702893Z in concatenated format, all :attr:`input_lengths` must be `T`. :math:`blank=0`, 2025-07-17T07:36:53.1703119Z :attr:`target_lengths` :math:`\leq 256`, the integer arguments must be of 2025-07-17T07:36:53.1703224Z dtype :attr:`torch.int32`. 2025-07-17T07:36:53.1703299Z 2025-07-17T07:36:53.1703576Z The regular implementation uses the (more common in PyTorch) `torch.long` dtype. 2025-07-17T07:36:53.1703654Z 2025-07-17T07:36:53.1703729Z 2025-07-17T07:36:53.1703822Z Note: 2025-07-17T07:36:53.1704061Z In some circumstances when using the CUDA backend with CuDNN, this operator 2025-07-17T07:36:53.1704327Z may select a nondeterministic algorithm to increase performance. If this is 2025-07-17T07:36:53.1704566Z undesirable, you can try to make the operation deterministic (potentially at 2025-07-17T07:36:53.1704799Z a performance cost) by setting ``torch.backends.cudnn.deterministic = 2025-07-17T07:36:53.1704897Z True``. 2025-07-17T07:36:53.1705092Z Please see the notes on :doc:`/notes/randomness` for background. 2025-07-17T07:36:53.1705168Z 2025-07-17T07:36:53.1705430Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1705509Z 2025-07-17T07:36:53.1705614Z warnings.warn(msg) 2025-07-17T07:36:53.1705692Z 2025-07-17T07:36:53.1705903Z --- Parse Warning: 106 / 136 --- 2025-07-17T07:36:53.1706821Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MaxUnpool2d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py line=406. 2025-07-17T07:36:53.1707117Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1707268Z Computes a partial inverse of :class:`MaxPool2d`. 2025-07-17T07:36:53.1707360Z 2025-07-17T07:36:53.1707622Z :class:`MaxPool2d` is not fully invertible, since the non-maximal values are lost. 2025-07-17T07:36:53.1707713Z 2025-07-17T07:36:53.1707937Z :class:`MaxUnpool2d` takes in as input the output of :class:`MaxPool2d` 2025-07-17T07:36:53.1708174Z including the indices of the maximal values and computes a partial inverse 2025-07-17T07:36:53.1708367Z in which all non-maximal values are set to zero. 2025-07-17T07:36:53.1708446Z 2025-07-17T07:36:53.1708525Z Note: 2025-07-17T07:36:53.1708853Z This operation may behave nondeterministically when the input indices has repeat values. 2025-07-17T07:36:53.1709231Z See https://github.com/pytorch/pytorch/issues/80827 and :doc:`/notes/randomness` for more information. 2025-07-17T07:36:53.1709308Z 2025-07-17T07:36:53.1709551Z .. note:: :class:`MaxPool2d` can map several input sizes to the same output 2025-07-17T07:36:53.1709719Z sizes. Hence, the inversion process can get ambiguous. 2025-07-17T07:36:53.1709965Z To accommodate this, you can provide the needed output size 2025-07-17T07:36:53.1710172Z as an additional argument :attr:`output_size` in the forward call. 2025-07-17T07:36:53.1710291Z See the Inputs and Example below. 2025-07-17T07:36:53.1710380Z 2025-07-17T07:36:53.1710459Z Args: 2025-07-17T07:36:53.1710637Z kernel_size (int or tuple): Size of the max pooling window. 2025-07-17T07:36:53.1710813Z stride (int or tuple): Stride of the max pooling window. 2025-07-17T07:36:53.1710943Z It is set to :attr:`kernel_size` by default. 2025-07-17T07:36:53.1711134Z padding (int or tuple): Padding that was added to the input 2025-07-17T07:36:53.1711209Z 2025-07-17T07:36:53.1711291Z Inputs: 2025-07-17T07:36:53.1711424Z - `input`: the input Tensor to invert 2025-07-17T07:36:53.1711627Z - `indices`: the indices given out by :class:`~torch.nn.MaxPool2d` 2025-07-17T07:36:53.1711780Z - `output_size` (optional): the targeted output size 2025-07-17T07:36:53.1711868Z 2025-07-17T07:36:53.1711950Z Shape: 2025-07-17T07:36:53.1712129Z - Input: :math:`(N, C, H_{in}, W_{in})` or :math:`(C, H_{in}, W_{in})`. 2025-07-17T07:36:53.1712350Z - Output: :math:`(N, C, H_{out}, W_{out})` or :math:`(C, H_{out}, W_{out})`, where 2025-07-17T07:36:53.1712428Z 2025-07-17T07:36:53.1712531Z .. math:: 2025-07-17T07:36:53.1712792Z H_{out} = (H_{in} - 1) \times \text{stride[0]} - 2 \times \text{padding[0]} + \text{kernel\_size[0]} 2025-07-17T07:36:53.1712872Z 2025-07-17T07:36:53.1712966Z .. math:: 2025-07-17T07:36:53.1713212Z W_{out} = (W_{in} - 1) \times \text{stride[1]} - 2 \times \text{padding[1]} + \text{kernel\_size[1]} 2025-07-17T07:36:53.1713288Z 2025-07-17T07:36:53.1713457Z or as given by :attr:`output_size` in the call operator 2025-07-17T07:36:53.1713539Z 2025-07-17T07:36:53.1713620Z Example:: 2025-07-17T07:36:53.1713707Z 2025-07-17T07:36:53.1713862Z >>> pool = nn.MaxPool2d(2, stride=2, return_indices=True) 2025-07-17T07:36:53.1713991Z >>> unpool = nn.MaxUnpool2d(2, stride=2) 2025-07-17T07:36:53.1714121Z >>> input = torch.tensor([[[[ 1., 2., 3., 4.], 2025-07-17T07:36:53.1714225Z [ 5., 6., 7., 8.], 2025-07-17T07:36:53.1714342Z [ 9., 10., 11., 12.], 2025-07-17T07:36:53.1714447Z [13., 14., 15., 16.]]]]) 2025-07-17T07:36:53.1714588Z >>> output, indices = pool(input) 2025-07-17T07:36:53.1714704Z >>> unpool(output, indices) 2025-07-17T07:36:53.1714805Z tensor([[[[ 0., 0., 0., 0.], 2025-07-17T07:36:53.1714944Z [ 0., 6., 0., 8.], 2025-07-17T07:36:53.1715049Z [ 0., 0., 0., 0.], 2025-07-17T07:36:53.1715151Z [ 0., 14., 0., 16.]]]]) 2025-07-17T07:36:53.1715368Z >>> # Now using output_size to resolve an ambiguous size for the inverse 2025-07-17T07:36:53.1715506Z >>> input = torch.tensor([[[[ 1., 2., 3., 4., 5.], 2025-07-17T07:36:53.1715637Z [ 6., 7., 8., 9., 10.], 2025-07-17T07:36:53.1715755Z [11., 12., 13., 14., 15.], 2025-07-17T07:36:53.1715862Z [16., 17., 18., 19., 20.]]]]) 2025-07-17T07:36:53.1715974Z >>> output, indices = pool(input) 2025-07-17T07:36:53.1716153Z >>> # This call will not work without specifying output_size 2025-07-17T07:36:53.1716308Z >>> unpool(output, indices, output_size=input.size()) 2025-07-17T07:36:53.1716426Z tensor([[[[ 0., 0., 0., 0., 0.], 2025-07-17T07:36:53.1716521Z [ 0., 7., 0., 9., 0.], 2025-07-17T07:36:53.1716664Z [ 0., 0., 0., 0., 0.], 2025-07-17T07:36:53.1716776Z [ 0., 17., 0., 19., 0.]]]]) 2025-07-17T07:36:53.1716854Z 2025-07-17T07:36:53.1716928Z 2025-07-17T07:36:53.1717017Z 2025-07-17T07:36:53.1717271Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1717350Z 2025-07-17T07:36:53.1717457Z warnings.warn(msg) 2025-07-17T07:36:53.1717533Z 2025-07-17T07:36:53.1717725Z --- Parse Warning: 107 / 136 --- 2025-07-17T07:36:53.1718643Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=EmbeddingBag in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py line=272. 2025-07-17T07:36:53.1718911Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1719239Z Compute sums or means of 'bags' of embeddings, without instantiating the intermediate embeddings. 2025-07-17T07:36:53.1719316Z 2025-07-17T07:36:53.1719686Z For bags of constant length, no :attr:`per_sample_weights`, no indices equal to :attr:`padding_idx`, 2025-07-17T07:36:53.1719805Z and with 2D inputs, this class 2025-07-17T07:36:53.1719884Z 2025-07-17T07:36:53.1720185Z * with ``mode="sum"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.sum(dim=1)``, 2025-07-17T07:36:53.1720503Z * with ``mode="mean"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.mean(dim=1)``, 2025-07-17T07:36:53.1720798Z * with ``mode="max"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.max(dim=1)``. 2025-07-17T07:36:53.1720887Z 2025-07-17T07:36:53.1721237Z However, :class:`~torch.nn.EmbeddingBag` is much more time and memory efficient than using a chain of these 2025-07-17T07:36:53.1721322Z operations. 2025-07-17T07:36:53.1721409Z 2025-07-17T07:36:53.1721667Z EmbeddingBag also supports per-sample weights as an argument to the forward 2025-07-17T07:36:53.1721898Z pass. This scales the output of the Embedding before performing a weighted 2025-07-17T07:36:53.1722153Z reduction as specified by ``mode``. If :attr:`per_sample_weights` is passed, the 2025-07-17T07:36:53.1722382Z only supported ``mode`` is ``"sum"``, which computes a weighted sum according to 2025-07-17T07:36:53.1722497Z :attr:`per_sample_weights`. 2025-07-17T07:36:53.1722573Z 2025-07-17T07:36:53.1722651Z Args: 2025-07-17T07:36:53.1722842Z num_embeddings (int): size of the dictionary of embeddings 2025-07-17T07:36:53.1723037Z embedding_dim (int): the size of each embedding vector 2025-07-17T07:36:53.1723346Z max_norm (float, optional): If given, each embedding vector with norm larger than :attr:`max_norm` 2025-07-17T07:36:53.1723507Z is renormalized to have norm :attr:`max_norm`. 2025-07-17T07:36:53.1723843Z norm_type (float, optional): The p of the p-norm to compute for the :attr:`max_norm` option. Default ``2``. 2025-07-17T07:36:53.1724175Z scale_grad_by_freq (bool, optional): if given, this will scale gradients by the inverse of frequency of 2025-07-17T07:36:53.1724363Z the words in the mini-batch. Default ``False``. 2025-07-17T07:36:53.1724540Z Note: this option is not supported when ``mode="max"``. 2025-07-17T07:36:53.1724793Z mode (str, optional): ``"sum"``, ``"mean"`` or ``"max"``. Specifies the way to reduce the bag. 2025-07-17T07:36:53.1725010Z ``"sum"`` computes the weighted sum, taking :attr:`per_sample_weights` 2025-07-17T07:36:53.1725231Z into consideration. ``"mean"`` computes the average of the values 2025-07-17T07:36:53.1725536Z in the bag, ``"max"`` computes the max value over each bag. 2025-07-17T07:36:53.1725653Z Default: ``"mean"`` 2025-07-17T07:36:53.1725981Z sparse (bool, optional): if ``True``, gradient w.r.t. :attr:`weight` matrix will be a sparse tensor. See 2025-07-17T07:36:53.1726234Z Notes for more details regarding sparse gradients. Note: this option is not 2025-07-17T07:36:53.1726358Z supported when ``mode="max"``. 2025-07-17T07:36:53.1726739Z include_last_offset (bool, optional): if ``True``, :attr:`offsets` has one additional element, where the last element 2025-07-17T07:36:53.1726956Z is equivalent to the size of `indices`. This matches the CSR format. 2025-07-17T07:36:53.1727298Z padding_idx (int, optional): If specified, the entries at :attr:`padding_idx` do not contribute to the 2025-07-17T07:36:53.1727569Z gradient; therefore, the embedding vector at :attr:`padding_idx` is not updated 2025-07-17T07:36:53.1727811Z during training, i.e. it remains as a fixed "pad". For a newly constructed 2025-07-17T07:36:53.1728090Z EmbeddingBag, the embedding vector at :attr:`padding_idx` will default to all 2025-07-17T07:36:53.1728328Z zeros, but can be updated to another value to be used as the padding vector. 2025-07-17T07:36:53.1728585Z Note that the embedding vector at :attr:`padding_idx` is excluded from the 2025-07-17T07:36:53.1728692Z reduction. 2025-07-17T07:36:53.1728768Z 2025-07-17T07:36:53.1728921Z Attributes: 2025-07-17T07:36:53.1729231Z weight (Tensor): the learnable weights of the module of shape `(num_embeddings, embedding_dim)` 2025-07-17T07:36:53.1729382Z initialized from :math:`\mathcal{N}(0, 1)`. 2025-07-17T07:36:53.1729457Z 2025-07-17T07:36:53.1729545Z Examples:: 2025-07-17T07:36:53.1729630Z 2025-07-17T07:36:53.1729794Z >>> # an EmbeddingBag module containing 10 tensors of size 3 2025-07-17T07:36:53.1729951Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum') 2025-07-17T07:36:53.1730085Z >>> # a batch of 2 samples of 4 indices each 2025-07-17T07:36:53.1730266Z >>> input = torch.tensor([1, 2, 4, 5, 4, 3, 2, 9], dtype=torch.long) 2025-07-17T07:36:53.1730408Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-07-17T07:36:53.1730587Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-07-17T07:36:53.1730698Z >>> embedding_sum(input, offsets) 2025-07-17T07:36:53.1730816Z tensor([[-0.8861, -5.4350, -0.0523], 2025-07-17T07:36:53.1730912Z [ 1.1306, -2.5798, -1.0044]]) 2025-07-17T07:36:53.1730993Z 2025-07-17T07:36:53.1731112Z >>> # Example with padding_idx 2025-07-17T07:36:53.1731314Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum', padding_idx=2) 2025-07-17T07:36:53.1731493Z >>> input = torch.tensor([2, 2, 2, 2, 4, 3, 2, 9], dtype=torch.long) 2025-07-17T07:36:53.1731673Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-07-17T07:36:53.1731781Z >>> embedding_sum(input, offsets) 2025-07-17T07:36:53.1731881Z tensor([[ 0.0000, 0.0000, 0.0000], 2025-07-17T07:36:53.1731986Z [-0.7082, 3.2145, -2.6251]]) 2025-07-17T07:36:53.1732066Z 2025-07-17T07:36:53.1732248Z >>> # An EmbeddingBag can be loaded from an Embedding like so 2025-07-17T07:36:53.1732389Z >>> embedding = nn.Embedding(10, 3, padding_idx=2) 2025-07-17T07:36:53.1732545Z >>> embedding_sum = nn.EmbeddingBag.from_pretrained( 2025-07-17T07:36:53.1732704Z embedding.weight, 2025-07-17T07:36:53.1732830Z padding_idx=embedding.padding_idx, 2025-07-17T07:36:53.1732920Z mode='sum') 2025-07-17T07:36:53.1733011Z 2025-07-17T07:36:53.1733263Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1733341Z 2025-07-17T07:36:53.1733444Z warnings.warn(msg) 2025-07-17T07:36:53.1733518Z 2025-07-17T07:36:53.1733733Z --- Parse Warning: 108 / 136 --- 2025-07-17T07:36:53.1734700Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Transformer.forward in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py line=186. 2025-07-17T07:36:53.1734963Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1735125Z Take in and process masked source/target sequences. 2025-07-17T07:36:53.1735203Z 2025-07-17T07:36:53.1735297Z .. note:: 2025-07-17T07:36:53.1735387Z 2025-07-17T07:36:53.1735772Z If a boolean tensor is provided for any of the [src/tgt/memory]_mask arguments, positions with a ``True`` value are 2025-07-17T07:36:53.1735923Z not allowed to participate in the attention, 2025-07-17T07:36:53.1736109Z which is the opposite of the definition for :attr:`attn_mask` 2025-07-17T07:36:53.1736295Z in :func:`torch.nn.functional.scaled_dot_product_attention`. 2025-07-17T07:36:53.1736381Z 2025-07-17T07:36:53.1736459Z Args: 2025-07-17T07:36:53.1736593Z src: the sequence to the encoder (required). 2025-07-17T07:36:53.1736731Z tgt: the sequence to the decoder (required). 2025-07-17T07:36:53.1736914Z src_mask: the additive mask for the src sequence (optional). 2025-07-17T07:36:53.1737094Z tgt_mask: the additive mask for the tgt sequence (optional). 2025-07-17T07:36:53.1737298Z memory_mask: the additive mask for the encoder output (optional). 2025-07-17T07:36:53.1737518Z src_key_padding_mask: the Tensor mask for src keys per batch (optional). 2025-07-17T07:36:53.1737747Z tgt_key_padding_mask: the Tensor mask for tgt keys per batch (optional). 2025-07-17T07:36:53.1737994Z memory_key_padding_mask: the Tensor mask for memory keys per batch (optional). 2025-07-17T07:36:53.1738203Z src_is_causal: If specified, applies a causal mask as ``src_mask``. 2025-07-17T07:36:53.1738342Z Default: ``None``; try to detect a causal mask. 2025-07-17T07:36:53.1738469Z Warning: 2025-07-17T07:36:53.1738632Z ``src_is_causal`` provides a hint that ``src_mask`` is 2025-07-17T07:36:53.1738804Z the causal mask. Providing incorrect hints can result in 2025-07-17T07:36:53.1738961Z incorrect execution, including forward and backward 2025-07-17T07:36:53.1739070Z compatibility. 2025-07-17T07:36:53.1739268Z tgt_is_causal: If specified, applies a causal mask as ``tgt_mask``. 2025-07-17T07:36:53.1739415Z Default: ``None``; try to detect a causal mask. 2025-07-17T07:36:53.1739529Z Warning: 2025-07-17T07:36:53.1739675Z ``tgt_is_causal`` provides a hint that ``tgt_mask`` is 2025-07-17T07:36:53.1739859Z the causal mask. Providing incorrect hints can result in 2025-07-17T07:36:53.1740019Z incorrect execution, including forward and backward 2025-07-17T07:36:53.1740114Z compatibility. 2025-07-17T07:36:53.1740297Z memory_is_causal: If specified, applies a causal mask as 2025-07-17T07:36:53.1740390Z ``memory_mask``. 2025-07-17T07:36:53.1740496Z Default: ``False``. 2025-07-17T07:36:53.1740584Z Warning: 2025-07-17T07:36:53.1740761Z ``memory_is_causal`` provides a hint that 2025-07-17T07:36:53.1740932Z ``memory_mask`` is the causal mask. Providing incorrect 2025-07-17T07:36:53.1741084Z hints can result in incorrect execution, including 2025-07-17T07:36:53.1741206Z forward and backward compatibility. 2025-07-17T07:36:53.1741293Z 2025-07-17T07:36:53.1741376Z Shape: 2025-07-17T07:36:53.1741617Z - src: :math:`(S, E)` for unbatched input, :math:`(S, N, E)` if `batch_first=False` or 2025-07-17T07:36:53.1741741Z `(N, S, E)` if `batch_first=True`. 2025-07-17T07:36:53.1741974Z - tgt: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-07-17T07:36:53.1742093Z `(N, T, E)` if `batch_first=True`. 2025-07-17T07:36:53.1742276Z - src_mask: :math:`(S, S)` or :math:`(N\cdot\text{num\_heads}, S, S)`. 2025-07-17T07:36:53.1742455Z - tgt_mask: :math:`(T, T)` or :math:`(N\cdot\text{num\_heads}, T, T)`. 2025-07-17T07:36:53.1742571Z - memory_mask: :math:`(T, S)`. 2025-07-17T07:36:53.1742808Z - src_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-07-17T07:36:53.1743046Z - tgt_key_padding_mask: :math:`(T)` for unbatched input otherwise :math:`(N, T)`. 2025-07-17T07:36:53.1743298Z - memory_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-07-17T07:36:53.1743376Z 2025-07-17T07:36:53.1743692Z Note: [src/tgt/memory]_mask ensures that position :math:`i` is allowed to attend the unmasked 2025-07-17T07:36:53.1743899Z positions. If a BoolTensor is provided, positions with ``True`` 2025-07-17T07:36:53.1744156Z are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor 2025-07-17T07:36:53.1744336Z is provided, it will be added to the attention weight. 2025-07-17T07:36:53.1744637Z [src/tgt/memory]_key_padding_mask provides specified elements in the key to be ignored by 2025-07-17T07:36:53.1744853Z the attention. If a BoolTensor is provided, the positions with the 2025-07-17T07:36:53.1745159Z value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged. 2025-07-17T07:36:53.1745233Z 2025-07-17T07:36:53.1745492Z - output: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-07-17T07:36:53.1745603Z `(N, T, E)` if `batch_first=True`. 2025-07-17T07:36:53.1745703Z 2025-07-17T07:36:53.1745952Z Note: Due to the multi-head attention architecture in the transformer model, 2025-07-17T07:36:53.1746184Z the output sequence length of a transformer is same as the input sequence 2025-07-17T07:36:53.1746309Z (i.e. target) length of the decoder. 2025-07-17T07:36:53.1746387Z 2025-07-17T07:36:53.1746701Z where :math:`S` is the source sequence length, :math:`T` is the target sequence length, :math:`N` is the 2025-07-17T07:36:53.1746833Z batch size, :math:`E` is the feature number 2025-07-17T07:36:53.1746933Z 2025-07-17T07:36:53.1747016Z Examples: 2025-07-17T07:36:53.1747124Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1747234Z >>> output = transformer_model( 2025-07-17T07:36:53.1747372Z ... src, tgt, src_mask=src_mask, tgt_mask=tgt_mask 2025-07-17T07:36:53.1747460Z ... ) 2025-07-17T07:36:53.1747540Z 2025-07-17T07:36:53.1747794Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1747869Z 2025-07-17T07:36:53.1747961Z warnings.warn(msg) 2025-07-17T07:36:53.1748041Z 2025-07-17T07:36:53.1748230Z --- Parse Warning: 109 / 136 --- 2025-07-17T07:36:53.1749308Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedDataParallel.join in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=1766. 2025-07-17T07:36:53.1749574Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1749653Z 2025-07-17T07:36:53.1749893Z Context manager for training with uneven inputs across processes in DDP. 2025-07-17T07:36:53.1749966Z 2025-07-17T07:36:53.1750185Z This context manager will keep track of already-joined DDP processes, 2025-07-17T07:36:53.1750394Z and "shadow" the forward and backward passes by inserting collective 2025-07-17T07:36:53.1750620Z communication operations to match with the ones created by non-joined 2025-07-17T07:36:53.1750846Z DDP processes. This will ensure each collective call has a corresponding 2025-07-17T07:36:53.1751071Z call by already-joined DDP processes, preventing hangs or errors that 2025-07-17T07:36:53.1751268Z would otherwise happen when training with uneven inputs across 2025-07-17T07:36:53.1751506Z processes. Alternatively, if the flag ``throw_on_early_termination`` is 2025-07-17T07:36:53.1751707Z specified to be ``True``, all trainers will throw an error once one rank 2025-07-17T07:36:53.1751903Z runs out of inputs, allowing these errors to be caught and handled 2025-07-17T07:36:53.1752019Z according to application logic. 2025-07-17T07:36:53.1752096Z 2025-07-17T07:36:53.1752307Z Once all DDP processes have joined, the context manager will broadcast 2025-07-17T07:36:53.1752536Z the model corresponding to the last joined process to all processes to 2025-07-17T07:36:53.1752678Z ensure the model is the same across all processes 2025-07-17T07:36:53.1752779Z (which is guaranteed by DDP). 2025-07-17T07:36:53.1752861Z 2025-07-17T07:36:53.1753061Z To use this to enable training with uneven inputs across processes, 2025-07-17T07:36:53.1753286Z simply wrap this context manager around your training loop. No further 2025-07-17T07:36:53.1753456Z modifications to the model or data loading is required. 2025-07-17T07:36:53.1753535Z 2025-07-17T07:36:53.1753625Z .. warning:: 2025-07-17T07:36:53.1753828Z If the model or training loop this context manager is wrapped around 2025-07-17T07:36:53.1754010Z has additional distributed collective operations, such as 2025-07-17T07:36:53.1754217Z ``SyncBatchNorm`` in the model's forward pass, then the flag 2025-07-17T07:36:53.1754416Z ``throw_on_early_termination`` must be enabled. This is because this 2025-07-17T07:36:53.1754660Z context manager is not aware of non-DDP collective communication. 2025-07-17T07:36:53.1754825Z This flag will cause all ranks to throw when any one rank 2025-07-17T07:36:53.1755032Z exhausts inputs, allowing these errors to be caught and recovered 2025-07-17T07:36:53.1755141Z from across all ranks. 2025-07-17T07:36:53.1755217Z 2025-07-17T07:36:53.1755294Z Args: 2025-07-17T07:36:53.1755481Z divide_by_initial_world_size (bool): If ``True``, will divide 2025-07-17T07:36:53.1755677Z gradients by the initial ``world_size`` DDP training was launched 2025-07-17T07:36:53.1755863Z with. If ``False``, will compute the effective world size 2025-07-17T07:36:53.1756045Z (number of ranks that have not depleted their inputs yet) and 2025-07-17T07:36:53.1756187Z divide gradients by that during allreduce. Set 2025-07-17T07:36:53.1756368Z ``divide_by_initial_world_size=True`` to ensure every input 2025-07-17T07:36:53.1756571Z sample including the uneven inputs have equal weight in terms of 2025-07-17T07:36:53.1756735Z how much they contribute to the global gradient. This is 2025-07-17T07:36:53.1756908Z achieved by always dividing the gradient by the initial 2025-07-17T07:36:53.1757133Z ``world_size`` even when we encounter uneven inputs. If you set 2025-07-17T07:36:53.1757297Z this to ``False``, we divide the gradient by the remaining 2025-07-17T07:36:53.1757491Z number of nodes. This ensures parity with training on a smaller 2025-07-17T07:36:53.1757671Z ``world_size`` although it also means the uneven inputs would 2025-07-17T07:36:53.1757863Z contribute more towards the global gradient. Typically, you 2025-07-17T07:36:53.1758041Z would want to set this to ``True`` for cases where the last few 2025-07-17T07:36:53.1758228Z inputs of your training job are uneven. In extreme cases, where 2025-07-17T07:36:53.1758416Z there is a large discrepancy in the number of inputs, setting 2025-07-17T07:36:53.1758552Z this to ``False`` might provide better results. 2025-07-17T07:36:53.1758759Z enable (bool): Whether to enable uneven input detection or not. Pass 2025-07-17T07:36:53.1758933Z in ``enable=False`` to disable in cases where you know that 2025-07-17T07:36:53.1759116Z inputs are even across participating processes. Default is 2025-07-17T07:36:53.1759207Z ``True``. 2025-07-17T07:36:53.1759381Z throw_on_early_termination (bool): Whether to throw an error 2025-07-17T07:36:53.1759552Z or continue training when at least one rank has exhausted 2025-07-17T07:36:53.1759737Z inputs. If ``True``, will throw upon the first rank reaching end 2025-07-17T07:36:53.1759903Z of data. If ``False``, will continue training with a smaller 2025-07-17T07:36:53.1760091Z effective world size until all ranks are joined. Note that if 2025-07-17T07:36:53.1760222Z this flag is specified, then the flag 2025-07-17T07:36:53.1760388Z ``divide_by_initial_world_size`` would be ignored. Default 2025-07-17T07:36:53.1760483Z is ``False``. 2025-07-17T07:36:53.1760556Z 2025-07-17T07:36:53.1760633Z 2025-07-17T07:36:53.1760743Z Example:: 2025-07-17T07:36:53.1760875Z 2025-07-17T07:36:53.1761019Z >>> # xdoctest: +SKIP("Distributed") 2025-07-17T07:36:53.1761140Z >>> import torch 2025-07-17T07:36:53.1761302Z >>> import torch.distributed as dist 2025-07-17T07:36:53.1761427Z >>> import os 2025-07-17T07:36:53.1761604Z >>> import torch.multiprocessing as mp 2025-07-17T07:36:53.1761702Z >>> import torch.nn as nn 2025-07-17T07:36:53.1761799Z >>> # On each spawned worker 2025-07-17T07:36:53.1761895Z >>> def worker(rank): 2025-07-17T07:36:53.1762064Z >>> dist.init_process_group("nccl", rank=rank, world_size=2) 2025-07-17T07:36:53.1762222Z >>> torch.cuda.set_device(rank) 2025-07-17T07:36:53.1762349Z >>> model = nn.Linear(1, 1, bias=False).to(rank) 2025-07-17T07:36:53.1762521Z >>> model = torch.nn.parallel.DistributedDataParallel( 2025-07-17T07:36:53.1762669Z >>> model, device_ids=[rank], output_device=rank 2025-07-17T07:36:53.1762746Z >>> ) 2025-07-17T07:36:53.1762868Z >>> # Rank 1 gets one more input than rank 0. 2025-07-17T07:36:53.1763058Z >>> inputs = [torch.tensor([1]).float() for _ in range(10 + rank)] 2025-07-17T07:36:53.1763180Z >>> with model.join(): 2025-07-17T07:36:53.1763281Z >>> for _ in range(5): 2025-07-17T07:36:53.1763376Z >>> for inp in inputs: 2025-07-17T07:36:53.1763482Z >>> loss = model(inp).sum() 2025-07-17T07:36:53.1763585Z >>> loss.backward() 2025-07-17T07:36:53.1763764Z >>> # Without the join() API, the below synchronization will hang 2025-07-17T07:36:53.1763902Z >>> # blocking for rank 1's allreduce to complete. 2025-07-17T07:36:53.1764033Z >>> torch.cuda.synchronize(device=rank) 2025-07-17T07:36:53.1764109Z 2025-07-17T07:36:53.1764425Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1764512Z 2025-07-17T07:36:53.1764605Z warnings.warn(msg) 2025-07-17T07:36:53.1764680Z 2025-07-17T07:36:53.1764899Z --- Parse Warning: 110 / 136 --- 2025-07-17T07:36:53.1766068Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedDataParallel._register_fused_optim in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=2057. 2025-07-17T07:36:53.1766342Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1766418Z 2025-07-17T07:36:53.1766723Z Register an optimizer in DDP to optimize parameter immediately after its gradient reduction. 2025-07-17T07:36:53.1766807Z 2025-07-17T07:36:53.1767010Z Registers an optimizer with DDP such that the optimization for a 2025-07-17T07:36:53.1767225Z parameter will run immediately when that parameter's gradient is 2025-07-17T07:36:53.1767421Z finished with reduction, instead of waiting for all parameters' 2025-07-17T07:36:53.1767633Z gradients to finish reduction. This can result in a training speedup 2025-07-17T07:36:53.1767854Z depending on your workload since the optimizer can run while gradient 2025-07-17T07:36:53.1768081Z reduction for other parameters are still ongoing. In addition, this has 2025-07-17T07:36:53.1768300Z the potential to reduce peak memory consumption during training, as it 2025-07-17T07:36:53.1768504Z only needs to load the per-parameter optimizer states of a single 2025-07-17T07:36:53.1768710Z parameter at a time, instead of loading all per-parameter optimizer 2025-07-17T07:36:53.1768809Z states at once. 2025-07-17T07:36:53.1768883Z 2025-07-17T07:36:53.1768962Z Args: 2025-07-17T07:36:53.1769166Z optim (Type): a ``torch.optim.Optimizer`` class to be registered 2025-07-17T07:36:53.1769259Z as a fused optimizer. 2025-07-17T07:36:53.1769425Z *args (Sequence[Any]): Arguments to forward to `optim`. 2025-07-17T07:36:53.1769643Z optim_params (Optional[Iterable[torch.Tensor]]): Set of parameters 2025-07-17T07:36:53.1769857Z to optimize, similar to `params` argument of traditional `torch.optim` 2025-07-17T07:36:53.1770234Z Optimizers. If this is omitted, all DDP model parameters will be 2025-07-17T07:36:53.1770331Z optimized. 2025-07-17T07:36:53.1770521Z **kwargs: (Dict[str, Any]): Keyword arguments to forward to `optim`. 2025-07-17T07:36:53.1770611Z 2025-07-17T07:36:53.1770696Z .. warning :: 2025-07-17T07:36:53.1770904Z _register_fused_optim should only be called once on a DDP instance, 2025-07-17T07:36:53.1771202Z and registering multiple fused optimizers for the same DDP model 2025-07-17T07:36:53.1771324Z is not currently supported. Please ping 2025-07-17T07:36:53.1771556Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-07-17T07:36:53.1771666Z for your use case. 2025-07-17T07:36:53.1771741Z 2025-07-17T07:36:53.1771827Z .. warning :: 2025-07-17T07:36:53.1772026Z _register_fused_optim and register_comm_hook currently do not 2025-07-17T07:36:53.1772235Z compose together, meaning that custom DDP communication hooks are 2025-07-17T07:36:53.1772458Z not supported with overlapped optimizers. Please ping 2025-07-17T07:36:53.1772681Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-07-17T07:36:53.1772771Z for your use case. 2025-07-17T07:36:53.1772858Z 2025-07-17T07:36:53.1772941Z .. warning :: 2025-07-17T07:36:53.1773163Z Gradient accumulation and DDP `no_sync` are currently not supported 2025-07-17T07:36:53.1773296Z with overlapped optimizer. Please ping 2025-07-17T07:36:53.1773517Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-07-17T07:36:53.1773608Z for your use case. 2025-07-17T07:36:53.1773773Z 2025-07-17T07:36:53.1773858Z Example:: 2025-07-17T07:36:53.1773946Z 2025-07-17T07:36:53.1774073Z >>> # xdoctest: +SKIP("No rendezvous handler") 2025-07-17T07:36:53.1774367Z >>> torch.distributed.init_process_group(backend='nccl', world_size=4, init_method='...') 2025-07-17T07:36:53.1774576Z >>> net = torch.nn.parallel.DistributedDataParallel(model, pg) 2025-07-17T07:36:53.1774657Z >>> lr = 1e-2 2025-07-17T07:36:53.1774745Z >>> betas = (0.9, 0.99) 2025-07-17T07:36:53.1774841Z >>> eps = 1e-6 2025-07-17T07:36:53.1775057Z >>> net._register_fused_optim(torch.optim.Adam, lr, betas=betas, eps=eps) 2025-07-17T07:36:53.1775174Z >>> # Example with subset of parameters 2025-07-17T07:36:53.1775315Z >>> params_to_opt = [list(net.parameters())[0]] 2025-07-17T07:36:53.1775419Z >>> net._register_fused_optim( 2025-07-17T07:36:53.1775656Z ... torch.optim.Adam, lr, optim_params=params_to_opt, betas=betas, eps=eps 2025-07-17T07:36:53.1775733Z ... ) 2025-07-17T07:36:53.1775808Z 2025-07-17T07:36:53.1776069Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1776143Z 2025-07-17T07:36:53.1776235Z warnings.warn(msg) 2025-07-17T07:36:53.1776324Z 2025-07-17T07:36:53.1776529Z --- Parse Warning: 111 / 136 --- 2025-07-17T07:36:53.1777542Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=convert_conv2d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=14. 2025-07-17T07:36:53.1777814Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1778023Z Convert ``memory_format`` of ``nn.Conv2d.weight`` to ``memory_format``. 2025-07-17T07:36:53.1778113Z 2025-07-17T07:36:53.1778384Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-07-17T07:36:53.1778651Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-07-17T07:36:53.1778912Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-07-17T07:36:53.1779215Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-07-17T07:36:53.1779303Z 2025-07-17T07:36:53.1779382Z .. note:: 2025-07-17T07:36:53.1779613Z Calling ``model.to(memory_format=torch.channels_last)`` is more aggressive 2025-07-17T07:36:53.1779842Z than the utility function ``convert_conv2d_weight_memory_format``. Any 2025-07-17T07:36:53.1780073Z layer with 4d weight will be affected by ``model.to``, which does not 2025-07-17T07:36:53.1780293Z necessarily benefit from conversion to specified ``memory_format``. 2025-07-17T07:36:53.1780526Z One place we are confident in is that NHWC(channels_last) conversion for 2025-07-17T07:36:53.1780735Z convolution in cuDNN, as it is beneficial to run convolution in NHWC, 2025-07-17T07:36:53.1780944Z even in cases where we have to apply permutation to input tensors. 2025-07-17T07:36:53.1781022Z 2025-07-17T07:36:53.1781240Z Hence our strategy here is to convert only the weight of convolution to 2025-07-17T07:36:53.1781394Z channels_last. This ensures that; 2025-07-17T07:36:53.1781603Z 1. Fast convolution kernels will be used, the benefit of which could 2025-07-17T07:36:53.1781829Z outweigh overhead of permutation (if input is not in the same format). 2025-07-17T07:36:53.1782072Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-07-17T07:36:53.1782179Z from memory_format conversion. 2025-07-17T07:36:53.1782266Z 2025-07-17T07:36:53.1782484Z The optimal case is that, layers between convolution layers are channels 2025-07-17T07:36:53.1782759Z last compatible. Input tensor would be permuted to channels last when it 2025-07-17T07:36:53.1782995Z encounters the first convolution layer and stay in that memory format. 2025-07-17T07:36:53.1783229Z Hence following convolutions will not need to permute its input tensor. 2025-07-17T07:36:53.1783304Z 2025-07-17T07:36:53.1783528Z In case where a channels last incompatible layer is between convolution 2025-07-17T07:36:53.1783733Z layers, we need to permute the input tensor back to contiguous format 2025-07-17T07:36:53.1783960Z for that layer. The input tensor will go through the remaining layers in 2025-07-17T07:36:53.1784183Z contiguous format and be permuted to channels last when it encounters 2025-07-17T07:36:53.1784384Z another convolution layer. There's no point in propagating that 2025-07-17T07:36:53.1784605Z permutation to an earlier layer, as most layers are quite agnostic to 2025-07-17T07:36:53.1784703Z ``memory_format``. 2025-07-17T07:36:53.1784776Z 2025-07-17T07:36:53.1785014Z This claim might change when PyTorch supports fusion of permutation, as 2025-07-17T07:36:53.1785231Z there might have been a better spot to fuse the permutation other than 2025-07-17T07:36:53.1785342Z immediately before a convolution. 2025-07-17T07:36:53.1785427Z 2025-07-17T07:36:53.1785504Z Args: 2025-07-17T07:36:53.1785720Z module (nn.Module): ``nn.Conv2d`` & ``nn.ConvTranspose2d`` or container 2025-07-17T07:36:53.1785818Z ``nn.Module`` 2025-07-17T07:36:53.1785966Z memory_format: user specified ``memory_format``, 2025-07-17T07:36:53.1786150Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-07-17T07:36:53.1786246Z 2025-07-17T07:36:53.1786321Z Returns: 2025-07-17T07:36:53.1786469Z The original module with updated ``nn.Conv2d`` 2025-07-17T07:36:53.1786546Z 2025-07-17T07:36:53.1786626Z Example: 2025-07-17T07:36:53.1786768Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:53.1786915Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-07-17T07:36:53.1787028Z >>> input = torch.randint( 2025-07-17T07:36:53.1787174Z ... 1, 10, (2, 8, 4, 4), dtype=torch.float16, device="cuda" 2025-07-17T07:36:53.1787251Z ... ) 2025-07-17T07:36:53.1787362Z >>> model = nn.Sequential( 2025-07-17T07:36:53.1787470Z >>> nn.Conv2d(8, 4, 3)).cuda().half() 2025-07-17T07:36:53.1787566Z >>> # This is identical to: 2025-07-17T07:36:53.1787845Z >>> # nn.utils.convert_conv2d_weight_memory_format(model, torch.channels_last) 2025-07-17T07:36:53.1788003Z >>> model = nn.utils.convert_conv2d_weight_memory_format( 2025-07-17T07:36:53.1788111Z ... model, torch.channels_last 2025-07-17T07:36:53.1788203Z ... ) 2025-07-17T07:36:53.1788294Z >>> out = model(input) 2025-07-17T07:36:53.1788381Z 2025-07-17T07:36:53.1788627Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1788700Z 2025-07-17T07:36:53.1788802Z warnings.warn(msg) 2025-07-17T07:36:53.1788898Z 2025-07-17T07:36:53.1789086Z --- Parse Warning: 112 / 136 --- 2025-07-17T07:36:53.1790106Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=convert_conv3d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=93. 2025-07-17T07:36:53.1790364Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1790583Z Convert ``memory_format`` of ``nn.Conv3d.weight`` to ``memory_format`` 2025-07-17T07:36:53.1790905Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-07-17T07:36:53.1791172Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-07-17T07:36:53.1791440Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-07-17T07:36:53.1791744Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-07-17T07:36:53.1791819Z 2025-07-17T07:36:53.1791914Z .. note:: 2025-07-17T07:36:53.1792148Z Calling ``model.to(memory_format=torch.channels_last_3d)`` is more aggressive 2025-07-17T07:36:53.1792375Z than the utility function ``convert_conv3d_weight_memory_format``. Any 2025-07-17T07:36:53.1792580Z layer with 4d weight will be affected by ``model.to``, which does not 2025-07-17T07:36:53.1792794Z necessarily benefit from conversion to specified ``memory_format``. 2025-07-17T07:36:53.1793036Z One place we are confident in is that NDHWC(channels_last_3d) conversion for 2025-07-17T07:36:53.1793253Z convolution in cuDNN, as it is beneficial to run convolution in NDHWC, 2025-07-17T07:36:53.1793445Z even in cases where we have to apply permutation to input tensors. 2025-07-17T07:36:53.1793528Z 2025-07-17T07:36:53.1793746Z Hence our strategy here is to convert only the weight of convolution to 2025-07-17T07:36:53.1793874Z channels_last_3d. This ensures that; 2025-07-17T07:36:53.1794087Z 1. Fast convolution kernels will be used, the benefit of which could 2025-07-17T07:36:53.1794312Z outweigh overhead of permutation (if input is not in the same format). 2025-07-17T07:36:53.1794555Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-07-17T07:36:53.1794664Z from memory_format conversion. 2025-07-17T07:36:53.1794737Z 2025-07-17T07:36:53.1794968Z The optimal case is that, layers between convolution layers are channels 2025-07-17T07:36:53.1795200Z last compatible. Input tensor would be permuted to channels last when it 2025-07-17T07:36:53.1795429Z encounters the first convolution layer and stay in that memory format. 2025-07-17T07:36:53.1795666Z Hence following convolutions will not need to permute its input tensor. 2025-07-17T07:36:53.1795744Z 2025-07-17T07:36:53.1795972Z In case where a channels last incompatible layer is between convolution 2025-07-17T07:36:53.1796180Z layers, we need to permute the input tensor back to contiguous format 2025-07-17T07:36:53.1796393Z for that layer. The input tensor will go through the remaining layers in 2025-07-17T07:36:53.1796654Z contiguous format and be permuted to channels last when it encounters 2025-07-17T07:36:53.1796858Z another convolution layer. There's no point in propagating that 2025-07-17T07:36:53.1797085Z permutation to an earlier layer, as most layers are quite agnostic to 2025-07-17T07:36:53.1797178Z ``memory_format``. 2025-07-17T07:36:53.1797249Z 2025-07-17T07:36:53.1797487Z This claim might change when PyTorch supports fusion of permutation, as 2025-07-17T07:36:53.1797702Z there might have been a better spot to fuse the permutation other than 2025-07-17T07:36:53.1797840Z immediately before a convolution. 2025-07-17T07:36:53.1797928Z 2025-07-17T07:36:53.1798004Z Args: 2025-07-17T07:36:53.1798208Z module (nn.Module): ``nn.Conv3d`` & ``nn.ConvTranspose3d`` or container 2025-07-17T07:36:53.1798319Z ``nn.Module`` 2025-07-17T07:36:53.1798463Z memory_format: user specified ``memory_format``, 2025-07-17T07:36:53.1798648Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-07-17T07:36:53.1798723Z 2025-07-17T07:36:53.1798806Z Returns: 2025-07-17T07:36:53.1799016Z The original module with updated ``nn.Conv3d`` 2025-07-17T07:36:53.1799094Z 2025-07-17T07:36:53.1799172Z Example: 2025-07-17T07:36:53.1799316Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-07-17T07:36:53.1799462Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-07-17T07:36:53.1799566Z >>> input = torch.randint( 2025-07-17T07:36:53.1799720Z ... 1, 10, (2, 8, 4, 4, 4), dtype=torch.float16, device="cuda" 2025-07-17T07:36:53.1799797Z ... ) 2025-07-17T07:36:53.1799905Z >>> model = nn.Sequential( 2025-07-17T07:36:53.1800016Z >>> nn.Conv3d(8, 4, 3)).cuda().half() 2025-07-17T07:36:53.1800112Z >>> # This is identical to: 2025-07-17T07:36:53.1800370Z >>> # nn.utils.convert_conv3d_weight_memory_format(model, torch.channels_last_3d) 2025-07-17T07:36:53.1800528Z >>> model = nn.utils.convert_conv3d_weight_memory_format( 2025-07-17T07:36:53.1800639Z ... model, torch.channels_last_3d 2025-07-17T07:36:53.1800729Z ... ) 2025-07-17T07:36:53.1800820Z >>> out = model(input) 2025-07-17T07:36:53.1800897Z 2025-07-17T07:36:53.1801162Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1801238Z 2025-07-17T07:36:53.1801347Z warnings.warn(msg) 2025-07-17T07:36:53.1801425Z 2025-07-17T07:36:53.1801617Z --- Parse Warning: 113 / 136 --- 2025-07-17T07:36:53.1802610Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_parametrization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrize.py line=424. 2025-07-17T07:36:53.1802869Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1803021Z Register a parametrization to a tensor in a module. 2025-07-17T07:36:53.1803110Z 2025-07-17T07:36:53.1803384Z Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``, 2025-07-17T07:36:53.1803676Z the module will return the parametrized version ``parametrization(module.weight)``. 2025-07-17T07:36:53.1803936Z If the original tensor requires a gradient, the backward pass will differentiate 2025-07-17T07:36:53.1804225Z through :attr:`parametrization`, and the optimizer will update the tensor accordingly. 2025-07-17T07:36:53.1804316Z 2025-07-17T07:36:53.1804625Z The first time that a module registers a parametrization, this function will add an attribute 2025-07-17T07:36:53.1804869Z ``parametrizations`` to the module of type :class:`~ParametrizationList`. 2025-07-17T07:36:53.1804988Z 2025-07-17T07:36:53.1805237Z The list of parametrizations on the tensor ``weight`` will be accessible under 2025-07-17T07:36:53.1805485Z ``module.parametrizations.weight``. 2025-07-17T07:36:53.1805565Z 2025-07-17T07:36:53.1805705Z The original tensor will be accessible under 2025-07-17T07:36:53.1805867Z ``module.parametrizations.weight.original``. 2025-07-17T07:36:53.1805942Z 2025-07-17T07:36:53.1806206Z Parametrizations may be concatenated by registering several parametrizations 2025-07-17T07:36:53.1806322Z on the same attribute. 2025-07-17T07:36:53.1806427Z 2025-07-17T07:36:53.1806668Z The training mode of a registered parametrization is updated on registration 2025-07-17T07:36:53.1806815Z to match the training mode of the host module 2025-07-17T07:36:53.1806894Z 2025-07-17T07:36:53.1807212Z Parametrized parameters and buffers have an inbuilt caching system that can be activated 2025-07-17T07:36:53.1807336Z using the context manager :func:`cached`. 2025-07-17T07:36:53.1807414Z 2025-07-17T07:36:53.1807664Z A :attr:`parametrization` may optionally implement a method with signature 2025-07-17T07:36:53.1807739Z 2025-07-17T07:36:53.1807843Z .. code-block:: python 2025-07-17T07:36:53.1807985Z 2025-07-17T07:36:53.1808199Z def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]] 2025-07-17T07:36:53.1808274Z 2025-07-17T07:36:53.1808545Z This method is called on the unparametrized tensor when the first parametrization 2025-07-17T07:36:53.1808752Z is registered to compute the initial value of the original tensor. 2025-07-17T07:36:53.1809068Z If this method is not implemented, the original tensor will be just the unparametrized tensor. 2025-07-17T07:36:53.1809145Z 2025-07-17T07:36:53.1809455Z If all the parametrizations registered on a tensor implement `right_inverse` it is possible 2025-07-17T07:36:53.1809752Z to initialize a parametrized tensor by assigning to it, as shown in the example below. 2025-07-17T07:36:53.1809827Z 2025-07-17T07:36:53.1810049Z It is possible for the first parametrization to depend on several inputs. 2025-07-17T07:36:53.1810299Z This may be implemented returning a tuple of tensors from ``right_inverse`` 2025-07-17T07:36:53.1810530Z (see the example implementation of a ``RankOne`` parametrization below). 2025-07-17T07:36:53.1810616Z 2025-07-17T07:36:53.1810947Z In this case, the unconstrained tensors are also located under ``module.parametrizations.weight`` 2025-07-17T07:36:53.1811073Z with names ``original0``, ``original1``,... 2025-07-17T07:36:53.1811156Z 2025-07-17T07:36:53.1811240Z .. note:: 2025-07-17T07:36:53.1811315Z 2025-07-17T07:36:53.1811590Z If unsafe=False (default) both the forward and right_inverse methods will be called 2025-07-17T07:36:53.1811733Z once to perform a number of consistency checks. 2025-07-17T07:36:53.1811996Z If unsafe=True, then right_inverse will be called if the tensor is not parametrized, 2025-07-17T07:36:53.1812123Z and nothing will be called otherwise. 2025-07-17T07:36:53.1812201Z 2025-07-17T07:36:53.1812295Z .. note:: 2025-07-17T07:36:53.1812373Z 2025-07-17T07:36:53.1812575Z In most situations, ``right_inverse`` will be a function such that 2025-07-17T07:36:53.1812701Z ``forward(right_inverse(X)) == X`` (see 2025-07-17T07:36:53.1812979Z `right inverse `_). 2025-07-17T07:36:53.1813227Z Sometimes, when the parametrization is not surjective, it may be reasonable 2025-07-17T07:36:53.1813326Z to relax this. 2025-07-17T07:36:53.1813405Z 2025-07-17T07:36:53.1813494Z .. warning:: 2025-07-17T07:36:53.1813581Z 2025-07-17T07:36:53.1813854Z If a parametrization depends on several inputs, :func:`~register_parametrization` 2025-07-17T07:36:53.1814148Z will register a number of new parameters. If such parametrization is registered 2025-07-17T07:36:53.1814414Z after the optimizer is created, these new parameters will need to be added manually 2025-07-17T07:36:53.1814612Z to the optimizer. See :meth:`torch.Optimizer.add_param_group`. 2025-07-17T07:36:53.1814702Z 2025-07-17T07:36:53.1814783Z Args: 2025-07-17T07:36:53.1814992Z module (nn.Module): module on which to register the parametrization 2025-07-17T07:36:53.1815239Z tensor_name (str): name of the parameter or buffer on which to register 2025-07-17T07:36:53.1815340Z the parametrization 2025-07-17T07:36:53.1815553Z parametrization (nn.Module): the parametrization to register 2025-07-17T07:36:53.1815641Z Keyword args: 2025-07-17T07:36:53.1815855Z unsafe (bool): a boolean flag that denotes whether the parametrization 2025-07-17T07:36:53.1816053Z may change the dtype and shape of the tensor. Default: `False` 2025-07-17T07:36:53.1816319Z Warning: the parametrization is not checked for consistency upon registration. 2025-07-17T07:36:53.1816434Z Enable this flag at your own risk. 2025-07-17T07:36:53.1816568Z 2025-07-17T07:36:53.1816649Z Raises: 2025-07-17T07:36:53.1816941Z ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name` 2025-07-17T07:36:53.1817017Z 2025-07-17T07:36:53.1817100Z Examples: 2025-07-17T07:36:53.1817257Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-07-17T07:36:53.1817350Z >>> import torch 2025-07-17T07:36:53.1817451Z >>> import torch.nn as nn 2025-07-17T07:36:53.1817594Z >>> import torch.nn.utils.parametrize as P 2025-07-17T07:36:53.1817673Z >>> 2025-07-17T07:36:53.1817782Z >>> class Symmetric(nn.Module): 2025-07-17T07:36:53.1817895Z >>> def forward(self, X): 2025-07-17T07:36:53.1818069Z >>> return X.triu() + X.triu(1).T # Return a symmetric matrix 2025-07-17T07:36:53.1818147Z >>> 2025-07-17T07:36:53.1818270Z >>> def right_inverse(self, A): 2025-07-17T07:36:53.1818373Z >>> return A.triu() 2025-07-17T07:36:53.1818463Z >>> 2025-07-17T07:36:53.1818558Z >>> m = nn.Linear(5, 5) 2025-07-17T07:36:53.1818725Z >>> P.register_parametrization(m, "weight", Symmetric()) 2025-07-17T07:36:53.1818973Z >>> print(torch.allclose(m.weight, m.weight.T)) # m.weight is now symmetric 2025-07-17T07:36:53.1819052Z True 2025-07-17T07:36:53.1819147Z >>> A = torch.rand(5, 5) 2025-07-17T07:36:53.1819265Z >>> A = A + A.T # A is now symmetric 2025-07-17T07:36:53.1819458Z >>> m.weight = A # Initialize the weight to be the symmetric matrix A 2025-07-17T07:36:53.1819578Z >>> print(torch.allclose(m.weight, A)) 2025-07-17T07:36:53.1819667Z True 2025-07-17T07:36:53.1819744Z 2025-07-17T07:36:53.1819858Z >>> class RankOne(nn.Module): 2025-07-17T07:36:53.1819960Z >>> def forward(self, x, y): 2025-07-17T07:36:53.1820101Z >>> # Form a rank 1 matrix multiplying two vectors 2025-07-17T07:36:53.1820241Z >>> return x.unsqueeze(-1) @ y.unsqueeze(-2) 2025-07-17T07:36:53.1820321Z >>> 2025-07-17T07:36:53.1820429Z >>> def right_inverse(self, Z): 2025-07-17T07:36:53.1820556Z >>> # Project Z onto the rank 1 matrices 2025-07-17T07:36:53.1820704Z >>> U, S, Vh = torch.linalg.svd(Z, full_matrices=False) 2025-07-17T07:36:53.1820819Z >>> # Return rescaled singular vectors 2025-07-17T07:36:53.1820947Z >>> s0_sqrt = S[0].sqrt().unsqueeze(-1) 2025-07-17T07:36:53.1821088Z >>> return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt 2025-07-17T07:36:53.1821201Z >>> 2025-07-17T07:36:53.1821345Z >>> linear_rank_one = P.register_parametrization( 2025-07-17T07:36:53.1821464Z ... nn.Linear(4, 4), "weight", RankOne() 2025-07-17T07:36:53.1821555Z ... ) 2025-07-17T07:36:53.1821756Z >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item()) 2025-07-17T07:36:53.1821834Z 1 2025-07-17T07:36:53.1821919Z 2025-07-17T07:36:53.1821997Z 2025-07-17T07:36:53.1822248Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1822360Z 2025-07-17T07:36:53.1822452Z warnings.warn(msg) 2025-07-17T07:36:53.1822537Z 2025-07-17T07:36:53.1822741Z --- Parse Warning: 114 / 136 --- 2025-07-17T07:36:53.1823623Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ln_structured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=979. 2025-07-17T07:36:53.1823895Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1824200Z Prune tensor by removing channels with the lowest L\ ``n``-norm along the specified dimension. 2025-07-17T07:36:53.1824327Z 2025-07-17T07:36:53.1824570Z Prunes tensor corresponding to parameter called ``name`` in ``module`` 2025-07-17T07:36:53.1824787Z by removing the specified ``amount`` of (currently unpruned) channels 2025-07-17T07:36:53.1824973Z along the specified ``dim`` with the lowest L\ ``n``-norm. 2025-07-17T07:36:53.1825167Z Modifies module in place (and also return the modified module) 2025-07-17T07:36:53.1825248Z by: 2025-07-17T07:36:53.1825333Z 2025-07-17T07:36:53.1825537Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-07-17T07:36:53.1825750Z binary mask applied to the parameter ``name`` by the pruning method. 2025-07-17T07:36:53.1825967Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-07-17T07:36:53.1826171Z original (unpruned) parameter is stored in a new parameter named 2025-07-17T07:36:53.1826269Z ``name+'_orig'``. 2025-07-17T07:36:53.1826349Z 2025-07-17T07:36:53.1826429Z Args: 2025-07-17T07:36:53.1826610Z module (nn.Module): module containing the tensor to prune 2025-07-17T07:36:53.1826786Z name (str): parameter name within ``module`` on which pruning 2025-07-17T07:36:53.1826876Z will act. 2025-07-17T07:36:53.1827055Z amount (int or float): quantity of parameters to prune. 2025-07-17T07:36:53.1827225Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-07-17T07:36:53.1827421Z fraction of parameters to prune. If ``int``, it represents the 2025-07-17T07:36:53.1827561Z absolute number of parameters to prune. 2025-07-17T07:36:53.1827752Z n (int, float, inf, -inf, 'fro', 'nuc'): See documentation of valid 2025-07-17T07:36:53.1827915Z entries for argument ``p`` in :func:`torch.norm`. 2025-07-17T07:36:53.1828107Z dim (int): index of the dim along which we define channels to prune. 2025-07-17T07:36:53.1828344Z importance_scores (torch.Tensor): tensor of importance scores (of same 2025-07-17T07:36:53.1828535Z shape as module parameter) used to compute mask for pruning. 2025-07-17T07:36:53.1828753Z The values in this tensor indicate the importance of the corresponding 2025-07-17T07:36:53.1828883Z elements in the parameter being pruned. 2025-07-17T07:36:53.1829114Z If unspecified or None, the module parameter will be used in its place. 2025-07-17T07:36:53.1829191Z 2025-07-17T07:36:53.1829283Z Returns: 2025-07-17T07:36:53.1829497Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-07-17T07:36:53.1829600Z 2025-07-17T07:36:53.1829691Z Examples: 2025-07-17T07:36:53.1829807Z >>> from torch.nn.utils import prune 2025-07-17T07:36:53.1829912Z >>> m = prune.ln_structured( 2025-07-17T07:36:53.1830100Z ... nn.Conv2d(5, 3, 2), "weight", amount=0.3, dim=1, n=float("-inf") 2025-07-17T07:36:53.1830180Z ... ) 2025-07-17T07:36:53.1830259Z 2025-07-17T07:36:53.1830521Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1830597Z 2025-07-17T07:36:53.1830740Z warnings.warn(msg) 2025-07-17T07:36:53.1830815Z 2025-07-17T07:36:53.1831003Z --- Parse Warning: 115 / 136 --- 2025-07-17T07:36:53.1831927Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=global_unstructured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1026. 2025-07-17T07:36:53.1832186Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1832261Z 2025-07-17T07:36:53.1832703Z Globally prunes tensors corresponding to all parameters in ``parameters`` by applying the specified ``pruning_method``. 2025-07-17T07:36:53.1832828Z 2025-07-17T07:36:53.1832948Z Modifies modules in place by: 2025-07-17T07:36:53.1833025Z 2025-07-17T07:36:53.1833230Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-07-17T07:36:53.1833455Z binary mask applied to the parameter ``name`` by the pruning method. 2025-07-17T07:36:53.1833666Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-07-17T07:36:53.1833872Z original (unpruned) parameter is stored in a new parameter named 2025-07-17T07:36:53.1833971Z ``name+'_orig'``. 2025-07-17T07:36:53.1834049Z 2025-07-17T07:36:53.1834131Z Args: 2025-07-17T07:36:53.1834344Z parameters (Iterable of (module, name) tuples): parameters of 2025-07-17T07:36:53.1834535Z the model to prune in a global fashion, i.e. by aggregating all 2025-07-17T07:36:53.1834751Z weights prior to deciding which ones to prune. module must be of 2025-07-17T07:36:53.1834903Z type :class:`nn.Module`, and name must be a string. 2025-07-17T07:36:53.1835123Z pruning_method (function): a valid pruning function from this module, 2025-07-17T07:36:53.1835312Z or a custom one implemented by the user that satisfies the 2025-07-17T07:36:53.1835541Z implementation guidelines and has ``PRUNING_TYPE='unstructured'``. 2025-07-17T07:36:53.1835769Z importance_scores (dict): a dictionary mapping (module, name) tuples to 2025-07-17T07:36:53.1836007Z the corresponding parameter's importance scores tensor. The tensor 2025-07-17T07:36:53.1836214Z should be the same shape as the parameter, and is used for computing 2025-07-17T07:36:53.1836329Z mask for pruning. 2025-07-17T07:36:53.1836536Z If unspecified or None, the parameter will be used in place of its 2025-07-17T07:36:53.1836636Z importance scores. 2025-07-17T07:36:53.1836773Z kwargs: other keyword arguments such as: 2025-07-17T07:36:53.1836972Z amount (int or float): quantity of parameters to prune across the 2025-07-17T07:36:53.1837074Z specified parameters. 2025-07-17T07:36:53.1837261Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-07-17T07:36:53.1837457Z fraction of parameters to prune. If ``int``, it represents the 2025-07-17T07:36:53.1837598Z absolute number of parameters to prune. 2025-07-17T07:36:53.1837676Z 2025-07-17T07:36:53.1837758Z Raises: 2025-07-17T07:36:53.1837914Z TypeError: if ``PRUNING_TYPE != 'unstructured'`` 2025-07-17T07:36:53.1837993Z 2025-07-17T07:36:53.1838073Z Note: 2025-07-17T07:36:53.1838324Z Since global structured pruning doesn't make much sense unless the 2025-07-17T07:36:53.1838521Z norm is normalized by the size of the parameter, we now limit the 2025-07-17T07:36:53.1838665Z scope of global pruning to unstructured methods. 2025-07-17T07:36:53.1838753Z 2025-07-17T07:36:53.1838835Z Examples: 2025-07-17T07:36:53.1838954Z >>> from torch.nn.utils import prune 2025-07-17T07:36:53.1839083Z >>> from collections import OrderedDict 2025-07-17T07:36:53.1839180Z >>> net = nn.Sequential( 2025-07-17T07:36:53.1839281Z ... OrderedDict( 2025-07-17T07:36:53.1839359Z ... [ 2025-07-17T07:36:53.1839501Z ... ("first", nn.Linear(10, 4)), 2025-07-17T07:36:53.1839628Z ... ("second", nn.Linear(4, 1)), 2025-07-17T07:36:53.1839707Z ... ] 2025-07-17T07:36:53.1839782Z ... ) 2025-07-17T07:36:53.1839875Z ... ) 2025-07-17T07:36:53.1839978Z >>> parameters_to_prune = ( 2025-07-17T07:36:53.1840076Z ... (net.first, "weight"), 2025-07-17T07:36:53.1840187Z ... (net.second, "weight"), 2025-07-17T07:36:53.1840264Z ... ) 2025-07-17T07:36:53.1840369Z >>> prune.global_unstructured( 2025-07-17T07:36:53.1840483Z ... parameters_to_prune, 2025-07-17T07:36:53.1840659Z ... pruning_method=prune.L1Unstructured, 2025-07-17T07:36:53.1840758Z ... amount=10, 2025-07-17T07:36:53.1840835Z ... ) 2025-07-17T07:36:53.1841050Z >>> print(sum(torch.nn.utils.parameters_to_vector(net.buffers()) == 0)) 2025-07-17T07:36:53.1841146Z tensor(10) 2025-07-17T07:36:53.1841224Z 2025-07-17T07:36:53.1841303Z 2025-07-17T07:36:53.1841567Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1841641Z 2025-07-17T07:36:53.1841732Z warnings.warn(msg) 2025-07-17T07:36:53.1841820Z 2025-07-17T07:36:53.1842004Z --- Parse Warning: 116 / 136 --- 2025-07-17T07:36:53.1842911Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=custom_from_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1149. 2025-07-17T07:36:53.1843173Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1843566Z Prune tensor corresponding to parameter called ``name`` in ``module`` by applying the pre-computed mask in ``mask``. 2025-07-17T07:36:53.1843654Z 2025-07-17T07:36:53.1843862Z Modifies module in place (and also return the modified module) by: 2025-07-17T07:36:53.1843937Z 2025-07-17T07:36:53.1844157Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-07-17T07:36:53.1844367Z binary mask applied to the parameter ``name`` by the pruning method. 2025-07-17T07:36:53.1844583Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-07-17T07:36:53.1844788Z original (unpruned) parameter is stored in a new parameter named 2025-07-17T07:36:53.1844880Z ``name+'_orig'``. 2025-07-17T07:36:53.1844968Z 2025-07-17T07:36:53.1845046Z Args: 2025-07-17T07:36:53.1845222Z module (nn.Module): module containing the tensor to prune 2025-07-17T07:36:53.1845501Z name (str): parameter name within ``module`` on which pruning 2025-07-17T07:36:53.1845587Z will act. 2025-07-17T07:36:53.1845756Z mask (Tensor): binary mask to be applied to the parameter. 2025-07-17T07:36:53.1845847Z 2025-07-17T07:36:53.1845931Z Returns: 2025-07-17T07:36:53.1846156Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-07-17T07:36:53.1846234Z 2025-07-17T07:36:53.1846317Z Examples: 2025-07-17T07:36:53.1846443Z >>> from torch.nn.utils import prune 2025-07-17T07:36:53.1846549Z >>> m = prune.custom_from_mask( 2025-07-17T07:36:53.1846752Z ... nn.Linear(5, 3), name="bias", mask=torch.tensor([0, 1, 0]) 2025-07-17T07:36:53.1846844Z ... ) 2025-07-17T07:36:53.1846939Z >>> print(m.bias_mask) 2025-07-17T07:36:53.1847029Z tensor([0., 1., 0.]) 2025-07-17T07:36:53.1847120Z 2025-07-17T07:36:53.1847201Z 2025-07-17T07:36:53.1847455Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1847540Z 2025-07-17T07:36:53.1847633Z warnings.warn(msg) 2025-07-17T07:36:53.1847721Z 2025-07-17T07:36:53.1847913Z --- Parse Warning: 117 / 136 --- 2025-07-17T07:36:53.1848837Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=pad_packed_sequence in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py line=342. 2025-07-17T07:36:53.1849109Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1849250Z Pad a packed batch of variable length sequences. 2025-07-17T07:36:53.1849326Z 2025-07-17T07:36:53.1849510Z It is an inverse operation to :func:`pack_padded_sequence`. 2025-07-17T07:36:53.1849583Z 2025-07-17T07:36:53.1849915Z The returned Tensor's data will be of size ``T x B x *`` (if :attr:`batch_first` is ``False``) 2025-07-17T07:36:53.1850150Z or ``B x T x *`` (if :attr:`batch_first` is ``True``) , where ``T`` is the length of the longest 2025-07-17T07:36:53.1850263Z sequence and ``B`` is the batch size. 2025-07-17T07:36:53.1850348Z 2025-07-17T07:36:53.1850430Z Example: 2025-07-17T07:36:53.1850666Z >>> from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence 2025-07-17T07:36:53.1850821Z >>> seq = torch.tensor([[1, 2, 0], [3, 0, 0], [4, 5, 6]]) 2025-07-17T07:36:53.1850911Z >>> lens = [2, 1, 3] 2025-07-17T07:36:53.1851024Z >>> packed = pack_padded_sequence( 2025-07-17T07:36:53.1851184Z ... seq, lens, batch_first=True, enforce_sorted=False 2025-07-17T07:36:53.1851262Z ... ) 2025-07-17T07:36:53.1851355Z >>> packed 2025-07-17T07:36:53.1851590Z PackedSequence(data=tensor([4, 1, 3, 5, 2, 6]), batch_sizes=tensor([3, 2, 1]), 2025-07-17T07:36:53.1851804Z sorted_indices=tensor([2, 0, 1]), unsorted_indices=tensor([1, 2, 0])) 2025-07-17T07:36:53.1852055Z >>> seq_unpacked, lens_unpacked = pad_packed_sequence(packed, batch_first=True) 2025-07-17T07:36:53.1852146Z >>> seq_unpacked 2025-07-17T07:36:53.1852289Z tensor([[1, 2, 0], 2025-07-17T07:36:53.1852383Z [3, 0, 0], 2025-07-17T07:36:53.1852466Z [4, 5, 6]]) 2025-07-17T07:36:53.1852556Z >>> lens_unpacked 2025-07-17T07:36:53.1852650Z tensor([2, 1, 3]) 2025-07-17T07:36:53.1852725Z 2025-07-17T07:36:53.1852819Z .. note:: 2025-07-17T07:36:53.1852960Z :attr:`total_length` is useful to implement the 2025-07-17T07:36:53.1853176Z ``pack sequence -> recurrent network -> unpack sequence`` pattern in a 2025-07-17T07:36:53.1853398Z :class:`~torch.nn.Module` wrapped in :class:`~torch.nn.DataParallel`. 2025-07-17T07:36:53.1853630Z See :ref:`this FAQ section ` for 2025-07-17T07:36:53.1853711Z details. 2025-07-17T07:36:53.1853794Z 2025-07-17T07:36:53.1853873Z Args: 2025-07-17T07:36:53.1854000Z sequence (PackedSequence): batch to pad 2025-07-17T07:36:53.1854241Z batch_first (bool, optional): if ``True``, the output will be in ``B x T x *`` 2025-07-17T07:36:53.1854351Z format, ``T x B x *`` otherwise. 2025-07-17T07:36:53.1854549Z padding_value (float, optional): values for padded elements. 2025-07-17T07:36:53.1854774Z total_length (int, optional): if not ``None``, the output will be padded to 2025-07-17T07:36:53.1855036Z have length :attr:`total_length`. This method will throw :class:`ValueError` 2025-07-17T07:36:53.1855231Z if :attr:`total_length` is less than the max sequence length in 2025-07-17T07:36:53.1855326Z :attr:`sequence`. 2025-07-17T07:36:53.1855402Z 2025-07-17T07:36:53.1855496Z Returns: 2025-07-17T07:36:53.1855680Z Tuple of Tensor containing the padded sequence, and a Tensor 2025-07-17T07:36:53.1855883Z containing the list of lengths of each sequence in the batch. 2025-07-17T07:36:53.1856102Z Batch elements will be re-ordered as they were ordered originally when 2025-07-17T07:36:53.1856341Z the batch was passed to ``pack_padded_sequence`` or ``pack_sequence``. 2025-07-17T07:36:53.1856429Z 2025-07-17T07:36:53.1856676Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1856752Z 2025-07-17T07:36:53.1856858Z warnings.warn(msg) 2025-07-17T07:36:53.1856933Z 2025-07-17T07:36:53.1857116Z --- Parse Warning: 118 / 136 --- 2025-07-17T07:36:53.1858109Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SequentialLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=808. 2025-07-17T07:36:53.1858367Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1858704Z Contains a list of schedulers expected to be called sequentially during the optimization process. 2025-07-17T07:36:53.1858784Z 2025-07-17T07:36:53.1859154Z Specifically, the schedulers will be called according to the milestone points, which should provide exact 2025-07-17T07:36:53.1859374Z intervals by which each scheduler should be called at a given epoch. 2025-07-17T07:36:53.1859451Z 2025-07-17T07:36:53.1859546Z Args: 2025-07-17T07:36:53.1859684Z optimizer (Optimizer): Wrapped optimizer. 2025-07-17T07:36:53.1859824Z schedulers (list): List of chained schedulers. 2025-07-17T07:36:53.1860046Z milestones (list): List of integers that reflects milestone points. 2025-07-17T07:36:53.1860207Z last_epoch (int): The index of last epoch. Default: -1. 2025-07-17T07:36:53.1860286Z 2025-07-17T07:36:53.1860379Z Example: 2025-07-17T07:36:53.1860475Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1860621Z >>> # Assuming optimizer uses lr = 0.05 for all groups 2025-07-17T07:36:53.1860739Z >>> # lr = 0.005 if epoch == 0 2025-07-17T07:36:53.1860842Z >>> # lr = 0.005 if epoch == 1 2025-07-17T07:36:53.1860949Z >>> # lr = 0.005 if epoch == 2 2025-07-17T07:36:53.1861029Z >>> # ... 2025-07-17T07:36:53.1861130Z >>> # lr = 0.05 if epoch == 20 2025-07-17T07:36:53.1861241Z >>> # lr = 0.045 if epoch == 21 2025-07-17T07:36:53.1861340Z >>> # lr = 0.0405 if epoch == 22 2025-07-17T07:36:53.1861538Z >>> scheduler1 = ConstantLR(optimizer, factor=0.1, total_iters=20) 2025-07-17T07:36:53.1861705Z >>> scheduler2 = ExponentialLR(optimizer, gamma=0.9) 2025-07-17T07:36:53.1861813Z >>> scheduler = SequentialLR( 2025-07-17T07:36:53.1861903Z ... optimizer, 2025-07-17T07:36:53.1862040Z ... schedulers=[scheduler1, scheduler2], 2025-07-17T07:36:53.1862134Z ... milestones=[20], 2025-07-17T07:36:53.1862231Z ... ) 2025-07-17T07:36:53.1862336Z >>> for epoch in range(100): 2025-07-17T07:36:53.1862425Z >>> train(...) 2025-07-17T07:36:53.1862531Z >>> validate(...) 2025-07-17T07:36:53.1862629Z >>> scheduler.step() 2025-07-17T07:36:53.1862708Z 2025-07-17T07:36:53.1862896Z .. image:: ../scripts/lr_scheduler_images/SequentialLR.png 2025-07-17T07:36:53.1863055Z 2025-07-17T07:36:53.1863306Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1863397Z 2025-07-17T07:36:53.1863494Z warnings.warn(msg) 2025-07-17T07:36:53.1863569Z 2025-07-17T07:36:53.1863769Z --- Parse Warning: 119 / 136 --- 2025-07-17T07:36:53.1864714Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ReduceLROnPlateau in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1233. 2025-07-17T07:36:53.1864973Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-07-17T07:36:53.1865181Z Reduce learning rate when a metric has stopped improving. 2025-07-17T07:36:53.1865257Z 2025-07-17T07:36:53.1865474Z Models often benefit from reducing the learning rate by a factor 2025-07-17T07:36:53.1865659Z of 2-10 once learning stagnates. This scheduler reads a metrics 2025-07-17T07:36:53.1865852Z quantity and if no improvement is seen for a 'patience' number 2025-07-17T07:36:53.1865989Z of epochs, the learning rate is reduced. 2025-07-17T07:36:53.1866066Z 2025-07-17T07:36:53.1866163Z Args: 2025-07-17T07:36:53.1866299Z optimizer (Optimizer): Wrapped optimizer. 2025-07-17T07:36:53.1866497Z mode (str): One of `min`, `max`. In `min` mode, lr will 2025-07-17T07:36:53.1866666Z be reduced when the quantity monitored has stopped 2025-07-17T07:36:53.1866827Z decreasing; in `max` mode it will be reduced when the 2025-07-17T07:36:53.1867020Z quantity monitored has stopped increasing. Default: 'min'. 2025-07-17T07:36:53.1867206Z factor (float): Factor by which the learning rate will be 2025-07-17T07:36:53.1867342Z reduced. new_lr = lr * factor. Default: 0.1. 2025-07-17T07:36:53.1867571Z patience (int): The number of allowed epochs with no improvement after 2025-07-17T07:36:53.1867701Z which the learning rate will be reduced. 2025-07-17T07:36:53.1867924Z For example, consider the case of having no patience (`patience = 0`). 2025-07-17T07:36:53.1868300Z In the first epoch, a baseline is established and is always considered good as there's no previous baseline. 2025-07-17T07:36:53.1868505Z In the second epoch, if the performance is worse than the baseline, 2025-07-17T07:36:53.1868652Z we have what is considered an intolerable epoch. 2025-07-17T07:36:53.1868924Z Since the count of intolerable epochs (1) is greater than the patience level (0), 2025-07-17T07:36:53.1869091Z the learning rate is reduced at the end of this epoch. 2025-07-17T07:36:53.1869430Z From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch 2025-07-17T07:36:53.1869740Z if the performance is worse than the baseline. If the performance improves or remains the same, 2025-07-17T07:36:53.1869860Z the learning rate is not adjusted. 2025-07-17T07:36:53.1870284Z Default: 10. 2025-07-17T07:36:53.1870478Z threshold (float): Threshold for measuring the new optimum, 2025-07-17T07:36:53.1870658Z to only focus on significant changes. Default: 1e-4. 2025-07-17T07:36:53.1870829Z threshold_mode (str): One of `rel`, `abs`. In `rel` mode, 2025-07-17T07:36:53.1870984Z dynamic_threshold = best * ( 1 + threshold ) in 'max' 2025-07-17T07:36:53.1871139Z mode or best * ( 1 - threshold ) in `min` mode. 2025-07-17T07:36:53.1871293Z In `abs` mode, dynamic_threshold = best + threshold in 2025-07-17T07:36:53.1871465Z `max` mode or best - threshold in `min` mode. Default: 'rel'. 2025-07-17T07:36:53.1871642Z cooldown (int): Number of epochs to wait before resuming 2025-07-17T07:36:53.1872261Z normal operation after lr has been reduced. Default: 0. 2025-07-17T07:36:53.1872432Z min_lr (float or list): A scalar or a list of scalars. A 2025-07-17T07:36:53.1872588Z lower bound on the learning rate of all param groups 2025-07-17T07:36:53.1872722Z or each group respectively. Default: 0. 2025-07-17T07:36:53.1872907Z eps (float): Minimal decay applied to lr. If the difference 2025-07-17T07:36:53.1873081Z between new and old lr is smaller than eps, the update is 2025-07-17T07:36:53.1873183Z ignored. Default: 1e-8. 2025-07-17T07:36:53.1873312Z 2025-07-17T07:36:53.1873397Z Example: 2025-07-17T07:36:53.1873492Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1873727Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-07-17T07:36:53.1873886Z >>> scheduler = ReduceLROnPlateau(optimizer, "min") 2025-07-17T07:36:53.1873997Z >>> for epoch in range(10): 2025-07-17T07:36:53.1874091Z >>> train(...) 2025-07-17T07:36:53.1874200Z >>> val_loss = validate(...) 2025-07-17T07:36:53.1874359Z >>> # Note that step should be called after validate() 2025-07-17T07:36:53.1874468Z >>> scheduler.step(val_loss) 2025-07-17T07:36:53.1874610Z 2025-07-17T07:36:53.1874813Z .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png 2025-07-17T07:36:53.1874890Z 2025-07-17T07:36:53.1875305Z Original Error: IndentationError('unexpected indent', ('', 8, 4, ' scheduler.step(val_loss)\n', 8, -1)) 2025-07-17T07:36:53.1875396Z 2025-07-17T07:36:53.1875499Z scheduler.step(val_loss) 2025-07-17T07:36:53.1875589Z ^ 2025-07-17T07:36:53.1875686Z warnings.warn(msg) 2025-07-17T07:36:53.1875764Z 2025-07-17T07:36:53.1875991Z --- Parse Warning: 120 / 136 --- 2025-07-17T07:36:53.1876883Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CyclicLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1430. 2025-07-17T07:36:53.1877148Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1877485Z Sets the learning rate of each parameter group according to cyclical learning rate policy (CLR). 2025-07-17T07:36:53.1877564Z 2025-07-17T07:36:53.1877857Z The policy cycles the learning rate between two boundaries with a constant frequency, 2025-07-17T07:36:53.1878112Z as detailed in the paper `Cyclical Learning Rates for Training Neural Networks`_. 2025-07-17T07:36:53.1878341Z The distance between the two boundaries can be scaled on a per-iteration 2025-07-17T07:36:53.1878449Z or per-cycle basis. 2025-07-17T07:36:53.1878527Z 2025-07-17T07:36:53.1878768Z Cyclical learning rate policy changes the learning rate after every batch. 2025-07-17T07:36:53.1878972Z `step` should be called after a batch has been used for training. 2025-07-17T07:36:53.1879048Z 2025-07-17T07:36:53.1879251Z This class has three built-in policies, as put forth in the paper: 2025-07-17T07:36:53.1879337Z 2025-07-17T07:36:53.1879541Z * "triangular": A basic triangular cycle without amplitude scaling. 2025-07-17T07:36:53.1879847Z * "triangular2": A basic triangular cycle that scales initial amplitude by half each cycle. 2025-07-17T07:36:53.1880164Z * "exp_range": A cycle that scales initial amplitude by :math:`\text{gamma}^{\text{cycle iterations}}` 2025-07-17T07:36:53.1880265Z at each cycle iteration. 2025-07-17T07:36:53.1880354Z 2025-07-17T07:36:53.1880592Z This implementation was adapted from the github repo: `bckenstler/CLR`_ 2025-07-17T07:36:53.1880668Z 2025-07-17T07:36:53.1880760Z Args: 2025-07-17T07:36:53.1880893Z optimizer (Optimizer): Wrapped optimizer. 2025-07-17T07:36:53.1881108Z base_lr (float or list): Initial learning rate which is the 2025-07-17T07:36:53.1881274Z lower boundary in the cycle for each parameter group. 2025-07-17T07:36:53.1881469Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-07-17T07:36:53.1881611Z for each parameter group. Functionally, 2025-07-17T07:36:53.1881763Z it defines the cycle amplitude (max_lr - base_lr). 2025-07-17T07:36:53.1881888Z The lr at any cycle is the sum of base_lr 2025-07-17T07:36:53.1882036Z and some scaling of the amplitude; therefore 2025-07-17T07:36:53.1882206Z max_lr may not actually be reached depending on 2025-07-17T07:36:53.1882314Z scaling function. 2025-07-17T07:36:53.1882479Z step_size_up (int): Number of training iterations in the 2025-07-17T07:36:53.1882606Z increasing half of a cycle. Default: 2000 2025-07-17T07:36:53.1882795Z step_size_down (int): Number of training iterations in the 2025-07-17T07:36:53.1882959Z decreasing half of a cycle. If step_size_down is None, 2025-07-17T07:36:53.1883082Z it is set to step_size_up. Default: None 2025-07-17T07:36:53.1883302Z mode (str): One of {triangular, triangular2, exp_range}. 2025-07-17T07:36:53.1883446Z Values correspond to policies detailed above. 2025-07-17T07:36:53.1883592Z If scale_fn is not None, this argument is ignored. 2025-07-17T07:36:53.1883708Z Default: 'triangular' 2025-07-17T07:36:53.1883872Z gamma (float): Constant in 'exp_range' scaling function: 2025-07-17T07:36:53.1883990Z gamma**(cycle iterations) 2025-07-17T07:36:53.1884080Z Default: 1.0 2025-07-17T07:36:53.1884267Z scale_fn (function): Custom scaling policy defined by a single 2025-07-17T07:36:53.1884394Z argument lambda function, where 2025-07-17T07:36:53.1884508Z 0 <= scale_fn(x) <= 1 for all x >= 0. 2025-07-17T07:36:53.1884628Z If specified, then 'mode' is ignored. 2025-07-17T07:36:53.1884730Z Default: None 2025-07-17T07:36:53.1884854Z scale_mode (str): {'cycle', 'iterations'}. 2025-07-17T07:36:53.1884995Z Defines whether scale_fn is evaluated on 2025-07-17T07:36:53.1885124Z cycle number or cycle iterations (training 2025-07-17T07:36:53.1885400Z iterations since start of cycle). 2025-07-17T07:36:53.1885510Z Default: 'cycle' 2025-07-17T07:36:53.1885704Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-07-17T07:36:53.1885885Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-07-17T07:36:53.1885990Z Default: True 2025-07-17T07:36:53.1886206Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-07-17T07:36:53.1886410Z for each parameter group. Note that momentum is cycled inversely 2025-07-17T07:36:53.1886581Z to learning rate; at the peak of a cycle, momentum is 2025-07-17T07:36:53.1886720Z 'base_momentum' and learning rate is 'max_lr'. 2025-07-17T07:36:53.1886825Z Default: 0.8 2025-07-17T07:36:53.1887037Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-07-17T07:36:53.1887165Z for each parameter group. Functionally, 2025-07-17T07:36:53.1887368Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-07-17T07:36:53.1887546Z The momentum at any cycle is the difference of max_momentum 2025-07-17T07:36:53.1887682Z and some scaling of the amplitude; therefore 2025-07-17T07:36:53.1887861Z base_momentum may not actually be reached depending on 2025-07-17T07:36:53.1888035Z scaling function. Note that momentum is cycled inversely 2025-07-17T07:36:53.1888289Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-07-17T07:36:53.1888400Z and learning rate is 'base_lr' 2025-07-17T07:36:53.1888489Z Default: 0.9 2025-07-17T07:36:53.1888719Z last_epoch (int): The index of the last batch. This parameter is used when 2025-07-17T07:36:53.1888934Z resuming a training job. Since `step()` should be invoked after each 2025-07-17T07:36:53.1889145Z batch instead of after each epoch, this number represents the total 2025-07-17T07:36:53.1889373Z number of *batches* computed, not the total number of epochs computed. 2025-07-17T07:36:53.1889590Z When last_epoch=-1, the schedule is started from the beginning. 2025-07-17T07:36:53.1889696Z Default: -1 2025-07-17T07:36:53.1889773Z 2025-07-17T07:36:53.1889855Z Example: 2025-07-17T07:36:53.1889964Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1890190Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-07-17T07:36:53.1890341Z >>> scheduler = torch.optim.lr_scheduler.CyclicLR( 2025-07-17T07:36:53.1890445Z ... optimizer, 2025-07-17T07:36:53.1890536Z ... base_lr=0.01, 2025-07-17T07:36:53.1890690Z ... max_lr=0.1, 2025-07-17T07:36:53.1890797Z ... step_size_up=10, 2025-07-17T07:36:53.1890877Z ... ) 2025-07-17T07:36:53.1891039Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-07-17T07:36:53.1891140Z >>> for epoch in range(10): 2025-07-17T07:36:53.1891249Z >>> for batch in data_loader: 2025-07-17T07:36:53.1891359Z >>> train_batch(...) 2025-07-17T07:36:53.1891460Z >>> scheduler.step() 2025-07-17T07:36:53.1891538Z 2025-07-17T07:36:53.1891704Z .. image:: ../scripts/lr_scheduler_images/CyclicLR.png 2025-07-17T07:36:53.1891782Z 2025-07-17T07:36:53.1892084Z .. _Cyclical Learning Rates for Training Neural Networks: https://arxiv.org/abs/1506.01186 2025-07-17T07:36:53.1892257Z .. _bckenstler/CLR: https://github.com/bckenstler/CLR 2025-07-17T07:36:53.1892338Z 2025-07-17T07:36:53.1892601Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1892677Z 2025-07-17T07:36:53.1892771Z warnings.warn(msg) 2025-07-17T07:36:53.1892859Z 2025-07-17T07:36:53.1893061Z --- Parse Warning: 121 / 136 --- 2025-07-17T07:36:53.1894062Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CosineAnnealingWarmRestarts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1713. 2025-07-17T07:36:53.1894336Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1894588Z Set the learning rate of each parameter group using a cosine annealing schedule. 2025-07-17T07:36:53.1894717Z 2025-07-17T07:36:53.1894893Z The :math:`\eta_{max}` is set to the initial lr, :math:`T_{cur}` 2025-07-17T07:36:53.1895128Z is the number of epochs since the last restart and :math:`T_{i}` is the number 2025-07-17T07:36:53.1895282Z of epochs between two warm restarts in SGDR: 2025-07-17T07:36:53.1895360Z 2025-07-17T07:36:53.1895446Z .. math:: 2025-07-17T07:36:53.1895634Z \eta_t = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 + 2025-07-17T07:36:53.1895774Z \cos\left(\frac{T_{cur}}{T_{i}}\pi\right)\right) 2025-07-17T07:36:53.1895854Z 2025-07-17T07:36:53.1896031Z When :math:`T_{cur}=T_{i}`, set :math:`\eta_t = \eta_{min}`. 2025-07-17T07:36:53.1896216Z When :math:`T_{cur}=0` after restart, set :math:`\eta_t=\eta_{max}`. 2025-07-17T07:36:53.1896306Z 2025-07-17T07:36:53.1896405Z It has been proposed in 2025-07-17T07:36:53.1896605Z `SGDR: Stochastic Gradient Descent with Warm Restarts`_. 2025-07-17T07:36:53.1896698Z 2025-07-17T07:36:53.1896779Z Args: 2025-07-17T07:36:53.1896913Z optimizer (Optimizer): Wrapped optimizer. 2025-07-17T07:36:53.1897084Z T_0 (int): Number of iterations until the first restart. 2025-07-17T07:36:53.1897374Z T_mult (int, optional): A factor by which :math:`T_{i}` increases after a restart. Default: 1. 2025-07-17T07:36:53.1897573Z eta_min (float, optional): Minimum learning rate. Default: 0. 2025-07-17T07:36:53.1897784Z last_epoch (int, optional): The index of the last epoch. Default: -1. 2025-07-17T07:36:53.1897891Z 2025-07-17T07:36:53.1898071Z .. _SGDR\: Stochastic Gradient Descent with Warm Restarts: 2025-07-17T07:36:53.1898192Z https://arxiv.org/abs/1608.03983 2025-07-17T07:36:53.1898270Z 2025-07-17T07:36:53.1898369Z Example: 2025-07-17T07:36:53.1898469Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1898653Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.05) 2025-07-17T07:36:53.1898927Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts( 2025-07-17T07:36:53.1899026Z ... optimizer, T_0=20 2025-07-17T07:36:53.1899119Z ... ) 2025-07-17T07:36:53.1899270Z >>> for epoch in range(100): 2025-07-17T07:36:53.1899363Z >>> train(...) 2025-07-17T07:36:53.1899470Z >>> validate(...) 2025-07-17T07:36:53.1899571Z >>> scheduler.step() 2025-07-17T07:36:53.1899648Z 2025-07-17T07:36:53.1899899Z .. image:: ../scripts/lr_scheduler_images/CosineAnnealingWarmRestarts.png 2025-07-17T07:36:53.1899981Z 2025-07-17T07:36:53.1900233Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1900322Z 2025-07-17T07:36:53.1900418Z warnings.warn(msg) 2025-07-17T07:36:53.1900496Z 2025-07-17T07:36:53.1900701Z --- Parse Warning: 122 / 136 --- 2025-07-17T07:36:53.1901609Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=OneCycleLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1863. 2025-07-17T07:36:53.1901886Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1902185Z Sets the learning rate of each parameter group according to the 1cycle learning rate policy. 2025-07-17T07:36:53.1902262Z 2025-07-17T07:36:53.1902566Z The 1cycle policy anneals the learning rate from an initial learning rate to some maximum 2025-07-17T07:36:53.1902855Z learning rate and then from that maximum learning rate to some minimum learning rate much 2025-07-17T07:36:53.1902986Z lower than the initial learning rate. 2025-07-17T07:36:53.1903206Z This policy was initially described in the paper `Super-Convergence: 2025-07-17T07:36:53.1903415Z Very Fast Training of Neural Networks Using Large Learning Rates`_. 2025-07-17T07:36:53.1903504Z 2025-07-17T07:36:53.1903745Z The 1cycle learning rate policy changes the learning rate after every batch. 2025-07-17T07:36:53.1903940Z `step` should be called after a batch has been used for training. 2025-07-17T07:36:53.1904028Z 2025-07-17T07:36:53.1904135Z This scheduler is not chainable. 2025-07-17T07:36:53.1904212Z 2025-07-17T07:36:53.1904458Z Note also that the total number of steps in the cycle can be determined in one 2025-07-17T07:36:53.1904591Z of two ways (listed in order of precedence): 2025-07-17T07:36:53.1904680Z 2025-07-17T07:36:53.1904827Z #. A value for total_steps is explicitly provided. 2025-07-17T07:36:53.1905005Z #. A number of epochs (epochs) and a number of steps per epoch 2025-07-17T07:36:53.1905126Z (steps_per_epoch) are provided. 2025-07-17T07:36:53.1905313Z In this case, the number of total steps is inferred by 2025-07-17T07:36:53.1905433Z total_steps = epochs * steps_per_epoch 2025-07-17T07:36:53.1905522Z 2025-07-17T07:36:53.1905762Z You must either provide a value for total_steps or provide a value for both 2025-07-17T07:36:53.1905870Z epochs and steps_per_epoch. 2025-07-17T07:36:53.1905959Z 2025-07-17T07:36:53.1906262Z The default behaviour of this scheduler follows the fastai implementation of 1cycle, which 2025-07-17T07:36:53.1906565Z claims that "unpublished work has shown even better results by using only two phases". To 2025-07-17T07:36:53.1906831Z mimic the behaviour of the original paper instead, set ``three_phase=True``. 2025-07-17T07:36:53.1906911Z 2025-07-17T07:36:53.1907003Z Args: 2025-07-17T07:36:53.1907134Z optimizer (Optimizer): Wrapped optimizer. 2025-07-17T07:36:53.1907330Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-07-17T07:36:53.1907452Z for each parameter group. 2025-07-17T07:36:53.1907654Z total_steps (int): The total number of steps in the cycle. Note that 2025-07-17T07:36:53.1907873Z if a value is not provided here, then it must be inferred by providing 2025-07-17T07:36:53.1908051Z a value for epochs and steps_per_epoch. 2025-07-17T07:36:53.1908144Z Default: None 2025-07-17T07:36:53.1908353Z epochs (int): The number of epochs to train for. This is used along 2025-07-17T07:36:53.1908593Z with steps_per_epoch in order to infer the total number of steps in the cycle 2025-07-17T07:36:53.1908726Z if a value for total_steps is not provided. 2025-07-17T07:36:53.1908831Z Default: None 2025-07-17T07:36:53.1909052Z steps_per_epoch (int): The number of steps per epoch to train for. This is 2025-07-17T07:36:53.1909287Z used along with epochs in order to infer the total number of steps in the 2025-07-17T07:36:53.1909434Z cycle if a value for total_steps is not provided. 2025-07-17T07:36:53.1909527Z Default: None 2025-07-17T07:36:53.1909764Z pct_start (float): The percentage of the cycle (in number of steps) spent 2025-07-17T07:36:53.1909881Z increasing the learning rate. 2025-07-17T07:36:53.1909972Z Default: 0.3 2025-07-17T07:36:53.1910103Z anneal_strategy (str): {'cos', 'linear'} 2025-07-17T07:36:53.1910347Z Specifies the annealing strategy: "cos" for cosine annealing, "linear" for 2025-07-17T07:36:53.1910443Z linear annealing. 2025-07-17T07:36:53.1910549Z Default: 'cos' 2025-07-17T07:36:53.1910744Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-07-17T07:36:53.1910936Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-07-17T07:36:53.1911027Z Default: True 2025-07-17T07:36:53.1911246Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-07-17T07:36:53.1911462Z for each parameter group. Note that momentum is cycled inversely 2025-07-17T07:36:53.1911620Z to learning rate; at the peak of a cycle, momentum is 2025-07-17T07:36:53.1911759Z 'base_momentum' and learning rate is 'max_lr'. 2025-07-17T07:36:53.1911860Z Default: 0.85 2025-07-17T07:36:53.1912069Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-07-17T07:36:53.1912210Z for each parameter group. Functionally, 2025-07-17T07:36:53.1912401Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-07-17T07:36:53.1912523Z Note that momentum is cycled inversely 2025-07-17T07:36:53.1912741Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-07-17T07:36:53.1912853Z and learning rate is 'base_lr' 2025-07-17T07:36:53.1912970Z Default: 0.95 2025-07-17T07:36:53.1913163Z div_factor (float): Determines the initial learning rate via 2025-07-17T07:36:53.1913272Z initial_lr = max_lr/div_factor 2025-07-17T07:36:53.1913373Z Default: 25 2025-07-17T07:36:53.1913578Z final_div_factor (float): Determines the minimum learning rate via 2025-07-17T07:36:53.1913696Z min_lr = initial_lr/final_div_factor 2025-07-17T07:36:53.1913797Z Default: 1e4 2025-07-17T07:36:53.1914041Z three_phase (bool): If ``True``, use a third phase of the schedule to annihilate the 2025-07-17T07:36:53.1914319Z learning rate according to 'final_div_factor' instead of modifying the second 2025-07-17T07:36:53.1914566Z phase (the first two phases will be symmetrical about the step indicated by 2025-07-17T07:36:53.1914658Z 'pct_start'). 2025-07-17T07:36:53.1914886Z last_epoch (int): The index of the last batch. This parameter is used when 2025-07-17T07:36:53.1915099Z resuming a training job. Since `step()` should be invoked after each 2025-07-17T07:36:53.1915309Z batch instead of after each epoch, this number represents the total 2025-07-17T07:36:53.1915586Z number of *batches* computed, not the total number of epochs computed. 2025-07-17T07:36:53.1915776Z When last_epoch=-1, the schedule is started from the beginning. 2025-07-17T07:36:53.1915867Z Default: -1 2025-07-17T07:36:53.1915953Z 2025-07-17T07:36:53.1916038Z Example: 2025-07-17T07:36:53.1916134Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1916294Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-07-17T07:36:53.1916523Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9) 2025-07-17T07:36:53.1916692Z >>> scheduler = torch.optim.lr_scheduler.OneCycleLR( 2025-07-17T07:36:53.1916902Z ... optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10 2025-07-17T07:36:53.1916982Z ... ) 2025-07-17T07:36:53.1917094Z >>> for epoch in range(10): 2025-07-17T07:36:53.1917200Z >>> for batch in data_loader: 2025-07-17T07:36:53.1917299Z >>> train_batch(...) 2025-07-17T07:36:53.1917411Z >>> optimizer.step() 2025-07-17T07:36:53.1917509Z >>> scheduler.step() 2025-07-17T07:36:53.1917585Z 2025-07-17T07:36:53.1917758Z .. image:: ../scripts/lr_scheduler_images/OneCycleLR.png 2025-07-17T07:36:53.1917836Z 2025-07-17T07:36:53.1918136Z .. _Super-Convergence\: Very Fast Training of Neural Networks Using Large Learning Rates: 2025-07-17T07:36:53.1918253Z https://arxiv.org/abs/1708.07120 2025-07-17T07:36:53.1918332Z 2025-07-17T07:36:53.1918594Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1918672Z 2025-07-17T07:36:53.1918764Z warnings.warn(msg) 2025-07-17T07:36:53.1918851Z 2025-07-17T07:36:53.1919042Z --- Parse Warning: 123 / 136 --- 2025-07-17T07:36:53.1919999Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Optimizer.load_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/optimizer.py line=867. 2025-07-17T07:36:53.1920259Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1920362Z Load the optimizer state. 2025-07-17T07:36:53.1920455Z 2025-07-17T07:36:53.1920535Z Args: 2025-07-17T07:36:53.1920731Z state_dict (dict): optimizer state. Should be an object returned 2025-07-17T07:36:53.1920861Z from a call to :meth:`state_dict`. 2025-07-17T07:36:53.1920937Z 2025-07-17T07:36:53.1921026Z .. warning:: 2025-07-17T07:36:53.1921406Z Make sure this method is called after initializing :class:`torch.optim.lr_scheduler.LRScheduler`, 2025-07-17T07:36:53.1921613Z as calling it beforehand will overwrite the loaded learning rates. 2025-07-17T07:36:53.1921702Z 2025-07-17T07:36:53.1921786Z .. note:: 2025-07-17T07:36:53.1922074Z The names of the parameters (if they exist under the "param_names" key of each param group 2025-07-17T07:36:53.1922256Z in :meth:`state_dict`) will not affect the loading process. 2025-07-17T07:36:53.1922578Z To use the parameters' names for custom cases (such as when the parameters in the loaded state dict 2025-07-17T07:36:53.1922757Z differ from those initialized in the optimizer), 2025-07-17T07:36:53.1923073Z a custom ``register_load_state_dict_pre_hook`` should be implemented to adapt the loaded dict 2025-07-17T07:36:53.1923164Z accordingly. 2025-07-17T07:36:53.1923466Z If ``param_names`` exist in loaded state dict ``param_groups`` they will be saved and override 2025-07-17T07:36:53.1923780Z the current names, if present, in the optimizer state. If they do not exist in loaded state dict, 2025-07-17T07:36:53.1924003Z the optimizer ``param_names`` will remain unchanged. 2025-07-17T07:36:53.1924097Z 2025-07-17T07:36:53.1924180Z Example: 2025-07-17T07:36:53.1924277Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.1924403Z >>> model = torch.nn.Linear(10, 10) 2025-07-17T07:36:53.1924567Z >>> optim = torch.optim.SGD(model.parameters(), lr=3e-4) 2025-07-17T07:36:53.1924734Z >>> scheduler1 = torch.optim.lr_scheduler.LinearLR( 2025-07-17T07:36:53.1924822Z ... optim, 2025-07-17T07:36:53.1924922Z ... start_factor=0.1, 2025-07-17T07:36:53.1925027Z ... end_factor=1, 2025-07-17T07:36:53.1925123Z ... total_iters=20, 2025-07-17T07:36:53.1925203Z ... ) 2025-07-17T07:36:53.1925504Z >>> scheduler2 = torch.optim.lr_scheduler.CosineAnnealingLR( 2025-07-17T07:36:53.1925595Z ... optim, 2025-07-17T07:36:53.1925684Z ... T_max=80, 2025-07-17T07:36:53.1925795Z ... eta_min=3e-5, 2025-07-17T07:36:53.1925885Z ... ) 2025-07-17T07:36:53.1926041Z >>> lr = torch.optim.lr_scheduler.SequentialLR( 2025-07-17T07:36:53.1926132Z ... optim, 2025-07-17T07:36:53.1926265Z ... schedulers=[scheduler1, scheduler2], 2025-07-17T07:36:53.1926379Z ... milestones=[20], 2025-07-17T07:36:53.1926462Z ... ) 2025-07-17T07:36:53.1926607Z >>> lr.load_state_dict(torch.load("./save_seq.pt")) 2025-07-17T07:36:53.1926820Z >>> # now load the optimizer checkpoint after loading the LRScheduler 2025-07-17T07:36:53.1926990Z >>> optim.load_state_dict(torch.load("./save_optim.pt")) 2025-07-17T07:36:53.1927064Z 2025-07-17T07:36:53.1927151Z 2025-07-17T07:36:53.1927403Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1927494Z 2025-07-17T07:36:53.1927609Z warnings.warn(msg) 2025-07-17T07:36:53.1927689Z 2025-07-17T07:36:53.1927900Z --- Parse Warning: 124 / 136 --- 2025-07-17T07:36:53.1928800Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=AveragedModel in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=120. 2025-07-17T07:36:53.1929063Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1929443Z Implements averaged model for Stochastic Weight Averaging (SWA) and Exponential Moving Average (EMA). 2025-07-17T07:36:53.1929560Z 2025-07-17T07:36:53.1929812Z Stochastic Weight Averaging was proposed in `Averaging Weights Leads to 2025-07-17T07:36:53.1930028Z Wider Optima and Better Generalization`_ by Pavel Izmailov, Dmitrii 2025-07-17T07:36:53.1930243Z Podoprikhin, Timur Garipov, Dmitry Vetrov and Andrew Gordon Wilson 2025-07-17T07:36:53.1930347Z (UAI 2018). 2025-07-17T07:36:53.1930429Z 2025-07-17T07:36:53.1930648Z Exponential Moving Average is a variation of `Polyak averaging`_, 2025-07-17T07:36:53.1930901Z but using exponential weights instead of equal weights across iterations. 2025-07-17T07:36:53.1931004Z 2025-07-17T07:36:53.1931239Z AveragedModel class creates a copy of the provided module :attr:`model` 2025-07-17T07:36:53.1931472Z on the device :attr:`device` and allows to compute running averages of the 2025-07-17T07:36:53.1931582Z parameters of the :attr:`model`. 2025-07-17T07:36:53.1931670Z 2025-07-17T07:36:53.1931757Z Args: 2025-07-17T07:36:53.1931910Z model (torch.nn.Module): model to use with SWA/EMA 2025-07-17T07:36:53.1932151Z device (torch.device, optional): if provided, the averaged model will be 2025-07-17T07:36:53.1932257Z stored on the :attr:`device` 2025-07-17T07:36:53.1932562Z avg_fn (function, optional): the averaging function used to update 2025-07-17T07:36:53.1932772Z parameters; the function must take in the current value of the 2025-07-17T07:36:53.1932992Z :class:`AveragedModel` parameter, the current value of :attr:`model` 2025-07-17T07:36:53.1933194Z parameter, and the number of models already averaged; if None, 2025-07-17T07:36:53.1933349Z an equally weighted average is used (default: None) 2025-07-17T07:36:53.1933572Z multi_avg_fn (function, optional): the averaging function used to update 2025-07-17T07:36:53.1933817Z parameters inplace; the function must take in the current values of the 2025-07-17T07:36:53.1934082Z :class:`AveragedModel` parameters as a list, the current values of :attr:`model` 2025-07-17T07:36:53.1934305Z parameters as a list, and the number of models already averaged; if None, 2025-07-17T07:36:53.1934469Z an equally weighted average is used (default: None) 2025-07-17T07:36:53.1934672Z use_buffers (bool): if ``True``, it will compute running averages for 2025-07-17T07:36:53.1934899Z both the parameters and the buffers of the model. (default: ``False``) 2025-07-17T07:36:53.1934975Z 2025-07-17T07:36:53.1935060Z Example: 2025-07-17T07:36:53.1935202Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.1935325Z >>> loader, optimizer, model, loss_fn = ... 2025-07-17T07:36:53.1935490Z >>> swa_model = torch.optim.swa_utils.AveragedModel(model) 2025-07-17T07:36:53.1935722Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, 2025-07-17T07:36:53.1935830Z >>> T_max=300) 2025-07-17T07:36:53.1935928Z >>> swa_start = 160 2025-07-17T07:36:53.1936066Z >>> swa_scheduler = SWALR(optimizer, swa_lr=0.05) 2025-07-17T07:36:53.1936160Z >>> for i in range(300): 2025-07-17T07:36:53.1936285Z >>> for input, target in loader: 2025-07-17T07:36:53.1936393Z >>> optimizer.zero_grad() 2025-07-17T07:36:53.1936522Z >>> loss_fn(model(input), target).backward() 2025-07-17T07:36:53.1936632Z >>> optimizer.step() 2025-07-17T07:36:53.1936731Z >>> if i > swa_start: 2025-07-17T07:36:53.1936858Z >>> swa_model.update_parameters(model) 2025-07-17T07:36:53.1936978Z >>> swa_scheduler.step() 2025-07-17T07:36:53.1937063Z >>> else: 2025-07-17T07:36:53.1937174Z >>> scheduler.step() 2025-07-17T07:36:53.1937278Z >>> 2025-07-17T07:36:53.1937428Z >>> # Update bn statistics for the swa_model at the end 2025-07-17T07:36:53.1937596Z >>> torch.optim.swa_utils.update_bn(loader, swa_model) 2025-07-17T07:36:53.1937672Z 2025-07-17T07:36:53.1937970Z You can also use custom averaging functions with the `avg_fn` or `multi_avg_fn` parameters. 2025-07-17T07:36:53.1938176Z If no averaging function is provided, the default is to compute 2025-07-17T07:36:53.1938320Z equally-weighted average of the weights (SWA). 2025-07-17T07:36:53.1938393Z 2025-07-17T07:36:53.1938511Z Example: 2025-07-17T07:36:53.1938637Z >>> # xdoctest: +SKIP("undefined variables") 2025-07-17T07:36:53.1938850Z >>> # Compute exponential moving averages of the weights and buffers 2025-07-17T07:36:53.1939016Z >>> ema_model = torch.optim.swa_utils.AveragedModel(model, 2025-07-17T07:36:53.1939227Z >>> torch.optim.swa_utils.get_ema_multi_avg_fn(0.9), use_buffers=True) 2025-07-17T07:36:53.1939314Z 2025-07-17T07:36:53.1939400Z .. note:: 2025-07-17T07:36:53.1939614Z When using SWA/EMA with models containing Batch Normalization you may 2025-07-17T07:36:53.1939876Z need to update the activation statistics for Batch Normalization. 2025-07-17T07:36:53.1940106Z This can be done either by using the :meth:`torch.optim.swa_utils.update_bn` 2025-07-17T07:36:53.1940336Z or by setting :attr:`use_buffers` to `True`. The first approach updates the 2025-07-17T07:36:53.1940573Z statistics in a post-training step by passing data through the model. The 2025-07-17T07:36:53.1940808Z second does it during the parameter update phase by averaging all buffers. 2025-07-17T07:36:53.1941060Z Empirical evidence has shown that updating the statistics in normalization 2025-07-17T07:36:53.1941284Z layers increases accuracy, but you may wish to empirically test which 2025-07-17T07:36:53.1941440Z approach yields the best results in your problem. 2025-07-17T07:36:53.1941522Z 2025-07-17T07:36:53.1941604Z .. note:: 2025-07-17T07:36:53.1941866Z :attr:`avg_fn` and `multi_avg_fn` are not saved in the :meth:`state_dict` of the model. 2025-07-17T07:36:53.1941946Z 2025-07-17T07:36:53.1942027Z .. note:: 2025-07-17T07:36:53.1942235Z When :meth:`update_parameters` is called for the first time (i.e. 2025-07-17T07:36:53.1942415Z :attr:`n_averaged` is `0`) the parameters of `model` are copied 2025-07-17T07:36:53.1942616Z to the parameters of :class:`AveragedModel`. For every subsequent 2025-07-17T07:36:53.1942808Z call of :meth:`update_parameters` the function `avg_fn` is used 2025-07-17T07:36:53.1942911Z to update the parameters. 2025-07-17T07:36:53.1942998Z 2025-07-17T07:36:53.1943218Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-07-17T07:36:53.1943341Z https://arxiv.org/abs/1803.05407 2025-07-17T07:36:53.1943587Z .. _There Are Many Consistent Explanations of Unlabeled Data: Why You Should 2025-07-17T07:36:53.1943669Z Average: 2025-07-17T07:36:53.1943783Z https://arxiv.org/abs/1806.05594 2025-07-17T07:36:53.1943993Z .. _SWALP: Stochastic Weight Averaging in Low-Precision Training: 2025-07-17T07:36:53.1944104Z https://arxiv.org/abs/1904.11943 2025-07-17T07:36:53.1944325Z .. _Stochastic Weight Averaging in Parallel: Large-Batch Training That 2025-07-17T07:36:53.1944434Z Generalizes Well: 2025-07-17T07:36:53.1944543Z https://arxiv.org/abs/2001.02312 2025-07-17T07:36:53.1944650Z .. _Polyak averaging: 2025-07-17T07:36:53.1944812Z https://paperswithcode.com/method/polyak-averaging 2025-07-17T07:36:53.1944889Z 2025-07-17T07:36:53.1945147Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1945248Z 2025-07-17T07:36:53.1945342Z warnings.warn(msg) 2025-07-17T07:36:53.1945428Z 2025-07-17T07:36:53.1945625Z --- Parse Warning: 125 / 136 --- 2025-07-17T07:36:53.1946478Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SWALR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=375. 2025-07-17T07:36:53.1946747Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1946958Z Anneals the learning rate in each parameter group to a fixed value. 2025-07-17T07:36:53.1947077Z 2025-07-17T07:36:53.1947305Z This learning rate scheduler is meant to be used with Stochastic Weight 2025-07-17T07:36:53.1947515Z Averaging (SWA) method (see `torch.optim.swa_utils.AveragedModel`). 2025-07-17T07:36:53.1947600Z 2025-07-17T07:36:53.1947679Z Args: 2025-07-17T07:36:53.1947850Z optimizer (torch.optim.Optimizer): wrapped optimizer 2025-07-17T07:36:53.1948064Z swa_lrs (float or list): the learning rate value for all param groups 2025-07-17T07:36:53.1948190Z together or separately for each group. 2025-07-17T07:36:53.1948448Z annealing_epochs (int): number of epochs in the annealing phase 2025-07-17T07:36:53.1948540Z (default: 10) 2025-07-17T07:36:53.1948753Z annealing_strategy (str): "cos" or "linear"; specifies the annealing 2025-07-17T07:36:53.1948972Z strategy: "cos" for cosine annealing, "linear" for linear annealing 2025-07-17T07:36:53.1949069Z (default: "cos") 2025-07-17T07:36:53.1949244Z last_epoch (int): the index of the last epoch (default: -1) 2025-07-17T07:36:53.1949326Z 2025-07-17T07:36:53.1949498Z The :class:`SWALR` scheduler can be used together with other 2025-07-17T07:36:53.1949708Z schedulers to switch to a constant learning rate late in the training 2025-07-17T07:36:53.1949815Z as in the example below. 2025-07-17T07:36:53.1949892Z 2025-07-17T07:36:53.1949985Z Example: 2025-07-17T07:36:53.1950110Z >>> # xdoctest: +SKIP("Undefined variables") 2025-07-17T07:36:53.1950220Z >>> loader, optimizer, model = ... 2025-07-17T07:36:53.1950338Z >>> lr_lambda = lambda epoch: 0.9 2025-07-17T07:36:53.1950554Z >>> scheduler = torch.optim.lr_scheduler.MultiplicativeLR(optimizer, 2025-07-17T07:36:53.1950656Z >>> lr_lambda=lr_lambda) 2025-07-17T07:36:53.1950831Z >>> swa_scheduler = torch.optim.swa_utils.SWALR(optimizer, 2025-07-17T07:36:53.1951007Z >>> anneal_strategy="linear", anneal_epochs=20, swa_lr=0.05) 2025-07-17T07:36:53.1951109Z >>> swa_start = 160 2025-07-17T07:36:53.1951202Z >>> for i in range(300): 2025-07-17T07:36:53.1951314Z >>> for input, target in loader: 2025-07-17T07:36:53.1951435Z >>> optimizer.zero_grad() 2025-07-17T07:36:53.1951562Z >>> loss_fn(model(input), target).backward() 2025-07-17T07:36:53.1951664Z >>> optimizer.step() 2025-07-17T07:36:53.1951765Z >>> if i > swa_start: 2025-07-17T07:36:53.1951875Z >>> swa_scheduler.step() 2025-07-17T07:36:53.1951959Z >>> else: 2025-07-17T07:36:53.1952065Z >>> scheduler.step() 2025-07-17T07:36:53.1952141Z 2025-07-17T07:36:53.1952360Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-07-17T07:36:53.1952489Z https://arxiv.org/abs/1803.05407 2025-07-17T07:36:53.1952571Z 2025-07-17T07:36:53.1952833Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1952910Z 2025-07-17T07:36:53.1953003Z warnings.warn(msg) 2025-07-17T07:36:53.1953086Z 2025-07-17T07:36:53.1953301Z --- Parse Warning: 126 / 136 --- 2025-07-17T07:36:53.1954207Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_close in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_comparison.py line=1331. 2025-07-17T07:36:53.1954479Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.1954626Z Asserts that ``actual`` and ``expected`` are close. 2025-07-17T07:36:53.1954710Z 2025-07-17T07:36:53.1955074Z If ``actual`` and ``expected`` are strided, non-quantized, real-valued, and finite, they are considered close if 2025-07-17T07:36:53.1955221Z 2025-07-17T07:36:53.1955308Z .. math:: 2025-07-17T07:36:53.1959388Z 2025-07-17T07:36:53.1959787Z \lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert 2025-07-17T07:36:53.1959876Z 2025-07-17T07:36:53.1960230Z Non-finite values (``-inf`` and ``inf``) are only considered close if and only if they are equal. ``NaN``'s are 2025-07-17T07:36:53.1960435Z only considered equal to each other if ``equal_nan`` is ``True``. 2025-07-17T07:36:53.1960524Z 2025-07-17T07:36:53.1960812Z In addition, they are only considered close if they have the same 2025-07-17T07:36:53.1960891Z 2025-07-17T07:36:53.1961099Z - :attr:`~torch.Tensor.device` (if ``check_device`` is ``True``), 2025-07-17T07:36:53.1961227Z - ``dtype`` (if ``check_dtype`` is ``True``), 2025-07-17T07:36:53.1961379Z - ``layout`` (if ``check_layout`` is ``True``), and 2025-07-17T07:36:53.1961503Z - stride (if ``check_stride`` is ``True``). 2025-07-17T07:36:53.1961582Z 2025-07-17T07:36:53.1961889Z If either ``actual`` or ``expected`` is a meta tensor, only the attribute checks will be performed. 2025-07-17T07:36:53.1961966Z 2025-07-17T07:36:53.1962322Z If ``actual`` and ``expected`` are sparse (either having COO, CSR, CSC, BSR, or BSC layout), their strided members are 2025-07-17T07:36:53.1962708Z checked individually. Indices, namely ``indices`` for COO, ``crow_indices`` and ``col_indices`` for CSR and BSR, 2025-07-17T07:36:53.1962936Z or ``ccol_indices`` and ``row_indices`` for CSC and BSC layouts, respectively, 2025-07-17T07:36:53.1963329Z are always checked for equality whereas the values are checked for closeness according to the definition above. 2025-07-17T07:36:53.1963407Z 2025-07-17T07:36:53.1963684Z If ``actual`` and ``expected`` are quantized, they are considered close if they have the same 2025-07-17T07:36:53.1964050Z :meth:`~torch.Tensor.qscheme` and the result of :meth:`~torch.Tensor.dequantize` is close according to the 2025-07-17T07:36:53.1964146Z definition above. 2025-07-17T07:36:53.1964223Z 2025-07-17T07:36:53.1964538Z ``actual`` and ``expected`` can be :class:`~torch.Tensor`'s or any tensor-or-scalar-likes from which 2025-07-17T07:36:53.1964914Z :class:`torch.Tensor`'s can be constructed with :func:`torch.as_tensor`. Except for Python scalars the input types 2025-07-17T07:36:53.1965289Z have to be directly related. In addition, ``actual`` and ``expected`` can be :class:`~collections.abc.Sequence`'s 2025-07-17T07:36:53.1965749Z or :class:`~collections.abc.Mapping`'s in which case they are considered close if their structure matches and all 2025-07-17T07:36:53.1965977Z their elements are considered close according to the above definition. 2025-07-17T07:36:53.1966067Z 2025-07-17T07:36:53.1966157Z .. note:: 2025-07-17T07:36:53.1966239Z 2025-07-17T07:36:53.1966581Z Python scalars are an exception to the type relation requirement, because their :func:`type`, i.e. 2025-07-17T07:36:53.1966901Z :class:`int`, :class:`float`, and :class:`complex`, is equivalent to the ``dtype`` of a tensor-like. Thus, 2025-07-17T07:36:53.1967188Z Python scalars of different types can be checked, but require ``check_dtype=False``. 2025-07-17T07:36:53.1967302Z 2025-07-17T07:36:53.1967383Z Args: 2025-07-17T07:36:53.1967501Z actual (Any): Actual input. 2025-07-17T07:36:53.1967612Z expected (Any): Expected input. 2025-07-17T07:36:53.1967973Z allow_subclasses (bool): If ``True`` (default) and except for Python scalars, inputs of directly related types 2025-07-17T07:36:53.1968144Z are allowed. Otherwise type equality is required. 2025-07-17T07:36:53.1968508Z rtol (Optional[float]): Relative tolerance. If specified ``atol`` must also be specified. If omitted, default 2025-07-17T07:36:53.1968812Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-07-17T07:36:53.1969173Z atol (Optional[float]): Absolute tolerance. If specified ``rtol`` must also be specified. If omitted, default 2025-07-17T07:36:53.1969434Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-07-17T07:36:53.1969691Z equal_nan (Union[bool, str]): If ``True``, two ``NaN`` values will be considered equal. 2025-07-17T07:36:53.1970120Z check_device (bool): If ``True`` (default), asserts that corresponding tensors are on the same 2025-07-17T07:36:53.1970474Z :attr:`~torch.Tensor.device`. If this check is disabled, tensors on different 2025-07-17T07:36:53.1970704Z :attr:`~torch.Tensor.device`'s are moved to the CPU before being compared. 2025-07-17T07:36:53.1971049Z check_dtype (bool): If ``True`` (default), asserts that corresponding tensors have the same ``dtype``. If this 2025-07-17T07:36:53.1971403Z check is disabled, tensors with different ``dtype``'s are promoted to a common ``dtype`` (according to 2025-07-17T07:36:53.1971559Z :func:`torch.promote_types`) before being compared. 2025-07-17T07:36:53.1971913Z check_layout (bool): If ``True`` (default), asserts that corresponding tensors have the same ``layout``. If this 2025-07-17T07:36:53.1972256Z check is disabled, tensors with different ``layout``'s are converted to strided tensors before being 2025-07-17T07:36:53.1972347Z compared. 2025-07-17T07:36:53.1972718Z check_stride (bool): If ``True`` and corresponding tensors are strided, asserts that they have the same stride. 2025-07-17T07:36:53.1973064Z msg (Optional[Union[str, Callable[[str], str]]]): Optional error message to use in case a failure occurs during 2025-07-17T07:36:53.1973417Z the comparison. Can also passed as callable in which case it will be called with the generated message and 2025-07-17T07:36:53.1973540Z should return the new message. 2025-07-17T07:36:53.1973616Z 2025-07-17T07:36:53.1973709Z Raises: 2025-07-17T07:36:53.1973938Z ValueError: If no :class:`torch.Tensor` can be constructed from an input. 2025-07-17T07:36:53.1974103Z ValueError: If only ``rtol`` or ``atol`` is specified. 2025-07-17T07:36:53.1974444Z AssertionError: If corresponding inputs are not Python scalars and are not directly related. 2025-07-17T07:36:53.1974807Z AssertionError: If ``allow_subclasses`` is ``False``, but corresponding inputs are not Python scalars and have 2025-07-17T07:36:53.1974905Z different types. 2025-07-17T07:36:53.1975277Z AssertionError: If the inputs are :class:`~collections.abc.Sequence`'s, but their length does not match. 2025-07-17T07:36:53.1975639Z AssertionError: If the inputs are :class:`~collections.abc.Mapping`'s, but their set of keys do not match. 2025-07-17T07:36:53.1975965Z AssertionError: If corresponding tensors do not have the same :attr:`~torch.Tensor.shape`. 2025-07-17T07:36:53.1976261Z AssertionError: If ``check_layout`` is ``True``, but corresponding tensors do not have the same 2025-07-17T07:36:53.1976416Z :attr:`~torch.Tensor.layout`. 2025-07-17T07:36:53.1976650Z AssertionError: If only one of corresponding tensors is quantized. 2025-07-17T07:36:53.1977037Z AssertionError: If corresponding tensors are quantized, but have different :meth:`~torch.Tensor.qscheme`'s. 2025-07-17T07:36:53.1977340Z AssertionError: If ``check_device`` is ``True``, but corresponding tensors are not on the same 2025-07-17T07:36:53.1977454Z :attr:`~torch.Tensor.device`. 2025-07-17T07:36:53.1977808Z AssertionError: If ``check_dtype`` is ``True``, but corresponding tensors do not have the same ``dtype``. 2025-07-17T07:36:53.1978212Z AssertionError: If ``check_stride`` is ``True``, but corresponding strided tensors do not have the same stride. 2025-07-17T07:36:53.1978574Z AssertionError: If the values of corresponding tensors are not close according to the definition above. 2025-07-17T07:36:53.1978650Z 2025-07-17T07:36:53.1979020Z The following table displays the default ``rtol`` and ``atol`` for different ``dtype``'s. In case of mismatching 2025-07-17T07:36:53.1979167Z ``dtype``'s, the maximum of both tolerances is used. 2025-07-17T07:36:53.1979259Z 2025-07-17T07:36:53.1979432Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1979556Z | ``dtype`` | ``rtol`` | ``atol`` | 2025-07-17T07:36:53.1979671Z +===========================+============+==========+ 2025-07-17T07:36:53.1979805Z | :attr:`~torch.float16` | ``1e-3`` | ``1e-5`` | 2025-07-17T07:36:53.1979929Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1980073Z | :attr:`~torch.bfloat16` | ``1.6e-2`` | ``1e-5`` | 2025-07-17T07:36:53.1980191Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1980333Z | :attr:`~torch.float32` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:53.1980451Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1980577Z | :attr:`~torch.float64` | ``1e-7`` | ``1e-7`` | 2025-07-17T07:36:53.1980709Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1980838Z | :attr:`~torch.complex32` | ``1e-3`` | ``1e-5`` | 2025-07-17T07:36:53.1980959Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1981101Z | :attr:`~torch.complex64` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:53.1981216Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1981362Z | :attr:`~torch.complex128` | ``1e-7`` | ``1e-7`` | 2025-07-17T07:36:53.1981477Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1981607Z | :attr:`~torch.quint8` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:53.1981734Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1981861Z | :attr:`~torch.quint2x4` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:53.1981981Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1982121Z | :attr:`~torch.quint4x2` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:53.1982237Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1982379Z | :attr:`~torch.qint8` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:53.1982495Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1982620Z | :attr:`~torch.qint32` | ``1.3e-6`` | ``1e-5`` | 2025-07-17T07:36:53.1982747Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1982864Z | other | ``0.0`` | ``0.0`` | 2025-07-17T07:36:53.1982979Z +---------------------------+------------+----------+ 2025-07-17T07:36:53.1983067Z 2025-07-17T07:36:53.1983153Z .. note:: 2025-07-17T07:36:53.1983229Z 2025-07-17T07:36:53.1983621Z :func:`~torch.testing.assert_close` is highly configurable with strict default settings. Users are encouraged 2025-07-17T07:36:53.1983996Z to :func:`~functools.partial` it to fit their use case. For example, if an equality check is needed, one might 2025-07-17T07:36:53.1984270Z define an ``assert_equal`` that uses zero tolerances for every ``dtype`` by default: 2025-07-17T07:36:53.1984348Z 2025-07-17T07:36:53.1984443Z >>> import functools 2025-07-17T07:36:53.1984712Z >>> assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=0) 2025-07-17T07:36:53.1984816Z >>> assert_equal(1e-9, 1e-10) 2025-07-17T07:36:53.1984966Z Traceback (most recent call last): 2025-07-17T07:36:53.1985059Z ... 2025-07-17T07:36:53.1985182Z AssertionError: Scalars are not equal! 2025-07-17T07:36:53.1985283Z 2025-07-17T07:36:53.1985389Z Expected 1e-10 but got 1e-09. 2025-07-17T07:36:53.1985511Z Absolute difference: 9.000000000000001e-10 2025-07-17T07:36:53.1985626Z Relative difference: 9.0 2025-07-17T07:36:53.1985702Z 2025-07-17T07:36:53.1985786Z Examples: 2025-07-17T07:36:53.1985910Z >>> # tensor to tensor comparison 2025-07-17T07:36:53.1986087Z >>> expected = torch.tensor([1e0, 1e-1, 1e-2]) 2025-07-17T07:36:53.1986219Z >>> actual = torch.acos(torch.cos(expected)) 2025-07-17T07:36:53.1986377Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:53.1986454Z 2025-07-17T07:36:53.1986562Z >>> # scalar to scalar comparison 2025-07-17T07:36:53.1986669Z >>> import math 2025-07-17T07:36:53.1986775Z >>> expected = math.sqrt(2.0) 2025-07-17T07:36:53.1986893Z >>> actual = 2.0 / math.sqrt(2.0) 2025-07-17T07:36:53.1987035Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:53.1987115Z 2025-07-17T07:36:53.1987251Z >>> # numpy array to numpy array comparison 2025-07-17T07:36:53.1987351Z >>> import numpy as np 2025-07-17T07:36:53.1987469Z >>> expected = np.array([1e0, 1e-1, 1e-2]) 2025-07-17T07:36:53.1987603Z >>> actual = np.arccos(np.cos(expected)) 2025-07-17T07:36:53.1987744Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:53.1987820Z 2025-07-17T07:36:53.1987948Z >>> # sequence to sequence comparison 2025-07-17T07:36:53.1988044Z >>> import numpy as np 2025-07-17T07:36:53.1988301Z >>> # The types of the sequences do not have to match. They only have to have the same 2025-07-17T07:36:53.1988433Z >>> # length and their elements have to match. 2025-07-17T07:36:53.1988586Z >>> expected = [torch.tensor([1.0]), 2.0, np.array(3.0)] 2025-07-17T07:36:53.1988700Z >>> actual = tuple(expected) 2025-07-17T07:36:53.1988843Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:53.1988922Z 2025-07-17T07:36:53.1989051Z >>> # mapping to mapping comparison 2025-07-17T07:36:53.1989169Z >>> from collections import OrderedDict 2025-07-17T07:36:53.1989265Z >>> import numpy as np 2025-07-17T07:36:53.1989376Z >>> foo = torch.tensor(1.0) 2025-07-17T07:36:53.1989466Z >>> bar = 2.0 2025-07-17T07:36:53.1989574Z >>> baz = np.array(3.0) 2025-07-17T07:36:53.1989822Z >>> # The types and a possible ordering of mappings do not have to match. They only 2025-07-17T07:36:53.1990021Z >>> # have to have the same set of keys and their elements have to match. 2025-07-17T07:36:53.1990237Z >>> expected = OrderedDict([("foo", foo), ("bar", bar), ("baz", baz)]) 2025-07-17T07:36:53.1990368Z >>> actual = {"baz": baz, "bar": bar, "foo": foo} 2025-07-17T07:36:53.1990513Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:53.1990604Z 2025-07-17T07:36:53.1990767Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-07-17T07:36:53.1990885Z >>> actual = expected.clone() 2025-07-17T07:36:53.1991050Z >>> # By default, directly related instances can be compared 2025-07-17T07:36:53.1991265Z >>> torch.testing.assert_close(torch.nn.Parameter(actual), expected) 2025-07-17T07:36:53.1991469Z >>> # This check can be made more strict with allow_subclasses=False 2025-07-17T07:36:53.1991581Z >>> torch.testing.assert_close( 2025-07-17T07:36:53.1991776Z ... torch.nn.Parameter(actual), expected, allow_subclasses=False 2025-07-17T07:36:53.1991898Z ... ) 2025-07-17T07:36:53.1992010Z Traceback (most recent call last): 2025-07-17T07:36:53.1992089Z ... 2025-07-17T07:36:53.1992304Z TypeError: No comparison pair was able to handle inputs of type 2025-07-17T07:36:53.1992516Z and . 2025-07-17T07:36:53.1992752Z >>> # If the inputs are not directly related, they are never considered close 2025-07-17T07:36:53.1992920Z >>> torch.testing.assert_close(actual.numpy(), expected) 2025-07-17T07:36:53.1993034Z Traceback (most recent call last): 2025-07-17T07:36:53.1993127Z ... 2025-07-17T07:36:53.1993461Z TypeError: No comparison pair was able to handle inputs of type 2025-07-17T07:36:53.1993570Z and . 2025-07-17T07:36:53.1993844Z >>> # Exceptions to these rules are Python scalars. They can be checked regardless of 2025-07-17T07:36:53.1993961Z >>> # their type if check_dtype=False. 2025-07-17T07:36:53.1994144Z >>> torch.testing.assert_close(1.0, 1, check_dtype=False) 2025-07-17T07:36:53.1994222Z 2025-07-17T07:36:53.1994318Z >>> # NaN != NaN by default. 2025-07-17T07:36:53.1994454Z >>> expected = torch.tensor(float("Nan")) 2025-07-17T07:36:53.1994564Z >>> actual = expected.clone() 2025-07-17T07:36:53.1994705Z >>> torch.testing.assert_close(actual, expected) 2025-07-17T07:36:53.1994832Z Traceback (most recent call last): 2025-07-17T07:36:53.1994912Z ... 2025-07-17T07:36:53.1995037Z AssertionError: Scalars are not close! 2025-07-17T07:36:53.1995136Z 2025-07-17T07:36:53.1995238Z Expected nan but got nan. 2025-07-17T07:36:53.1995389Z Absolute difference: nan (up to 1e-05 allowed) 2025-07-17T07:36:53.1995593Z Relative difference: nan (up to 1.3e-06 allowed) 2025-07-17T07:36:53.1995792Z >>> torch.testing.assert_close(actual, expected, equal_nan=True) 2025-07-17T07:36:53.1995881Z 2025-07-17T07:36:53.1995999Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-07-17T07:36:53.1996113Z >>> actual = torch.tensor([1.0, 4.0, 5.0]) 2025-07-17T07:36:53.1996264Z >>> # The default error message can be overwritten. 2025-07-17T07:36:53.1996552Z >>> torch.testing.assert_close(actual, expected, msg="Argh, the tensors are not close!") 2025-07-17T07:36:53.1996677Z Traceback (most recent call last): 2025-07-17T07:36:53.1996757Z ... 2025-07-17T07:36:53.1996907Z AssertionError: Argh, the tensors are not close! 2025-07-17T07:36:53.1997138Z >>> # If msg is a callable, it can be used to augment the generated message with 2025-07-17T07:36:53.1997236Z >>> # extra information 2025-07-17T07:36:53.1997349Z >>> torch.testing.assert_close( 2025-07-17T07:36:53.1997560Z ... actual, expected, msg=lambda msg: f"Header\n\n{msg}\n\nFooter" 2025-07-17T07:36:53.1997638Z ... ) 2025-07-17T07:36:53.1997752Z Traceback (most recent call last): 2025-07-17T07:36:53.1997842Z ... 2025-07-17T07:36:53.1997941Z AssertionError: Header 2025-07-17T07:36:53.1998072Z 2025-07-17T07:36:53.1998176Z Tensor-likes are not close! 2025-07-17T07:36:53.1998261Z 2025-07-17T07:36:53.1998382Z Mismatched elements: 2 / 3 (66.7%) 2025-07-17T07:36:53.1998603Z Greatest absolute difference: 2.0 at index (1,) (up to 1e-05 allowed) 2025-07-17T07:36:53.1998832Z Greatest relative difference: 1.0 at index (1,) (up to 1.3e-06 allowed) 2025-07-17T07:36:53.1998933Z 2025-07-17T07:36:53.1999013Z Footer 2025-07-17T07:36:53.1999095Z 2025-07-17T07:36:53.1999358Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.1999463Z 2025-07-17T07:36:53.1999558Z warnings.warn(msg) 2025-07-17T07:36:53.1999649Z 2025-07-17T07:36:53.1999886Z --- Parse Warning: 127 / 136 --- 2025-07-17T07:36:53.2000832Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_pytree_node in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py line=134. 2025-07-17T07:36:53.2001094Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.2001233Z Register a container-like type as pytree node. 2025-07-17T07:36:53.2001376Z 2025-07-17T07:36:53.2001455Z Args: 2025-07-17T07:36:53.2001662Z cls (type): A Python type to treat as an internal pytree node. 2025-07-17T07:36:53.2001940Z flatten_fn (callable): A function to be used during flattening, taking an instance of 2025-07-17T07:36:53.2002183Z ``cls`` and returning a pair, with (1) an iterable for the children to be flattened 2025-07-17T07:36:53.2002479Z recursively, and (2) some hashable auxiliary data to be stored in the treespec and to be 2025-07-17T07:36:53.2002593Z passed to the ``unflatten_fn``. 2025-07-17T07:36:53.2002865Z unflatten_fn (callable): A function taking two arguments: the auxiliary data that was 2025-07-17T07:36:53.2003132Z returned by ``flatten_fn`` and stored in the treespec, and the unflattened children. 2025-07-17T07:36:53.2003281Z The function should return an instance of ``cls``. 2025-07-17T07:36:53.2003556Z serialized_type_name (str, optional): A keyword argument used to specify the fully 2025-07-17T07:36:53.2003715Z qualified name used when serializing the tree spec. 2025-07-17T07:36:53.2004023Z to_dumpable_context (callable, optional): An optional keyword argument to custom specify how 2025-07-17T07:36:53.2004311Z to convert the context of the pytree to a custom json dumpable representation. This is 2025-07-17T07:36:53.2004578Z used for json serialization, which is being used in :mod:`torch.export` right now. 2025-07-17T07:36:53.2004876Z from_dumpable_context (callable, optional): An optional keyword argument to custom specify 2025-07-17T07:36:53.2005149Z how to convert the custom json dumpable representation of the context back to the 2025-07-17T07:36:53.2005489Z original context. This is used for json deserialization, which is being used in 2025-07-17T07:36:53.2005620Z :mod:`torch.export` right now. 2025-07-17T07:36:53.2005699Z 2025-07-17T07:36:53.2005790Z Example:: 2025-07-17T07:36:53.2005878Z 2025-07-17T07:36:53.2005974Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.2006117Z >>> # Registry a Python type with lambda functions 2025-07-17T07:36:53.2006233Z >>> register_pytree_node( 2025-07-17T07:36:53.2006319Z ... set, 2025-07-17T07:36:53.2006441Z ... lambda s: (sorted(s), None, None), 2025-07-17T07:36:53.2006577Z ... lambda children, _: set(children), 2025-07-17T07:36:53.2006656Z ... ) 2025-07-17T07:36:53.2006749Z 2025-07-17T07:36:53.2007036Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.2007112Z 2025-07-17T07:36:53.2007216Z warnings.warn(msg) 2025-07-17T07:36:53.2007291Z 2025-07-17T07:36:53.2007489Z --- Parse Warning: 128 / 136 --- 2025-07-17T07:36:53.2008495Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SelectiveCheckpointContext in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1218. 2025-07-17T07:36:53.2008754Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.2008870Z 2025-07-17T07:36:53.2009082Z Context passed to policy function during selective checkpointing. 2025-07-17T07:36:53.2009160Z 2025-07-17T07:36:53.2009404Z This class is used to pass relevant metadata to the policy function during 2025-07-17T07:36:53.2009666Z selective checkpointing. The metadata includes whether the current invocation 2025-07-17T07:36:53.2009825Z of the policy function is during recomputation or not. 2025-07-17T07:36:53.2009912Z 2025-07-17T07:36:53.2009996Z Example: 2025-07-17T07:36:53.2010096Z >>> # xdoctest: +SKIP(stub) 2025-07-17T07:36:53.2010191Z >>> 2025-07-17T07:36:53.2010360Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-07-17T07:36:53.2010472Z >>> print(ctx.is_recompute) 2025-07-17T07:36:53.2010562Z >>> 2025-07-17T07:36:53.2010831Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-07-17T07:36:53.2010922Z >>> 2025-07-17T07:36:53.2011063Z >>> out = torch.utils.checkpoint.checkpoint( 2025-07-17T07:36:53.2011148Z >>> fn, x, y, 2025-07-17T07:36:53.2011256Z >>> use_reentrant=False, 2025-07-17T07:36:53.2011351Z >>> context_fn=context_fn, 2025-07-17T07:36:53.2011430Z >>> ) 2025-07-17T07:36:53.2011518Z 2025-07-17T07:36:53.2011768Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.2011844Z 2025-07-17T07:36:53.2011947Z warnings.warn(msg) 2025-07-17T07:36:53.2012022Z 2025-07-17T07:36:53.2012202Z --- Parse Warning: 129 / 136 --- 2025-07-17T07:36:53.2013222Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=create_selective_checkpoint_contexts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1358. 2025-07-17T07:36:53.2013479Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.2013568Z 2025-07-17T07:36:53.2013799Z Helper to avoid recomputing certain ops during activation checkpointing. 2025-07-17T07:36:53.2013874Z 2025-07-17T07:36:53.2014101Z Use this with `torch.utils.checkpoint.checkpoint` to control which 2025-07-17T07:36:53.2014261Z operations are recomputed during the backward pass. 2025-07-17T07:36:53.2014338Z 2025-07-17T07:36:53.2014424Z Args: 2025-07-17T07:36:53.2014538Z policy_fn_or_list (Callable or List): 2025-07-17T07:36:53.2014698Z - If a policy function is provided, it should accept a 2025-07-17T07:36:53.2014952Z :class:`SelectiveCheckpointContext`, the :class:`OpOverload`, args and 2025-07-17T07:36:53.2015158Z kwargs to the op, and return a :class:`CheckpointPolicy` enum value 2025-07-17T07:36:53.2015403Z indicating whether the execution of the op should be recomputed or not. 2025-07-17T07:36:53.2015600Z - If a list of operations is provided, it is equivalent to a policy 2025-07-17T07:36:53.2015784Z returning `CheckpointPolicy.MUST_SAVE` for the specified 2025-07-17T07:36:53.2016014Z operations and `CheckpointPolicy.PREFER_RECOMPUTE` for all other 2025-07-17T07:36:53.2016101Z operations. 2025-07-17T07:36:53.2016320Z allow_cache_entry_mutation (bool, optional): By default, an error is 2025-07-17T07:36:53.2016556Z raised if any tensors cached by selective activation checkpoint are 2025-07-17T07:36:53.2016762Z mutated in order to ensure correctness. If set to `True`, this check 2025-07-17T07:36:53.2016863Z is disabled. 2025-07-17T07:36:53.2016946Z Returns: 2025-07-17T07:36:53.2017057Z A tuple of two context managers. 2025-07-17T07:36:53.2017143Z 2025-07-17T07:36:53.2017225Z Example: 2025-07-17T07:36:53.2017329Z >>> # xdoctest: +REQUIRES(LINUX) 2025-07-17T07:36:53.2017429Z >>> import functools 2025-07-17T07:36:53.2017533Z >>> 2025-07-17T07:36:53.2017656Z >>> x = torch.rand(10, 10, requires_grad=True) 2025-07-17T07:36:53.2017785Z >>> y = torch.rand(10, 10, requires_grad=True) 2025-07-17T07:36:53.2017863Z >>> 2025-07-17T07:36:53.2017963Z >>> ops_to_save = [ 2025-07-17T07:36:53.2018071Z >>> torch.ops.aten.mm.default, 2025-07-17T07:36:53.2018152Z >>> ] 2025-07-17T07:36:53.2018239Z >>> 2025-07-17T07:36:53.2018360Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-07-17T07:36:53.2018459Z >>> if op in ops_to_save: 2025-07-17T07:36:53.2018593Z >>> return CheckpointPolicy.MUST_SAVE 2025-07-17T07:36:53.2018675Z >>> else: 2025-07-17T07:36:53.2018874Z >>> return CheckpointPolicy.PREFER_RECOMPUTE 2025-07-17T07:36:53.2018965Z >>> 2025-07-17T07:36:53.2019233Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-07-17T07:36:53.2019312Z >>> 2025-07-17T07:36:53.2019417Z >>> # or equivalently 2025-07-17T07:36:53.2019689Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, ops_to_save) 2025-07-17T07:36:53.2019776Z >>> 2025-07-17T07:36:53.2019864Z >>> def fn(x, y): 2025-07-17T07:36:53.2020060Z >>> return torch.sigmoid(torch.matmul(torch.matmul(x, y), y)) * y 2025-07-17T07:36:53.2020148Z >>> 2025-07-17T07:36:53.2020288Z >>> out = torch.utils.checkpoint.checkpoint( 2025-07-17T07:36:53.2020377Z >>> fn, x, y, 2025-07-17T07:36:53.2020485Z >>> use_reentrant=False, 2025-07-17T07:36:53.2020591Z >>> context_fn=context_fn, 2025-07-17T07:36:53.2020913Z >>> ) 2025-07-17T07:36:53.2021150Z 2025-07-17T07:36:53.2021524Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.2021986Z 2025-07-17T07:36:53.2022199Z warnings.warn(msg) 2025-07-17T07:36:53.2022447Z 2025-07-17T07:36:53.2022738Z --- Parse Warning: 130 / 136 --- 2025-07-17T07:36:53.2023902Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CppExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1147. 2025-07-17T07:36:53.2025214Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.2025674Z 2025-07-17T07:36:53.2025909Z Create a :class:`setuptools.Extension` for C++. 2025-07-17T07:36:53.2026243Z 2025-07-17T07:36:53.2026587Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-07-17T07:36:53.2027163Z bare minimum (but often sufficient) arguments to build a C++ extension. 2025-07-17T07:36:53.2027574Z 2025-07-17T07:36:53.2027887Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-07-17T07:36:53.2028341Z constructor. Full list arguments can be found at 2025-07-17T07:36:53.2028935Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-07-17T07:36:53.2029458Z 2025-07-17T07:36:53.2029655Z .. warning:: 2025-07-17T07:36:53.2030011Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-07-17T07:36:53.2030567Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-07-17T07:36:53.2031123Z the user's responsibility in their library to not use APIs from 2025-07-17T07:36:53.2031658Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-07-17T07:36:53.2032279Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-07-17T07:36:53.2032855Z example, to give access to custom ops from python, the library should 2025-07-17T07:36:53.2033312Z register the ops through the dispatcher. 2025-07-17T07:36:53.2033615Z 2025-07-17T07:36:53.2033944Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-07-17T07:36:53.2034504Z as a compile flag when py_limited_api is specified as an option for 2025-07-17T07:36:53.2035027Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-07-17T07:36:53.2035552Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-07-17T07:36:53.2036097Z safety, and sanity in order to encourage best practices. To target a 2025-07-17T07:36:53.2036637Z different version, set min_supported_cpython to the hexcode of the 2025-07-17T07:36:53.2037056Z CPython version of choice. 2025-07-17T07:36:53.2037325Z 2025-07-17T07:36:53.2037518Z Example: 2025-07-17T07:36:53.2037778Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.2038109Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-07-17T07:36:53.2038479Z >>> from setuptools import setup 2025-07-17T07:36:53.2038914Z >>> from torch.utils.cpp_extension import BuildExtension, CppExtension 2025-07-17T07:36:53.2039322Z >>> setup( 2025-07-17T07:36:53.2039552Z ... name='extension', 2025-07-17T07:36:53.2039833Z ... ext_modules=[ 2025-07-17T07:36:53.2040090Z ... CppExtension( 2025-07-17T07:36:53.2040372Z ... name='extension', 2025-07-17T07:36:53.2040694Z ... sources=['extension.cpp'], 2025-07-17T07:36:53.2041036Z ... extra_compile_args=['-g'], 2025-07-17T07:36:53.2041409Z ... extra_link_args=['-Wl,--no-as-needed', '-lm']) 2025-07-17T07:36:53.2041751Z ... ], 2025-07-17T07:36:53.2041971Z ... cmdclass={ 2025-07-17T07:36:53.2042231Z ... 'build_ext': BuildExtension 2025-07-17T07:36:53.2042538Z ... }) 2025-07-17T07:36:53.2042749Z 2025-07-17T07:36:53.2043100Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.2043543Z 2025-07-17T07:36:53.2043748Z warnings.warn(msg) 2025-07-17T07:36:53.2043982Z 2025-07-17T07:36:53.2044284Z --- Parse Warning: 131 / 136 --- 2025-07-17T07:36:53.2045518Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CUDAExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1217. 2025-07-17T07:36:53.2046835Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.2047285Z 2025-07-17T07:36:53.2047548Z Create a :class:`setuptools.Extension` for CUDA/C++. 2025-07-17T07:36:53.2047894Z 2025-07-17T07:36:53.2048234Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-07-17T07:36:53.2048797Z bare minimum (but often sufficient) arguments to build a CUDA/C++ 2025-07-17T07:36:53.2049343Z extension. This includes the CUDA include path, library path and runtime 2025-07-17T07:36:53.2049760Z library. 2025-07-17T07:36:53.2049966Z 2025-07-17T07:36:53.2050282Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-07-17T07:36:53.2050740Z constructor. Full list arguments can be found at 2025-07-17T07:36:53.2051324Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-07-17T07:36:53.2051838Z 2025-07-17T07:36:53.2052035Z .. warning:: 2025-07-17T07:36:53.2052429Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-07-17T07:36:53.2052987Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-07-17T07:36:53.2053518Z the user's responsibility in their library to not use APIs from 2025-07-17T07:36:53.2054049Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-07-17T07:36:53.2054611Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-07-17T07:36:53.2055158Z example, to give access to custom ops from python, the library should 2025-07-17T07:36:53.2055646Z register the ops through the dispatcher. 2025-07-17T07:36:53.2055947Z 2025-07-17T07:36:53.2056277Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-07-17T07:36:53.2056830Z as a compile flag when py_limited_api is specified as an option for 2025-07-17T07:36:53.2057348Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-07-17T07:36:53.2057885Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-07-17T07:36:53.2058425Z safety, and sanity in order to encourage best practices. To target a 2025-07-17T07:36:53.2058968Z different version, set min_supported_cpython to the hexcode of the 2025-07-17T07:36:53.2059449Z CPython version of choice. 2025-07-17T07:36:53.2059720Z 2025-07-17T07:36:53.2059917Z Example: 2025-07-17T07:36:53.2060126Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.2060449Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-07-17T07:36:53.2060817Z >>> from setuptools import setup 2025-07-17T07:36:53.2061249Z >>> from torch.utils.cpp_extension import BuildExtension, CUDAExtension 2025-07-17T07:36:53.2061674Z >>> setup( 2025-07-17T07:36:53.2061912Z ... name='cuda_extension', 2025-07-17T07:36:53.2062198Z ... ext_modules=[ 2025-07-17T07:36:53.2062471Z ... CUDAExtension( 2025-07-17T07:36:53.2062772Z ... name='cuda_extension', 2025-07-17T07:36:53.2063158Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-07-17T07:36:53.2063553Z ... extra_compile_args={'cxx': ['-g'], 2025-07-17T07:36:53.2063914Z ... 'nvcc': ['-O2']}, 2025-07-17T07:36:53.2064290Z ... extra_link_args=['-Wl,--no-as-needed', '-lcuda']) 2025-07-17T07:36:53.2064631Z ... ], 2025-07-17T07:36:53.2064856Z ... cmdclass={ 2025-07-17T07:36:53.2065135Z ... 'build_ext': BuildExtension 2025-07-17T07:36:53.2065423Z ... }) 2025-07-17T07:36:53.2065630Z 2025-07-17T07:36:53.2065837Z Compute capabilities: 2025-07-17T07:36:53.2066068Z 2025-07-17T07:36:53.2066470Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-07-17T07:36:53.2067179Z building process of the extension, plus PTX. If down the road a new card is installed the 2025-07-17T07:36:53.2067882Z extension may need to be recompiled. If a visible card has a compute capability (CC) that's 2025-07-17T07:36:53.2068582Z newer than the newest version for which your nvcc can build fully-compiled binaries, PyTorch 2025-07-17T07:36:53.2069285Z will make nvcc fall back to building kernels with the newest version of PTX your nvcc does 2025-07-17T07:36:53.2069811Z support (see below for details on PTX). 2025-07-17T07:36:53.2070360Z 2025-07-17T07:36:53.2070783Z You can override the default behavior using `TORCH_CUDA_ARCH_LIST` to explicitly specify which 2025-07-17T07:36:53.2071333Z CCs you want the extension to support: 2025-07-17T07:36:53.2071634Z 2025-07-17T07:36:53.2071911Z ``TORCH_CUDA_ARCH_LIST="6.1 8.6" python build_my_extension.py`` 2025-07-17T07:36:53.2072445Z ``TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" python build_my_extension.py`` 2025-07-17T07:36:53.2072966Z 2025-07-17T07:36:53.2073386Z The +PTX option causes extension kernel binaries to include PTX instructions for the specified 2025-07-17T07:36:53.2074144Z CC. PTX is an intermediate representation that allows kernels to runtime-compile for any CC >= 2025-07-17T07:36:53.2074887Z the specified CC (for example, 8.6+PTX generates PTX that can runtime-compile for any GPU with 2025-07-17T07:36:53.2075602Z CC >= 8.6). This improves your binary's forward compatibility. However, relying on older PTX to 2025-07-17T07:36:53.2076328Z provide forward compat by runtime-compiling for newer CCs can modestly reduce performance on 2025-07-17T07:36:53.2077081Z those newer CCs. If you know exact CC(s) of the GPUs you want to target, you're always better 2025-07-17T07:36:53.2077791Z off specifying them individually. For example, if you want your extension to run on 8.0 and 8.6, 2025-07-17T07:36:53.2078582Z "8.0+PTX" would work functionally because it includes PTX that can runtime-compile for 8.6, but 2025-07-17T07:36:53.2079102Z "8.0 8.6" would be better. 2025-07-17T07:36:53.2079357Z 2025-07-17T07:36:53.2079766Z Note that while it's possible to include all supported archs, the more archs get included the 2025-07-17T07:36:53.2080537Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-07-17T07:36:53.2081024Z 2025-07-17T07:36:53.2081460Z Note that CUDA-11.5 nvcc will hit internal compiler error while parsing torch/extension.h on Windows. 2025-07-17T07:36:53.2082115Z To workaround the issue, move python binding logic to pure C++ file. 2025-07-17T07:36:53.2082527Z 2025-07-17T07:36:53.2082718Z Example use: 2025-07-17T07:36:53.2082941Z #include 2025-07-17T07:36:53.2083279Z at::Tensor SigmoidAlphaBlendForwardCuda(....) 2025-07-17T07:36:53.2083615Z 2025-07-17T07:36:53.2083806Z Instead of: 2025-07-17T07:36:53.2084031Z #include 2025-07-17T07:36:53.2084397Z torch::Tensor SigmoidAlphaBlendForwardCuda(...) 2025-07-17T07:36:53.2084737Z 2025-07-17T07:36:53.2085107Z Currently open issue for nvcc bug: https://github.com/pytorch/pytorch/issues/69460 2025-07-17T07:36:53.2086096Z Complete workaround code example: https://github.com/facebookresearch/pytorch3d/commit/cb170ac024a949f1f9614ffe6af1c38d972f7d48 2025-07-17T07:36:53.2086803Z 2025-07-17T07:36:53.2087005Z Relocatable device code linking: 2025-07-17T07:36:53.2087291Z 2025-07-17T07:36:53.2087678Z If you want to reference device symbols across compilation units (across object files), 2025-07-17T07:36:53.2088341Z the object files need to be built with `relocatable device code` (-rdc=true or -dc). 2025-07-17T07:36:53.2089070Z An exception to this rule is "dynamic parallelism" (nested kernel launches) which is not used a lot anymore. 2025-07-17T07:36:53.2089877Z `Relocatable device code` is less optimized so it needs to be used only on object files that need it. 2025-07-17T07:36:53.2090642Z Using `-dlto` (Device Link Time Optimization) at the device code compilation step and `dlink` step 2025-07-17T07:36:53.2091260Z helps reduce the protentional perf degradation of `-rdc`. 2025-07-17T07:36:53.2091712Z Note that it needs to be used at both steps to be useful. 2025-07-17T07:36:53.2092068Z 2025-07-17T07:36:53.2092543Z If you have `rdc` objects you need to have an extra `-dlink` (device linking) step before the CPU symbol linking step. 2025-07-17T07:36:53.2093184Z There is also a case where `-dlink` is used without `-rdc`: 2025-07-17T07:36:53.2093724Z when an extension is linked against a static lib containing rdc-compiled objects 2025-07-17T07:36:53.2094316Z like the [NVSHMEM library](https://developer.nvidia.com/nvshmem). 2025-07-17T07:36:53.2094707Z 2025-07-17T07:36:53.2095012Z Note: Ninja is required to build a CUDA Extension with RDC linking. 2025-07-17T07:36:53.2095402Z 2025-07-17T07:36:53.2095649Z Example: 2025-07-17T07:36:53.2095865Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.2096193Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-07-17T07:36:53.2096546Z >>> CUDAExtension( 2025-07-17T07:36:53.2096808Z ... name='cuda_extension', 2025-07-17T07:36:53.2097188Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-07-17T07:36:53.2097557Z ... dlink=True, 2025-07-17T07:36:53.2097839Z ... dlink_libraries=["dlink_lib"], 2025-07-17T07:36:53.2098187Z ... extra_compile_args={'cxx': ['-g'], 2025-07-17T07:36:53.2098550Z ... 'nvcc': ['-O2', '-rdc=true']}) 2025-07-17T07:36:53.2098890Z 2025-07-17T07:36:53.2099262Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.2099715Z 2025-07-17T07:36:53.2099913Z warnings.warn(msg) 2025-07-17T07:36:53.2100161Z 2025-07-17T07:36:53.2100513Z --- Parse Warning: 132 / 136 --- 2025-07-17T07:36:53.2101679Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyclExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1408. 2025-07-17T07:36:53.2103074Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.2103544Z 2025-07-17T07:36:53.2103822Z Creates a :class:`setuptools.Extension` for SYCL/C++. 2025-07-17T07:36:53.2104171Z 2025-07-17T07:36:53.2104533Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-07-17T07:36:53.2105103Z bare minimum (but often sufficient) arguments to build a SYCL/C++ 2025-07-17T07:36:53.2105501Z extension. 2025-07-17T07:36:53.2105719Z 2025-07-17T07:36:53.2106042Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-07-17T07:36:53.2106461Z constructor. 2025-07-17T07:36:53.2106673Z 2025-07-17T07:36:53.2106881Z .. warning:: 2025-07-17T07:36:53.2107254Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-07-17T07:36:53.2107800Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-07-17T07:36:53.2108335Z the user's responsibility in their library to not use APIs from 2025-07-17T07:36:53.2108888Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-07-17T07:36:53.2109442Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-07-17T07:36:53.2109999Z example, to give access to custom ops from python, the library should 2025-07-17T07:36:53.2110458Z register the ops through the dispatcher. 2025-07-17T07:36:53.2110777Z 2025-07-17T07:36:53.2111100Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-07-17T07:36:53.2111642Z as a compile flag when py_limited_api is specified as an option for 2025-07-17T07:36:53.2112171Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-07-17T07:36:53.2112704Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-07-17T07:36:53.2113261Z safety, and sanity in order to encourage best practices. To target a 2025-07-17T07:36:53.2113803Z different version, set min_supported_cpython to the hexcode of the 2025-07-17T07:36:53.2114241Z CPython version of choice. 2025-07-17T07:36:53.2114504Z 2025-07-17T07:36:53.2114694Z Example: 2025-07-17T07:36:53.2114919Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.2115233Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-07-17T07:36:53.2115721Z >>> from torch.utils.cpp_extension import BuildExtension, SyclExtension 2025-07-17T07:36:53.2116145Z >>> setup( 2025-07-17T07:36:53.2116379Z ... name='xpu_extension', 2025-07-17T07:36:53.2116673Z ... ext_modules=[ 2025-07-17T07:36:53.2116951Z ... SyclExtension( 2025-07-17T07:36:53.2117276Z ... name='xpu_extension', 2025-07-17T07:36:53.2117664Z ... sources=['extension.cpp', 'extension_kernel.cpp'], 2025-07-17T07:36:53.2118126Z ... extra_compile_args={'cxx': ['-g', '-std=c++20', '-fPIC']}) 2025-07-17T07:36:53.2118515Z ... ], 2025-07-17T07:36:53.2118768Z ... cmdclass={ 2025-07-17T07:36:53.2119044Z ... 'build_ext': BuildExtension 2025-07-17T07:36:53.2119353Z ... }) 2025-07-17T07:36:53.2119555Z 2025-07-17T07:36:53.2119967Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-07-17T07:36:53.2120680Z building process of the extension. If down the road a new card is installed the 2025-07-17T07:36:53.2121300Z extension may need to be recompiled. You can override the default behavior using 2025-07-17T07:36:53.2121978Z `TORCH_XPU_ARCH_LIST` to explicitly specify which device architectures you want the extension 2025-07-17T07:36:53.2122495Z to support: 2025-07-17T07:36:53.2122711Z 2025-07-17T07:36:53.2123011Z ``TORCH_XPU_ARCH_LIST="pvc,xe-lpg" python build_my_extension.py`` 2025-07-17T07:36:53.2123411Z 2025-07-17T07:36:53.2123873Z Note that while it's possible to include all supported archs, the more archs get included the 2025-07-17T07:36:53.2124578Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-07-17T07:36:53.2125068Z 2025-07-17T07:36:53.2125439Z Note: Ninja is required to build SyclExtension. 2025-07-17T07:36:53.2125760Z 2025-07-17T07:36:53.2126124Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.2126576Z 2025-07-17T07:36:53.2126774Z warnings.warn(msg) 2025-07-17T07:36:53.2127023Z 2025-07-17T07:36:53.2127346Z --- Parse Warning: 133 / 136 --- 2025-07-17T07:36:53.2128459Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1585. 2025-07-17T07:36:53.2129698Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.2130162Z 2025-07-17T07:36:53.2130423Z Load a PyTorch C++ extension just-in-time (JIT). 2025-07-17T07:36:53.2130749Z 2025-07-17T07:36:53.2131064Z To load an extension, a Ninja build file is emitted, which is used to 2025-07-17T07:36:53.2131594Z compile the given sources into a dynamic library. This library is 2025-07-17T07:36:53.2132138Z subsequently loaded into the current Python process as a module and 2025-07-17T07:36:53.2132597Z returned from this function, ready for use. 2025-07-17T07:36:53.2132915Z 2025-07-17T07:36:53.2133228Z By default, the directory to which the build file is emitted and the 2025-07-17T07:36:53.2133778Z resulting library compiled to is ``/torch_extensions/``, where 2025-07-17T07:36:53.2134346Z ```` is the temporary folder on the current platform and ```` 2025-07-17T07:36:53.2134884Z the name of the extension. This location can be overridden in two ways. 2025-07-17T07:36:53.2135417Z First, if the ``TORCH_EXTENSIONS_DIR`` environment variable is set, it 2025-07-17T07:36:53.2135963Z replaces ``/torch_extensions`` and all extensions will be compiled 2025-07-17T07:36:53.2136516Z into subfolders of this directory. Second, if the ``build_directory`` 2025-07-17T07:36:53.2137078Z argument to this function is supplied, it overrides the entire path, i.e. 2025-07-17T07:36:53.2137583Z the library will be compiled into that folder directly. 2025-07-17T07:36:53.2137942Z 2025-07-17T07:36:53.2138260Z To compile the sources, the default system compiler (``c++``) is used, 2025-07-17T07:36:53.2138815Z which can be overridden by setting the ``CXX`` environment variable. To pass 2025-07-17T07:36:53.2139451Z additional arguments to the compilation process, ``extra_cflags`` or 2025-07-17T07:36:53.2140020Z ``extra_ldflags`` can be provided. For example, to compile your extension 2025-07-17T07:36:53.2140575Z with optimizations, pass ``extra_cflags=['-O3']``. You can also use 2025-07-17T07:36:53.2141052Z ``extra_cflags`` to pass further include directories. 2025-07-17T07:36:53.2141402Z 2025-07-17T07:36:53.2141754Z CUDA support with mixed compilation is provided. Simply pass CUDA source 2025-07-17T07:36:53.2142284Z files (``.cu`` or ``.cuh``) along with other sources. Such files will be 2025-07-17T07:36:53.2142860Z detected and compiled with nvcc rather than the C++ compiler. This includes 2025-07-17T07:36:53.2143436Z passing the CUDA lib64 directory as a library directory, and linking 2025-07-17T07:36:53.2143921Z ``cudart``. You can pass additional flags to nvcc via 2025-07-17T07:36:53.2144379Z ``extra_cuda_cflags``, just like with ``extra_cflags`` for C++. Various 2025-07-17T07:36:53.2144937Z heuristics for finding the CUDA install directory are used, which usually 2025-07-17T07:36:53.2145504Z work fine. If not, setting the ``CUDA_HOME`` environment variable is the 2025-07-17T07:36:53.2145909Z safest option. 2025-07-17T07:36:53.2146134Z 2025-07-17T07:36:53.2146540Z SYCL support with mixed compilation is provided. Simply pass SYCL source 2025-07-17T07:36:53.2147091Z files (``.sycl``) along with other sources. Such files will be detected 2025-07-17T07:36:53.2147633Z and compiled with SYCL compiler (such as Intel DPC++ Compiler) rather 2025-07-17T07:36:53.2148183Z than the C++ compiler. You can pass additional flags to SYCL compiler 2025-07-17T07:36:53.2148705Z via ``extra_sycl_cflags``, just like with ``extra_cflags`` for C++. 2025-07-17T07:36:53.2149260Z SYCL compiler is expected to be found via system PATH environment 2025-07-17T07:36:53.2149674Z variable. 2025-07-17T07:36:53.2149883Z 2025-07-17T07:36:53.2150063Z Args: 2025-07-17T07:36:53.2150387Z name: The name of the extension to build. This MUST be the same as the 2025-07-17T07:36:53.2150826Z name of the pybind11 module! 2025-07-17T07:36:53.2151227Z sources: A list of relative or absolute paths to C++ source files. 2025-07-17T07:36:53.2151773Z extra_cflags: optional list of compiler flags to forward to the build. 2025-07-17T07:36:53.2152426Z extra_cuda_cflags: optional list of compiler flags to forward to nvcc 2025-07-17T07:36:53.2152873Z when building CUDA sources. 2025-07-17T07:36:53.2153294Z extra_sycl_cflags: optional list of compiler flags to forward to SYCL 2025-07-17T07:36:53.2153751Z compiler when building SYCL sources. 2025-07-17T07:36:53.2154199Z extra_ldflags: optional list of linker flags to forward to the build. 2025-07-17T07:36:53.2154758Z extra_include_paths: optional list of include directories to forward 2025-07-17T07:36:53.2155180Z to the build. 2025-07-17T07:36:53.2155518Z build_directory: optional path to use as build workspace. 2025-07-17T07:36:53.2155992Z verbose: If ``True``, turns on verbose logging of load steps. 2025-07-17T07:36:53.2156498Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-07-17T07:36:53.2156997Z the build. If set to ``None`` (default), this value is 2025-07-17T07:36:53.2157473Z automatically determined based on the existence of ``.cu`` or 2025-07-17T07:36:53.2157953Z ``.cuh`` in ``sources``. Set it to `True`` to force CUDA headers 2025-07-17T07:36:53.2158350Z and libraries to be included. 2025-07-17T07:36:53.2158790Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-07-17T07:36:53.2159286Z the build. If set to ``None`` (default), this value is 2025-07-17T07:36:53.2159789Z automatically determined based on the existence of ``.sycl`` in 2025-07-17T07:36:53.2160311Z ``sources``. Set it to `True`` to force SYCL headers and 2025-07-17T07:36:53.2160690Z libraries to be included. 2025-07-17T07:36:53.2161087Z is_python_module: If ``True`` (default), imports the produced shared 2025-07-17T07:36:53.2161598Z library as a Python module. If ``False``, behavior depends on 2025-07-17T07:36:53.2162000Z ``is_standalone``. 2025-07-17T07:36:53.2162385Z is_standalone: If ``False`` (default) loads the constructed extension 2025-07-17T07:36:53.2162891Z into the process as a plain dynamic library. If ``True``, build a 2025-07-17T07:36:53.2163334Z standalone executable. 2025-07-17T07:36:53.2163608Z 2025-07-17T07:36:53.2163790Z Returns: 2025-07-17T07:36:53.2164028Z If ``is_python_module`` is ``True``: 2025-07-17T07:36:53.2164423Z Returns the loaded PyTorch extension as a Python module. 2025-07-17T07:36:53.2164781Z 2025-07-17T07:36:53.2165089Z If ``is_python_module`` is ``False`` and ``is_standalone`` is ``False``: 2025-07-17T07:36:53.2165700Z Returns nothing. (The shared library is loaded into the process as 2025-07-17T07:36:53.2166123Z a side effect.) 2025-07-17T07:36:53.2166362Z 2025-07-17T07:36:53.2166579Z If ``is_standalone`` is ``True``. 2025-07-17T07:36:53.2167054Z Return the path to the executable. (On Windows, TORCH_LIB_PATH is 2025-07-17T07:36:53.2167536Z added to the PATH environment variable as a side effect.) 2025-07-17T07:36:53.2167903Z 2025-07-17T07:36:53.2168101Z Example: 2025-07-17T07:36:53.2168314Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.2168635Z >>> from torch.utils.cpp_extension import load 2025-07-17T07:36:53.2168977Z >>> module = load( 2025-07-17T07:36:53.2169230Z ... name='extension', 2025-07-17T07:36:53.2169575Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-07-17T07:36:53.2170098Z ... extra_cflags=['-O2'], 2025-07-17T07:36:53.2170400Z ... verbose=True) 2025-07-17T07:36:53.2170644Z 2025-07-17T07:36:53.2171006Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.2171453Z 2025-07-17T07:36:53.2171645Z warnings.warn(msg) 2025-07-17T07:36:53.2171890Z 2025-07-17T07:36:53.2172217Z --- Parse Warning: 134 / 136 --- 2025-07-17T07:36:53.2173360Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_inline in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1890. 2025-07-17T07:36:53.2174657Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.2175118Z 2025-07-17T07:36:53.2175436Z Load a PyTorch C++ extension just-in-time (JIT) from string sources. 2025-07-17T07:36:53.2175831Z 2025-07-17T07:36:53.2176179Z This function behaves exactly like :func:`load`, but takes its sources as 2025-07-17T07:36:53.2176758Z strings rather than filenames. These strings are stored to files in the 2025-07-17T07:36:53.2177305Z build directory, after which the behavior of :func:`load_inline` is 2025-07-17T07:36:53.2177731Z identical to :func:`load`. 2025-07-17T07:36:53.2177991Z 2025-07-17T07:36:53.2178177Z See `the 2025-07-17T07:36:53.2178637Z tests `_ 2025-07-17T07:36:53.2179204Z for good examples of using this function. 2025-07-17T07:36:53.2179503Z 2025-07-17T07:36:53.2179845Z Sources may omit two required parts of a typical non-inline C++ extension: 2025-07-17T07:36:53.2180441Z the necessary header includes, as well as the (pybind11) binding code. More 2025-07-17T07:36:53.2181044Z precisely, strings passed to ``cpp_sources`` are first concatenated into a 2025-07-17T07:36:53.2181578Z single ``.cpp`` file. This file is then prepended with ``#include 2025-07-17T07:36:53.2182067Z `` 2025-07-17T07:36:53.2182322Z 2025-07-17T07:36:53.2182651Z Furthermore, if the ``functions`` argument is supplied, bindings will be 2025-07-17T07:36:53.2183236Z automatically generated for each function specified. ``functions`` can 2025-07-17T07:36:53.2183825Z either be a list of function names, or a dictionary mapping from function 2025-07-17T07:36:53.2184393Z names to docstrings. If a list is given, the name of each function is used 2025-07-17T07:36:53.2184821Z as its docstring. 2025-07-17T07:36:53.2185063Z 2025-07-17T07:36:53.2185393Z The sources in ``cuda_sources`` are concatenated into a separate ``.cu`` 2025-07-17T07:36:53.2185945Z file and prepended with ``torch/types.h``, ``cuda.h`` and 2025-07-17T07:36:53.2186453Z ``cuda_runtime.h`` includes. The ``.cpp`` and ``.cu`` files are compiled 2025-07-17T07:36:53.2187010Z separately, but ultimately linked into a single library. Note that no 2025-07-17T07:36:53.2187576Z bindings are generated for functions in ``cuda_sources`` per se. To bind 2025-07-17T07:36:53.2188145Z to a CUDA kernel, you must create a C++ function that calls it, and either 2025-07-17T07:36:53.2188701Z declare or define this C++ function in one of the ``cpp_sources`` (and 2025-07-17T07:36:53.2189217Z include its name in ``functions``). 2025-07-17T07:36:53.2189506Z 2025-07-17T07:36:53.2189840Z The sources in ``sycl_sources`` are concatenated into a separate ``.sycl`` 2025-07-17T07:36:53.2190397Z file and prepended with ``torch/types.h``, ``sycl/sycl.hpp`` includes. 2025-07-17T07:36:53.2190921Z The ``.cpp`` and ``.sycl`` files are compiled separately, but ultimately 2025-07-17T07:36:53.2191455Z linked into a single library. Note that no bindings are generated for 2025-07-17T07:36:53.2192002Z functions in ``sycl_sources`` per se. To bind to a SYCL kernel, you must 2025-07-17T07:36:53.2192548Z create a C++ function that calls it, and either declare or define this 2025-07-17T07:36:53.2193055Z C++ function in one of the ``cpp_sources`` (and include its name 2025-07-17T07:36:53.2193453Z in ``functions``). 2025-07-17T07:36:53.2193688Z 2025-07-17T07:36:53.2193864Z 2025-07-17T07:36:53.2194048Z 2025-07-17T07:36:53.2194346Z See :func:`load` for a description of arguments omitted below. 2025-07-17T07:36:53.2194710Z 2025-07-17T07:36:53.2194904Z Args: 2025-07-17T07:36:53.2195238Z cpp_sources: A string, or list of strings, containing C++ source code. 2025-07-17T07:36:53.2195784Z cuda_sources: A string, or list of strings, containing CUDA source code. 2025-07-17T07:36:53.2196349Z sycl_sources: A string, or list of strings, containing SYCL source code. 2025-07-17T07:36:53.2196892Z functions: A list of function names for which to generate function 2025-07-17T07:36:53.2197428Z bindings. If a dictionary is given, it should map function names to 2025-07-17T07:36:53.2197937Z docstrings (which are otherwise just the function names). 2025-07-17T07:36:53.2198510Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-07-17T07:36:53.2199018Z the build. If set to ``None`` (default), this value is 2025-07-17T07:36:53.2199489Z automatically determined based on whether ``cuda_sources`` is 2025-07-17T07:36:53.2199966Z provided. Set it to ``True`` to force CUDA headers 2025-07-17T07:36:53.2200347Z and libraries to be included. 2025-07-17T07:36:53.2200788Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-07-17T07:36:53.2201279Z the build. If set to ``None`` (default), this value is 2025-07-17T07:36:53.2201755Z automatically determined based on whether ``sycl_sources`` is 2025-07-17T07:36:53.2202230Z provided. Set it to ``True`` to force SYCL headers 2025-07-17T07:36:53.2202598Z and libraries to be included. 2025-07-17T07:36:53.2203066Z with_pytorch_error_handling: Determines whether pytorch error and 2025-07-17T07:36:53.2203593Z warning macros are handled by pytorch instead of pybind. To do 2025-07-17T07:36:53.2204127Z this, each function ``foo`` is called via an intermediary ``_safe_foo`` 2025-07-17T07:36:53.2204665Z function. This redirection might cause issues in obscure cases 2025-07-17T07:36:53.2205174Z of cpp. This flag should be set to ``False`` when this redirect 2025-07-17T07:36:53.2205663Z causes issues. 2025-07-17T07:36:53.2206076Z no_implicit_headers: If ``True``, skips automatically adding headers, most notably 2025-07-17T07:36:53.2206712Z ``#include `` and ``#include `` lines. 2025-07-17T07:36:53.2207217Z Use this option to improve cold start times when you 2025-07-17T07:36:53.2207749Z already include the necessary headers in your source code. Default: ``False``. 2025-07-17T07:36:53.2208198Z 2025-07-17T07:36:53.2208393Z Example: 2025-07-17T07:36:53.2208672Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-07-17T07:36:53.2209085Z >>> from torch.utils.cpp_extension import load_inline 2025-07-17T07:36:53.2209451Z >>> source = """ 2025-07-17T07:36:53.2209864Z at::Tensor sin_add(at::Tensor x, at::Tensor y) { 2025-07-17T07:36:53.2210207Z return x.sin() + y.sin(); 2025-07-17T07:36:53.2210487Z } 2025-07-17T07:36:53.2210690Z """ 2025-07-17T07:36:53.2210952Z >>> module = load_inline(name='inline_extension', 2025-07-17T07:36:53.2211309Z ... cpp_sources=[source], 2025-07-17T07:36:53.2211657Z ... functions=['sin_add']) 2025-07-17T07:36:53.2211967Z 2025-07-17T07:36:53.2212152Z .. note:: 2025-07-17T07:36:53.2212518Z Since load_inline will just-in-time compile the source code, please ensure 2025-07-17T07:36:53.2213106Z that you have the right toolchains installed in the runtime. For example, 2025-07-17T07:36:53.2213662Z when loading C++, make sure a C++ compiler is available. If you're loading 2025-07-17T07:36:53.2214245Z a CUDA extension, you will need to additionally install the corresponding CUDA 2025-07-17T07:36:53.2214862Z toolkit (nvcc and any other dependencies your code has). Compiling toolchains 2025-07-17T07:36:53.2215472Z are not included when you install torch and must be additionally installed. 2025-07-17T07:36:53.2215898Z 2025-07-17T07:36:53.2216260Z During compiling, by default, the Ninja backend uses #CPUS + 2 workers to build 2025-07-17T07:36:53.2216855Z the extension. This may use up too many resources on some systems. One 2025-07-17T07:36:53.2217400Z can control the number of workers by setting the `MAX_JOBS` environment 2025-07-17T07:36:53.2217854Z variable to a non-negative number. 2025-07-17T07:36:53.2218153Z 2025-07-17T07:36:53.2218521Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.2218964Z 2025-07-17T07:36:53.2219172Z warnings.warn(msg) 2025-07-17T07:36:53.2219419Z 2025-07-17T07:36:53.2219732Z --- Parse Warning: 135 / 136 --- 2025-07-17T07:36:53.2220971Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ThroughputBenchmark in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/throughput_benchmark.py line=61. 2025-07-17T07:36:53.2222339Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.2222793Z 2025-07-17T07:36:53.2223199Z This class is a wrapper around a c++ component throughput_benchmark::ThroughputBenchmark. 2025-07-17T07:36:53.2223690Z 2025-07-17T07:36:53.2224153Z This wrapper on the throughput_benchmark::ThroughputBenchmark component is responsible 2025-07-17T07:36:53.2224813Z for executing a PyTorch module (nn.Module or ScriptModule) under an inference 2025-07-17T07:36:53.2225460Z server like load. It can emulate multiple calling threads to a single module 2025-07-17T07:36:53.2226055Z provided. In the future we plan to enhance this component to support inter and 2025-07-17T07:36:53.2226671Z intra-op parallelism as well as multiple models running in a single process. 2025-07-17T07:36:53.2227109Z 2025-07-17T07:36:53.2227477Z Please note that even though nn.Module is supported, it might incur an overhead 2025-07-17T07:36:53.2228079Z from the need to hold GIL every time we execute Python code or pass around 2025-07-17T07:36:53.2228682Z inputs as Python objects. As soon as you have a ScriptModule version of your 2025-07-17T07:36:53.2229284Z model for inference deployment it is better to switch to using it in this 2025-07-17T07:36:53.2229734Z benchmark. 2025-07-17T07:36:53.2229939Z 2025-07-17T07:36:53.2230144Z Example:: 2025-07-17T07:36:53.2230355Z 2025-07-17T07:36:53.2230580Z >>> # xdoctest: +SKIP("undefined vars") 2025-07-17T07:36:53.2230959Z >>> from torch.utils import ThroughputBenchmark 2025-07-17T07:36:53.2231349Z >>> bench = ThroughputBenchmark(my_module) 2025-07-17T07:36:53.2231755Z >>> # Pre-populate benchmark's data set with the inputs 2025-07-17T07:36:53.2232176Z >>> for input in inputs: 2025-07-17T07:36:53.2232593Z ... # Both args and kwargs work, same as any PyTorch Module / ScriptModule 2025-07-17T07:36:53.2233059Z ... bench.add_input(input[0], x2=input[1]) 2025-07-17T07:36:53.2233496Z >>> # Inputs supplied above are randomly used during the execution 2025-07-17T07:36:53.2233920Z >>> stats = bench.benchmark( 2025-07-17T07:36:53.2234236Z ... num_calling_threads=4, 2025-07-17T07:36:53.2234536Z ... num_warmup_iters = 100, 2025-07-17T07:36:53.2234841Z ... num_iters = 1000, 2025-07-17T07:36:53.2235115Z ... ) 2025-07-17T07:36:53.2235421Z >>> print("Avg latency (ms): {}".format(stats.latency_avg_ms)) 2025-07-17T07:36:53.2235877Z >>> print("Number of iterations: {}".format(stats.num_iters)) 2025-07-17T07:36:53.2236249Z 2025-07-17T07:36:53.2236613Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.2237048Z 2025-07-17T07:36:53.2237255Z warnings.warn(msg) 2025-07-17T07:36:53.2237502Z 2025-07-17T07:36:53.2237799Z --- Parse Warning: 136 / 136 --- 2025-07-17T07:36:53.2239006Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/distributed.py line=18. 2025-07-17T07:36:53.2240347Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-07-17T07:36:53.2240935Z Sampler that restricts data loading to a subset of the dataset. 2025-07-17T07:36:53.2241320Z 2025-07-17T07:36:53.2241570Z It is especially useful in conjunction with 2025-07-17T07:36:53.2242067Z :class:`torch.nn.parallel.DistributedDataParallel`. In such a case, each 2025-07-17T07:36:53.2242323Z process can pass a :class:`~torch.utils.data.DistributedSampler` instance as a 2025-07-17T07:36:53.2242551Z :class:`~torch.utils.data.DataLoader` sampler, and load a subset of the 2025-07-17T07:36:53.2242688Z original dataset that is exclusive to it. 2025-07-17T07:36:53.2242764Z 2025-07-17T07:36:53.2242862Z .. note:: 2025-07-17T07:36:53.2243092Z Dataset is assumed to be of constant size and that any instance of it always 2025-07-17T07:36:53.2243230Z returns the same elements in the same order. 2025-07-17T07:36:53.2243318Z 2025-07-17T07:36:53.2243397Z Args: 2025-07-17T07:36:53.2243512Z dataset: Dataset used for sampling. 2025-07-17T07:36:53.2243736Z num_replicas (int, optional): Number of processes participating in 2025-07-17T07:36:53.2244023Z distributed training. By default, :attr:`world_size` is retrieved from the 2025-07-17T07:36:53.2244136Z current distributed group. 2025-07-17T07:36:53.2244384Z rank (int, optional): Rank of the current process within :attr:`num_replicas`. 2025-07-17T07:36:53.2244586Z By default, :attr:`rank` is retrieved from the current distributed 2025-07-17T07:36:53.2244683Z group. 2025-07-17T07:36:53.2244903Z shuffle (bool, optional): If ``True`` (default), sampler will shuffle the 2025-07-17T07:36:53.2244990Z indices. 2025-07-17T07:36:53.2245219Z seed (int, optional): random seed used to shuffle the sampler if 2025-07-17T07:36:53.2245495Z :attr:`shuffle=True`. This number should be identical across all 2025-07-17T07:36:53.2245663Z processes in the distributed group. Default: ``0``. 2025-07-17T07:36:53.2245930Z drop_last (bool, optional): if ``True``, then the sampler will drop the 2025-07-17T07:36:53.2246125Z tail of the data to make it evenly divisible across the number of 2025-07-17T07:36:53.2246334Z replicas. If ``False``, the sampler will add extra indices to make 2025-07-17T07:36:53.2246596Z the data evenly divisible across the replicas. Default: ``False``. 2025-07-17T07:36:53.2246674Z 2025-07-17T07:36:53.2246774Z .. warning:: 2025-07-17T07:36:53.2246959Z In distributed mode, calling the :meth:`set_epoch` method at 2025-07-17T07:36:53.2247206Z the beginning of each epoch **before** creating the :class:`DataLoader` iterator 2025-07-17T07:36:53.2247475Z is necessary to make shuffling work properly across multiple epochs. Otherwise, 2025-07-17T07:36:53.2247593Z the same ordering will be always used. 2025-07-17T07:36:53.2247682Z 2025-07-17T07:36:53.2247767Z Example:: 2025-07-17T07:36:53.2247845Z 2025-07-17T07:36:53.2247955Z >>> # xdoctest: +SKIP 2025-07-17T07:36:53.2248171Z >>> sampler = DistributedSampler(dataset) if is_distributed else None 2025-07-17T07:36:53.2248340Z >>> loader = DataLoader(dataset, shuffle=(sampler is None), 2025-07-17T07:36:53.2248471Z ... sampler=sampler) 2025-07-17T07:36:53.2248603Z >>> for epoch in range(start_epoch, n_epochs): 2025-07-17T07:36:53.2248702Z ... if is_distributed: 2025-07-17T07:36:53.2248825Z ... sampler.set_epoch(epoch) 2025-07-17T07:36:53.2248921Z ... train(loader) 2025-07-17T07:36:53.2249016Z 2025-07-17T07:36:53.2249265Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-07-17T07:36:53.2249342Z 2025-07-17T07:36:53.2249447Z warnings.warn(msg) 2025-07-17T07:36:53.2249522Z 2025-07-17T07:36:53.2249640Z  2025-07-17T07:36:53.2249820Z === Found 9 run-time warnings === 2025-07-17T07:36:53.2249992Z --- Runtime Warning: 1 / 9 --- 2025-07-17T07:36:53.2250252Z example = 2025-07-17T07:36:53.2251626Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py:1351: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /var/lib/jenkins/workspace/c10/core/TensorImpl.h:1978.) 2025-07-17T07:36:53.2251736Z return super().refine_names(names) 2025-07-17T07:36:53.2251828Z 2025-07-17T07:36:53.2251998Z --- Runtime Warning: 2 / 9 --- 2025-07-17T07:36:53.2252305Z example = 2025-07-17T07:36:53.2252948Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py:281: UserWarning: Warning only once for all operators, other operators may also be overridden. 2025-07-17T07:36:53.2253299Z Overriding a previously registered kernel for the same operator and the same dispatch key 2025-07-17T07:36:53.2253508Z operator: aten::div.Tensor(Tensor self, Tensor other) -> Tensor 2025-07-17T07:36:53.2253804Z registered at /var/lib/jenkins/workspace/build/aten/src/ATen/RegisterSchema.cpp:6 2025-07-17T07:36:53.2253896Z dispatch key: CPU 2025-07-17T07:36:53.2254334Z previous kernel: registered at /var/lib/jenkins/workspace/aten/src/ATen/LegacyBatchingRegistrations.cpp:1079 2025-07-17T07:36:53.2254888Z new kernel: registered at /dev/null:811 (Triggered internally at /var/lib/jenkins/workspace/aten/src/ATen/core/dispatch/OperatorEntry.cpp:225.) 2025-07-17T07:36:53.2255084Z impl_fn(self.ns, name.split("::")[-1], dispatch_key) 2025-07-17T07:36:53.2255160Z 2025-07-17T07:36:53.2255331Z --- Runtime Warning: 3 / 9 --- 2025-07-17T07:36:53.2255579Z example = 2025-07-17T07:36:53.2257486Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py:117: UserWarning: The PyTorch API of nested tensors is in prototype stage and will change in the near future. We recommend specifying layout=torch.jagged when constructing a nested tensor, as this layout receives active development, has better operator coverage, and works with torch.compile. (Triggered internally at /var/lib/jenkins/workspace/aten/src/ATen/NestedTensorImpl.cpp:182.) 2025-07-17T07:36:53.2257740Z return torch._nested_tensor_from_tensor_list(ts, dtype, None, device, None) 2025-07-17T07:36:53.2257818Z 2025-07-17T07:36:53.2257989Z --- Runtime Warning: 4 / 9 --- 2025-07-17T07:36:53.2258251Z example = 2025-07-17T07:36:53.2259878Z :1: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /var/lib/jenkins/workspace/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) 2025-07-17T07:36:53.2259971Z 2025-07-17T07:36:53.2260142Z --- Runtime Warning: 5 / 9 --- 2025-07-17T07:36:53.2260446Z example = 2025-07-17T07:36:53.2261978Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/const_fold.py:271: UserWarning: Attempted to insert a get_attr Node with no underlying reference in the owning GraphModule! Call GraphModule.add_submodule to add the necessary submodule, GraphModule.add_parameter to add the necessary Parameter, or nn.Module.register_buffer to add the necessary buffer 2025-07-17T07:36:53.2262141Z new_node = root_const_gm.graph.get_attr(in_node.target) 2025-07-17T07:36:53.2262231Z 2025-07-17T07:36:53.2262402Z --- Runtime Warning: 6 / 9 --- 2025-07-17T07:36:53.2262688Z example = 2025-07-17T07:36:53.2263797Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py:392: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance) 2025-07-17T07:36:53.2263887Z warnings.warn( 2025-07-17T07:36:53.2263975Z 2025-07-17T07:36:53.2264149Z --- Runtime Warning: 7 / 9 --- 2025-07-17T07:36:53.2264481Z example = 2025-07-17T07:36:53.2265593Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py:392: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance) 2025-07-17T07:36:53.2265713Z warnings.warn( 2025-07-17T07:36:53.2265803Z 2025-07-17T07:36:53.2265975Z --- Runtime Warning: 8 / 9 --- 2025-07-17T07:36:53.2266250Z example = 2025-07-17T07:36:53.2267080Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`. 2025-07-17T07:36:53.2267228Z WeightNorm.apply(module, name, dim) 2025-07-17T07:36:53.2267306Z 2025-07-17T07:36:53.2267489Z --- Runtime Warning: 9 / 9 --- 2025-07-17T07:36:53.2267791Z example = 2025-07-17T07:36:53.2268609Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`. 2025-07-17T07:36:53.2268727Z WeightNorm.apply(module, name, dim) 2025-07-17T07:36:53.2268803Z 2025-07-17T07:36:53.2269161Z === 342 passed, 377 skipped, 145 warnings in 13.85 seconds === 2025-07-17T07:36:53.2269378Z Running test_namedtuple_return_api 1/1 ... [2025-07-17 07:36:53.025454] 2025-07-17T07:36:53.2269486Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T07:36:53.2270527Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_namedtuple_return_api.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:36:53.025861] 2025-07-17T07:36:59.4523358Z 2025-07-17T07:36:59.4524422Z test_namedtuple_return_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_namedtuple_return_api_1.1_d6ee1c20b3701728_.log 2025-07-17T07:36:59.4526512Z Running 3 items in this shard: test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_import_return_types, test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_namedtuple_return, test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_native_functions_yaml 2025-07-17T07:36:59.4528032Z 2025-07-17T07:36:59.4528772Z Running test_nn 1/4 ... [2025-07-17 07:36:59.452721] 2025-07-17T07:36:59.4529148Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T07:36:59.4533027Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_nn.py', '--shard-id=1', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:36:59.453082] 2025-07-17T07:45:29.6600670Z 2025-07-17T07:45:29.6601796Z test_nn 1/4 was successful, full logs can be found in artifacts with path test/test-reports/test_nn_1.4_c4d1772a17b581f5_.log 2025-07-17T07:45:29.6906615Z Running 531 items in this shard: test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_BCELoss_no_reduce_cuda, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_CELU_no_batch_dim, test/test_nn.py::TestNN::test_CTCLoss_zero_lengths, test/test_nn.py::TestNN::test_Conv1d_dilated_cuda, test/test_nn.py::TestNN::test_Conv1d_pad1_cuda, test/test_nn.py::TestNN::test_Conv1d_pad1size1_cuda, test/test_nn.py::TestNN::test_Conv1d_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_same_dilated_cuda, test/test_nn.py::TestNN::test_Conv1d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_stride, test/test_nn.py::TestNN::test_Conv2d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_dilated, test/test_nn.py::TestNN::test_Conv2d_depthwise_padded_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_with_multiplier_cuda, test/test_nn.py::TestNN::test_Conv2d_dilated, test/test_nn.py::TestNN::test_Conv2d_dilated_cuda, test/test_nn.py::TestNN::test_Conv2d_groups, test/test_nn.py::TestNN::test_Conv2d_groups_thnn, test/test_nn.py::TestNN::test_Conv2d_groups_thnn_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_no_bias, test/test_nn.py::TestNN::test_Conv2d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv2d_reflect_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_zero_batch_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias_cuda, test/test_nn.py::TestNN::test_Conv3d_circular_stride2_pad2, test/test_nn.py::TestNN::test_Conv3d_dilated_strided_cuda, test/test_nn.py::TestNN::test_Conv3d_groups_cuda, test/test_nn.py::TestNN::test_Conv3d_groups_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_no_bias_cuda, test/test_nn.py::TestNN::test_Conv3d_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_pad_same, test/test_nn.py::TestNN::test_Conv3d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d_stride, test/test_nn.py::TestNN::test_Conv3d_stride_padding, test/test_nn.py::TestNN::test_Conv3d_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_zero_batch_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d, test/test_nn.py::TestNN::test_ConvTranspose1d_dilated, test/test_nn.py::TestNN::test_ConvTranspose1d_dilated_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d_no_bias, test/test_nn.py::TestNN::test_ConvTranspose1d_no_bias_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_groups, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose3d_cuda, test/test_nn.py::TestNN::test_ConvTranspose3d_dilated, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_CrossMapLRN2d, test/test_nn.py::TestNN::test_EmbeddingBag_discontiguous_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_mean, test/test_nn.py::TestNN::test_EmbeddingBag_mean_padding_idx, test/test_nn.py::TestNN::test_EmbeddingBag_sparse, test/test_nn.py::TestNN::test_EmbeddingBag_sum, test/test_nn.py::TestNN::test_Embedding_discontiguous, test/test_nn.py::TestNN::test_Embedding_discontiguous_cuda, test/test_nn.py::TestNN::test_Embedding_sparse, test/test_nn.py::TestNN::test_Fold_no_batch_dim_int_input, test/test_nn.py::TestNN::test_Fold_no_batch_dim_int_input_cuda, test/test_nn.py::TestNN::test_GELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardswish_no_batch_dim, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_batch_mean_log_target, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar_log_target, test/test_nn.py::TestNN::test_KLDivLoss_with_log_target_no_reduce, test/test_nn.py::TestNN::test_KLDivLoss_with_target_no_reduce, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum, test/test_nn.py::TestNN::test_L1Loss_no_reduce, test/test_nn.py::TestNN::test_L1Loss_no_reduce_scalar, test/test_nn.py::TestNN::test_LSTM_cell, test/test_nn.py::TestNN::test_LSTM_cell_forward_input_size, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature_cuda, test/test_nn.py::TestNN::test_LeakyReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MSELoss_no_reduce, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MaxUnpool1d_net_cuda, test/test_nn.py::TestNN::test_MaxUnpool3d_net_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ModuleList, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_1d_no_reduce, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_index_neg_cuda, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_reduce, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_reduce, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_margin_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_weights, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_ignore_index, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index, test/test_nn.py::TestNN::test_PReLU_no_batch_dim, test/test_nn.py::TestNN::test_PReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_PairwiseDistance, test/test_nn.py::TestNN::test_ParameterDict, test/test_nn.py::TestNN::test_ParameterList_meta, test/test_nn.py::TestNN::test_PixelUnshuffle, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_reduce, test/test_nn.py::TestNN::test_RNN_cell_forward_zero_hidden_size, test/test_nn.py::TestNN::test_RReLU_no_batch_dim, test/test_nn.py::TestNN::test_RReLU_with_up_down_cuda, test/test_nn.py::TestNN::test_RReLU_with_up_down_scalar, test/test_nn.py::TestNN::test_ReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d_complex_cuda, test/test_nn.py::TestNN::test_Sequential_rmul, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_SmoothL1Loss_zero_beta_cuda, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_SoftMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_Softshrink_no_batch_dim, test/test_nn.py::TestNN::test_Softsign_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Tanhshrink_no_batch_dim_cuda, test/test_nn.py::TestNN::test_TransformerDecoderLayer_relu_activation_cuda, test/test_nn.py::TestNN::test_TransformerEncoderLayer_gelu_activation, test/test_nn.py::TestNN::test_Transformer_multilayer_coder, test/test_nn.py::TestNN::test_Transformer_multilayer_coder_cuda, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_Unfold, test/test_nn.py::TestNN::test_batch_norm_update_stats, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_cudnn_nhwc, test/test_nn.py::TestNN::test_batchnorm_load_state_dict, test/test_nn.py::TestNN::test_batchnorm_nhwc_cpu, test/test_nn.py::TestNN::test_batchnorm_nonaffine_cuda_half_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_bias_is_not_same_size_as_input, test/test_nn.py::TestNN::test_bce_with_logits_broadcasts_weights, test/test_nn.py::TestNN::test_bce_with_logits_has_correct_forward_grad, test/test_nn.py::TestNN::test_buffer_bad_module_subclass, test/test_nn.py::TestNN::test_buffer_not_persistent_load, test/test_nn.py::TestNN::test_buffers_and_named_buffers, test/test_nn.py::TestNN::test_cosine_embedding_loss_margin_no_reduce, test/test_nn.py::TestNN::test_cudnn_rnn_dropout_states_device, test/test_nn.py::TestNN::test_fb_fc_packed, test/test_nn.py::TestNN::test_grid_sample_error_checking, test/test_nn.py::TestNN::test_hardtanh_backward, test/test_nn.py::TestNN::test_hardtanh_inplace_gradgrad, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_linear_1d_align_corners, test/test_nn.py::TestNN::test_interpolate_linear_1d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d_align_corners, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_1d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_2d_launch_configs_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_scale_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_scale_2d, test/test_nn.py::TestNN::test_interpolate_nearest_scale_2d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_scale_3d, test/test_nn.py::TestNN::test_interpolate_nearest_scale_3d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_3d_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_3d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_align_corners_cuda, test/test_nn.py::TestNN::test_l1_loss_correct, test/test_nn.py::TestNN::test_layer_norm_grads_with_create_graph_flag, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightStrided, test/test_nn.py::TestNN::test_log_softmax_spatial_special_cuda, test/test_nn.py::TestNN::test_margin_ranking_loss_no_reduce, test/test_nn.py::TestNN::test_module_backcompat, test/test_nn.py::TestNN::test_named_parameters_remove_duplicate, test/test_nn.py::TestNN::test_nested_tensor_from_mask, test/test_nn.py::TestNN::test_parameterlistdict_setting_attributes, test/test_nn.py::TestNN::test_pdist_empty_col, test/test_nn.py::TestNN::test_pixel_shuffle_unshuffle, test/test_nn.py::TestNN::test_projections_errors_on_gru_and_rnn, test/test_nn.py::TestNN::test_projections_lstm_args_check, test/test_nn.py::TestNN::test_register_parameter_raises_error_if_name_is_not_string, test/test_nn.py::TestNN::test_relu_inplace_on_view, test/test_nn.py::TestNN::test_rnn_check_device, test/test_nn.py::TestNN::test_rnn_weight_norm, test/test_nn.py::TestNN::test_softmax_functional_dim0, test/test_nn.py::TestNN::test_softmax_functional_dim3, test/test_nn.py::TestNN::test_softmax_lastdim, test/test_nn.py::TestNN::test_softmax_lastdim_dtype, test/test_nn.py::TestNN::test_softmax_spatial_dtype_cuda, test/test_nn.py::TestNN::test_spectral_norm_load_state_dict, test/test_nn.py::TestNN::test_spectral_norm_pickle, test/test_nn.py::TestNN::test_swap_module_params_poisons_acc_grad, test/test_nn.py::TestNN::test_transformer_args_check, test/test_nn.py::TestNN::test_transformerdecoderlayer_gelu, test/test_nn.py::TestNN::test_triplet_margin_loss_no_reduce, test/test_nn.py::TestNN::test_triplet_margin_loss_swap, test/test_nn.py::TestNN::test_unflatten, test/test_nn.py::TestNN::test_upsamplingBilinear2d_spatial_invariance, test/test_nn.py::TestNN::test_upsampling_not_recompute_scale_factor, test/test_nn.py::TestNN::test_weighted_huber_loss, test/test_nn.py::TestNN::test_weighted_l1_loss_with_weights, test/test_nn.py::TestFusionEval::test_fuse_module_eval_numerics, test/test_nn.py::TestConstantPadNd::test_constant_pad_nd, test/test_nn.py::TestAddRelu::test_add_relu, test/test_nn.py::TestFunctionalPickle::test_pickle_softsign, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_mean_use_module_form_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_none_use_module_form_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_sum_use_module_form_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_memory_format_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_numeric_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm2d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_LSTM_grad_and_gradgrad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad2d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerEncoder_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_activations_bfloat16_half_cpu_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_3d_rotateRandom_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_mixed_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_simple_average_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_1_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_inf_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_0_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_multi_device_foreach_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_value_foreach_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_64bit_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_errors_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_weight_ignore_indices_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_large_tensor_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_large_tensor_reduction_sum_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_mean_weighted_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_none_weighted_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_elu_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_elu_inplace_with_neg_alpha_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_glu_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_gumbel_softmax_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_gumbel_softmax_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_False_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_False_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_True_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_less_than_one_value_per_channel_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_with_neg_slope_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_with_zero_slope_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_module_to_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_byte_target_matches_long_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_large_tensor_reduction_mean_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_out_of_bounds_ignore_index_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_total_weight_is_zero_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nonlinearity_propagate_nan_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_overwrite_module_params_on_conversion_cpu_device_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_prelu_backward_32bit_indexing_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_numeric_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_skip_init_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_double_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_results_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_threshold_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_transformerencoderlayer_fast_path_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_triplet_margin_with_distance_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_triplet_margin_with_distance_loss_default_parity_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_False_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_True_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_launch_fail_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_launch_rocm_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsampling_64bit_indexing_channels_last_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingnearest2d_backward_64bit_indexing_cpu_float16 2025-07-17T07:45:29.7193150Z 2025-07-17T07:45:29.7193348Z Running test_nn 3/4 ... [2025-07-17 07:45:29.662220] 2025-07-17T07:45:29.7193720Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T07:45:29.7194739Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_nn.py', '--shard-id=3', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:45:29.662645] 2025-07-17T07:55:45.0897370Z 2025-07-17T07:55:45.0898233Z test_nn 3/4 was successful, full logs can be found in artifacts with path test/test-reports/test_nn_3.4_0e850cd9350818b8_.log 2025-07-17T07:55:45.1181496Z Running 541 items in this shard: test/test_nn.py::TestNN::test_AdaptiveLogSoftmax, test/test_nn.py::TestNN::test_AdaptiveLogSoftmax_cuda, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_legacy_enum_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_CELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Conv1d, test/test_nn.py::TestNN::test_Conv1d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_dilated, test/test_nn.py::TestNN::test_Conv1d_groups_cuda, test/test_nn.py::TestNN::test_Conv1d_pad1, test/test_nn.py::TestNN::test_Conv1d_pad_same2, test/test_nn.py::TestNN::test_Conv1d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_same_dilated, test/test_nn.py::TestNN::test_Conv1d_pad_valid_cuda, test/test_nn.py::TestNN::test_Conv1d_zero_batch_cuda, test/test_nn.py::TestNN::test_Conv1d_zeros_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise, test/test_nn.py::TestNN::test_Conv2d_depthwise_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_strided, test/test_nn.py::TestNN::test_Conv2d_depthwise_strided_cuda, test/test_nn.py::TestNN::test_Conv2d_dilated_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_groups_cuda, test/test_nn.py::TestNN::test_Conv2d_groups_thnn_cuda, test/test_nn.py::TestNN::test_Conv2d_groups_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_pad_same, test/test_nn.py::TestNN::test_Conv2d_strided_cuda, test/test_nn.py::TestNN::test_Conv2d_zero_batch_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_zeros_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d_cuda, test/test_nn.py::TestNN::test_Conv3d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv3d_pad_valid, test/test_nn.py::TestNN::test_Conv3d_pad_valid_cuda, test/test_nn.py::TestNN::test_Conv3d_stride_padding_cuda, test/test_nn.py::TestNN::test_Conv3d_stride_padding_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_zero_batch, test/test_nn.py::TestNN::test_Conv3d_zeros_stride2_pad2_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d_groups, test/test_nn.py::TestNN::test_ConvTranspose2d_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_with_long_tensor, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_ELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_max_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_mean_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_sparse_cuda, test/test_nn.py::TestNN::test_Flatten_cuda, test/test_nn.py::TestNN::test_Fold_cuda, test/test_nn.py::TestNN::test_Fold_no_batch_dim_input, test/test_nn.py::TestNN::test_Hardshrink_no_batch_dim_cuda, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_KLDivLoss_batch_mean, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar_log_target_cuda, test/test_nn.py::TestNN::test_KLDivLoss_with_target_no_reduce_cuda, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_L1Loss_no_reduce_complex_cuda, test/test_nn.py::TestNN::test_Linear_no_bias_cuda, test/test_nn.py::TestNN::test_LogSigmoid_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MaxUnpool1d_net_no_batch_dim, test/test_nn.py::TestNN::test_MaxUnpool1d_net_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MaxUnpool2d_net_cuda, test/test_nn.py::TestNN::test_MaxUnpool2d_net_no_batch_dim, test/test_nn.py::TestNN::test_MaxUnpool3d_net, test/test_nn.py::TestNN::test_MaxUnpool3d_net_cuda, test/test_nn.py::TestNN::test_Mish_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_weights_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_1d_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_weights_no_reduce, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_ignore_index, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_weights, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_NLLLoss_no_reduce, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index_neg_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_with_non_default_args_cuda, test/test_nn.py::TestNN::test_ParameterList, test/test_nn.py::TestNN::test_PixelShuffle_cuda, test/test_nn.py::TestNN::test_PixelUnshuffle_cuda, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_RNN_cell_no_broadcasting, test/test_nn.py::TestNN::test_RNN_dropout_state, test/test_nn.py::TestNN::test_RReLU_cuda, test/test_nn.py::TestNN::test_RReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d_no_batch_dim_cuda, test/test_nn.py::TestNN::test_SELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Sequential_extend, test/test_nn.py::TestNN::test_Sequential_getitem, test/test_nn.py::TestNN::test_Sequential_iadd, test/test_nn.py::TestNN::test_SiLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Sigmoid_no_batch_dim_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_beta, test/test_nn.py::TestNN::test_SmoothL1Loss_beta_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_Softplus_no_batch_dim_cuda, test/test_nn.py::TestNN::test_TransformerEncoderLayer_relu_activation_cuda, test/test_nn.py::TestNN::test_Transformer_cell, test/test_nn.py::TestNN::test_Unfold_cuda, test/test_nn.py::TestNN::test_add_module_raises_error_if_attr_exists, test/test_nn.py::TestNN::test_affine_grid_3d, test/test_nn.py::TestNN::test_affine_grid_backward_cl_cf_consistency_device_cpu_nd_2, test/test_nn.py::TestNN::test_affine_grid_error_checking, test/test_nn.py::TestNN::test_assignment, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_buffer_update_when_stats_are_not_tracked, test/test_nn.py::TestNN::test_batchnorm_cudnn_half, test/test_nn.py::TestNN::test_batchnorm_nhwc_cuda, test/test_nn.py::TestNN::test_batchnorm_non_contig_cpu_BatchNorm2d, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_less_than_one_value_per_channel, test/test_nn.py::TestNN::test_bce_with_logits_gives_same_result_as_sigmoid_and_bce_loss, test/test_nn.py::TestNN::test_bce_with_logits_gives_same_result_as_sigmoid_and_bce_loss_large_tensors_with_grad, test/test_nn.py::TestNN::test_bce_with_logits_ones_in_pos_weights_are_the_same_as_none, test/test_nn.py::TestNN::test_bce_with_logits_with_pos_weight_has_correct_grad_at_zero, test/test_nn.py::TestNN::test_bilinear, test/test_nn.py::TestNN::test_broadcast_double_backwards_gpu, test/test_nn.py::TestNN::test_broadcast_no_grad, test/test_nn.py::TestNN::test_cosine_embedding_loss_no_reduce, test/test_nn.py::TestNN::test_cosine_embedding_loss_with_diff_type, test/test_nn.py::TestNN::test_cross_entropy_loss_precision, test/test_nn.py::TestNN::test_cudnn_weight_tying, test/test_nn.py::TestNN::test_extra_state, test/test_nn.py::TestNN::test_extra_state_missing_set_extra_state, test/test_nn.py::TestNN::test_flatten, test/test_nn.py::TestNN::test_fractional_max_pool2d_invalid_output_ratio, test/test_nn.py::TestNN::test_gaussian_nll_loss_args, test/test_nn.py::TestNN::test_gaussian_nll_loss_broadcasting, test/test_nn.py::TestNN::test_gaussian_nll_loss_scalar_var, test/test_nn.py::TestNN::test_get_buffer, test/test_nn.py::TestNN::test_grid_sample, test/test_nn.py::TestNN::test_grid_sample_3d, test/test_nn.py::TestNN::test_huber_loss_invalid_delta, test/test_nn.py::TestNN::test_inplace_thnn, test/test_nn.py::TestNN::test_interpolate_bicubic_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_shared_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_shared_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_linear_1d_cuda, test/test_nn.py::TestNN::test_interpolate_linear_1d_zero_dim, test/test_nn.py::TestNN::test_interpolate_linear_tuple_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_2d_launch_configs, test/test_nn.py::TestNN::test_interpolate_nearest_3d, test/test_nn.py::TestNN::test_interpolate_nearest_3d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_3d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_3d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_1d, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_2d, test/test_nn.py::TestNN::test_interpolate_trilinear_3d, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d_align_corners, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_align_corners, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_cuda, test/test_nn.py::TestNN::test_interpolate_undefined_behavior_casting, test/test_nn.py::TestNN::test_layer_norm_large_tensor, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightCSR, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightCOO, test/test_nn.py::TestNN::test_log_softmax_scalar, test/test_nn.py::TestNN::test_loss_equal_input_target_shape, test/test_nn.py::TestNN::test_module_super_init, test/test_nn.py::TestNN::test_modules, test/test_nn.py::TestNN::test_multimarginloss_1d_input_0d_target_no_reduce, test/test_nn.py::TestNN::test_named_modules, test/test_nn.py::TestNN::test_overwrite_module_params_on_conversion, test/test_nn.py::TestNN::test_pack_sequence_batch_sizes_throw, test/test_nn.py::TestNN::test_padding_list, test/test_nn.py::TestNN::test_pickle_module_no_weights_only_warning, test/test_nn.py::TestNN::test_pixel_shuffle_nhwc_cpu, test/test_nn.py::TestNN::test_pointwise_loss_broadcast, test/test_nn.py::TestNN::test_projections_lstm_initial_hidden_state, test/test_nn.py::TestNN::test_register_buffer_allows_overwriting_with_same_name, test/test_nn.py::TestNN::test_register_buffer_raises_error_if_attr_exists, test/test_nn.py::TestNN::test_rnn_initial_hidden_state, test/test_nn.py::TestNN::test_set_submodule, test/test_nn.py::TestNN::test_smoothl1loss_intergral_target, test/test_nn.py::TestNN::test_softmax_functional_dim0_cuda, test/test_nn.py::TestNN::test_softmax_spatial, test/test_nn.py::TestNN::test_softmax_spatial_special, test/test_nn.py::TestNN::test_softmin, test/test_nn.py::TestNN::test_spectral_norm, test/test_nn.py::TestNN::test_spectral_norm_dim, test/test_nn.py::TestNN::test_spectral_norm_forward, test/test_nn.py::TestNN::test_state_dict, test/test_nn.py::TestNN::test_to, test/test_nn.py::TestNN::test_type, test/test_nn.py::TestNN::test_unfold_invalid_arg, test/test_nn.py::TestNN::test_upsamplingLinear1d_spatial_invariance, test/test_nn.py::TestNN::test_upsampling_bfloat16, test/test_nn.py::TestNN::test_upsampling_small_scale, test/test_nn.py::TestNN::test_weighted_mse_loss, test/test_nn.py::TestFusionUtils::test_fuse_linear_bn_requires_grad, test/test_nn.py::TestUtils::test_consume_prefix_in_state_dict_if_present, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_sum_use_module_form_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm1d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm3d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_LSTM_differentiable_backward_using_oneDNN_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_LayerNorm_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_warnings_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad2d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad_empty_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_Unfold_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_activations_bfloat16_half_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_adaptiveavg_pool1d_shmem_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotate0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_avg_pool_large_tensor2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_avg_pool_large_tensor_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_mixed_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_0_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_value_foreach_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_one_hot_target_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_sum_weighted_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_sum_weighted_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cudnn_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cudnn_tensor_cpu_length_cuda_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_nan_inf_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_for_single_spatial_element_during_training_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_False_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_invalid_reduction_strings_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_linear_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_log_softmax_big_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_log_softmax_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_forward_with_nans_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_transformer_layout_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_module_to_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_invalid_weights_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_large_tensor_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nn_scalars_reductions_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_one_hot_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_pad_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_rnn_fused_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_smooth_l1_loss_vs_huber_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_unaligned_grad_output_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_complex64, test/test_nn.py::TestNNDeviceTypeCPU::test_transformerencoderlayer_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_False_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_True_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_uint8_cpu_uint8, 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test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_launch_config_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact1d_correctness_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact1d_correctness_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_variable_sequence_cpu_float32 2025-07-17T07:55:45.1457035Z 2025-07-17T07:55:45.5269500Z Uploading artifacts took 0.44 seconds 2025-07-17T07:55:45.5272541Z Running test_spectral_ops 1/1 ... [2025-07-17 07:55:45.527082] 2025-07-17T07:55:45.5272952Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T07:55:45.5276397Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_spectral_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:55:45.527407] 2025-07-17T07:56:48.5313704Z 2025-07-17T07:56:48.5314967Z test_spectral_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_spectral_ops_1.1_6349d2840a068de8_.log 2025-07-17T07:56:48.5418017Z Running 281 items in this shard: test/test_spectral_ops.py::TestFFTCPU::test_batch_istft_cpu, test/test_spectral_ops.py::TestFFTCPU::test_complex_istft_real_equiv_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_definition_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_onesided_cpu, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_real_equiv_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_roundtrip_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_roundtrip_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_cufft_context_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_cufft_context_cpu_complex64, 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test/test_spectral_ops.py::TestFFTCPU::test_fft_half_and_bfloat16_errors_fft_irfft2_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_fft_half_and_bfloat16_errors_fft_irfft_cpu_bfloat16, test/test_spectral_ops.py::TestFFTCPU::test_fft_half_and_bfloat16_errors_fft_irfft_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_fft_half_and_bfloat16_errors_fft_irfftn_cpu_bfloat16, test/test_spectral_ops.py::TestFFTCPU::test_fft_half_and_bfloat16_errors_fft_irfftn_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_fft_half_and_bfloat16_errors_fft_rfft2_cpu_bfloat16, test/test_spectral_ops.py::TestFFTCPU::test_fft_half_and_bfloat16_errors_fft_rfft2_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_fft_half_and_bfloat16_errors_fft_rfft_cpu_bfloat16, test/test_spectral_ops.py::TestFFTCPU::test_fft_half_and_bfloat16_errors_fft_rfft_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_fft_half_and_bfloat16_errors_fft_rfftn_cpu_bfloat16, test/test_spectral_ops.py::TestFFTCPU::test_fft_half_and_bfloat16_errors_fft_rfftn_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_fft_ifft_rfft_irfft_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_fft_input_modification_cpu, test/test_spectral_ops.py::TestFFTCPU::test_fft_invalid_dtypes_cpu, test/test_spectral_ops.py::TestFFTCPU::test_fft_plan_repeatable_cpu, test/test_spectral_ops.py::TestFFTCPU::test_fft_round_trip_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_fft_round_trip_cpu_complex32, test/test_spectral_ops.py::TestFFTCPU::test_fft_round_trip_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fft_round_trip_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_fft_round_trip_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fft_round_trip_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_fft_type_promotion_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_fft_type_promotion_cpu_complex32, test/test_spectral_ops.py::TestFFTCPU::test_fft_type_promotion_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fft_type_promotion_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_fft_type_promotion_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fft_type_promotion_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_fft_type_promotion_cpu_int8, test/test_spectral_ops.py::TestFFTCPU::test_fftfreq_numpy_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftfreq_numpy_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_fftfreq_out_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftfreq_out_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid__refs_fft_fftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid__refs_fft_fftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid__refs_fft_hfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid__refs_fft_hfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid__refs_fft_ifftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid__refs_fft_ifftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid__refs_fft_ihfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid__refs_fft_irfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid__refs_fft_irfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid__refs_fft_rfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid_fft_fftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid_fft_fftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid_fft_hfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid_fft_hfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid_fft_ifftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid_fft_ifftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid_fft_ihfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid_fft_irfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid_fft_irfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_invalid_fft_rfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_noop_transform_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_fftn_noop_transform_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_noop_transform_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_fftn_noop_transform_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_noop_transform_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_round_trip_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_fftn_round_trip_cpu_complex32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_round_trip_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fftn_round_trip_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_fftn_round_trip_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftn_round_trip_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_fftshift_frequencies_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftshift_frequencies_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_fftshift_numpy_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_fftshift_numpy_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_fftshift_numpy_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_fftshift_numpy_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_hfftn_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_hfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_hfftn_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_ihfftn_cpu_float16, test/test_spectral_ops.py::TestFFTCPU::test_ihfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_ihfftn_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_istft_against_librosa_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_istft_linearity_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_istft_of_sine_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_istft_requires_window_cpu, test/test_spectral_ops.py::TestFFTCPU::test_istft_round_trip_simple_cases_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_istft_round_trip_various_params_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_istft_round_trip_with_padding_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_istft_throws_cpu, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d__refs_fft_fft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d__refs_fft_fft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d__refs_fft_hfft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d__refs_fft_hfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d__refs_fft_ifft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d__refs_fft_ifft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d__refs_fft_ihfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d__refs_fft_irfft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d__refs_fft_irfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d__refs_fft_rfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_fft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_fft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_hfft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_hfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_ifft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_ifft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_ihfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_irfft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_irfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_rfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_fftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_fftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_hfftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_hfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_ifftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_ifftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_irfftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_irfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_fftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_fftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_hfftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_hfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_ifftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_ifftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_irfftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_irfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_stft_align_to_window_only_requires_non_center_cpu, test/test_spectral_ops.py::TestFFTCPU::test_stft_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_stft_requires_complex_cpu, test/test_spectral_ops.py::TestFFTCPU::test_stft_requires_window_cpu, test/test_spectral_ops.py::TestFFTCPU::test_stft_roundtrip_complex_window_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_stft_roundtrip_complex_window_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_stft_window_device_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_fft2_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_fft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_fftfreq_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_fftn_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_fftshift_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_hfft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_ifft2_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_ifft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_ifftn_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_ifftshift_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_ihfft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_irfft2_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_irfft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_irfftn_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfft2_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfftfreq_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfftn_cpu 2025-07-17T07:56:48.5510833Z 2025-07-17T07:56:48.5511103Z Running distributions/test_distributions 1/3 ... [2025-07-17 07:56:48.532151] 2025-07-17T07:56:48.5511606Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T07:56:48.5512725Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'distributions/test_distributions.py', '--shard-id=1', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:56:48.532485] 2025-07-17T08:01:31.0995084Z 2025-07-17T08:01:31.0996204Z distributions/test_distributions 1/3 was successful, full logs can be found in artifacts with path test/test-reports/distributions.test_distributions_1.3_8645f5ba656f90ea_.log 2025-07-17T08:01:31.1026419Z Running 71 items in this shard: test/distributions/test_distributions.py::TestDistributions::test_argmax_relaxed_categorical, test/distributions/test_distributions.py::TestDistributions::test_binomial_extreme_vals, test/distributions/test_distributions.py::TestDistributions::test_binomial_half, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_categorical_2d, test/distributions/test_distributions.py::TestDistributions::test_dirichlet_log_prob_zero, test/distributions/test_distributions.py::TestDistributions::test_dirichlet_mode, test/distributions/test_distributions.py::TestDistributions::test_exponential_sample, test/distributions/test_distributions.py::TestDistributions::test_fishersnedecor_sample, test/distributions/test_distributions.py::TestDistributions::test_generalized_pareto_sample, test/distributions/test_distributions.py::TestDistributions::test_geometric_sample, test/distributions/test_distributions.py::TestDistributions::test_halfcauchy, test/distributions/test_distributions.py::TestDistributions::test_halfnormal, test/distributions/test_distributions.py::TestDistributions::test_halfnormal_logprob, test/distributions/test_distributions.py::TestDistributions::test_has_examples, test/distributions/test_distributions.py::TestDistributions::test_independent_expand, test/distributions/test_distributions.py::TestDistributions::test_invalid_parameter_broadcasting, test/distributions/test_distributions.py::TestDistributions::test_kumaraswamy_shape, test/distributions/test_distributions.py::TestDistributions::test_lkj_cholesky_log_prob, test/distributions/test_distributions.py::TestDistributions::test_logisticnormal_logprob, test/distributions/test_distributions.py::TestDistributions::test_lognormal_sample, test/distributions/test_distributions.py::TestDistributions::test_lowrank_multivariate_normal_properties, test/distributions/test_distributions.py::TestDistributions::test_mixture_same_family_binomial_log_prob, test/distributions/test_distributions.py::TestDistributions::test_mixture_same_family_sample, test/distributions/test_distributions.py::TestDistributions::test_multinomial_1d_log_prob_and_entropy, test/distributions/test_distributions.py::TestDistributions::test_multinomial_sequential_draw, test/distributions/test_distributions.py::TestDistributions::test_multivariate_normal_moments, test/distributions/test_distributions.py::TestDistributions::test_multivariate_normal_shape, test/distributions/test_distributions.py::TestDistributions::test_negative_binomial_log_prob, test/distributions/test_distributions.py::TestDistributions::test_one_hot_categorical_2d, test/distributions/test_distributions.py::TestDistributions::test_poisson_forward_ad, test/distributions/test_distributions.py::TestDistributions::test_poisson_shape, test/distributions/test_distributions.py::TestDistributions::test_relaxed_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_relaxed_one_hot_categorical_2d, test/distributions/test_distributions.py::TestDistributions::test_sample_detached, test/distributions/test_distributions.py::TestDistributions::test_studentT, test/distributions/test_distributions.py::TestDistributions::test_torch_binomial_dtype_errors, test/distributions/test_distributions.py::TestDistributions::test_wishart_log_prob, test/distributions/test_distributions.py::TestDistributions::test_wishart_moments, test/distributions/test_distributions.py::TestDistributions::test_wishart_shape, test/distributions/test_distributions.py::TestDistributions::test_wishart_stable_with_precision_matrix, test/distributions/test_distributions.py::TestRsample::test_gamma, test/distributions/test_distributions.py::TestDistributionShapes::test_bernoulli_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_beta_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_binomial_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_continuous_bernoulli_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_dirichlet_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_gamma_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_geometric_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_laplace_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_mixture_same_family_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_normal_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_one_hot_categorical_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_studentT_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_vonmises_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_weibull_scale_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_wishart_shape_tensor_params, test/distributions/test_distributions.py::TestKL::test_entropy_exponential_family, test/distributions/test_distributions.py::TestKL::test_kl_infinite, test/distributions/test_distributions.py::TestKL::test_kl_lowrank_multivariate_normal_batched, test/distributions/test_distributions.py::TestKL::test_kl_multivariate_normal, test/distributions/test_distributions.py::TestNumericalStability::test_bernoulli_with_logits_overflow, test/distributions/test_distributions.py::TestNumericalStability::test_categorical_log_prob, test/distributions/test_distributions.py::TestNumericalStability::test_categorical_log_prob_with_logits, test/distributions/test_distributions.py::TestAgainstScipy::test_icdf, test/distributions/test_distributions.py::TestAgainstScipy::test_variance_stddev, test/distributions/test_distributions.py::TestFunctors::test_cat_transform, test/distributions/test_distributions.py::TestValidation::test_invalid, test/distributions/test_distributions.py::TestJit::test_mean, test/distributions/test_distributions.py::TestJit::test_rsample, test/distributions/test_distributions.py::TestJit::test_variance 2025-07-17T08:01:31.1055466Z 2025-07-17T08:01:31.1055725Z Running distributions/test_distributions 3/3 ... [2025-07-17 08:01:31.099337] 2025-07-17T08:01:31.1056217Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:01:31.1057364Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'distributions/test_distributions.py', '--shard-id=3', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:01:31.099720] 2025-07-17T08:04:18.4443537Z 2025-07-17T08:04:18.4444694Z distributions/test_distributions 3/3 was successful, full logs can be found in artifacts with path test/test-reports/distributions.test_distributions_3.3_f255a45fb4a25492_.log 2025-07-17T08:04:18.4481681Z Running 81 items in this shard: test/distributions/test_distributions.py::TestDistributions::test_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_bernoulli_enumerate_support, test/distributions/test_distributions.py::TestDistributions::test_beta_underflow, test/distributions/test_distributions.py::TestDistributions::test_binomial, test/distributions/test_distributions.py::TestDistributions::test_binomial_log_prob_and_entropy, test/distributions/test_distributions.py::TestDistributions::test_binomial_log_prob_vectorized_count, test/distributions/test_distributions.py::TestDistributions::test_binomial_vectorized_count, test/distributions/test_distributions.py::TestDistributions::test_cauchy, test/distributions/test_distributions.py::TestDistributions::test_cdf_icdf_inverse, test/distributions/test_distributions.py::TestDistributions::test_cdf_log_prob, test/distributions/test_distributions.py::TestDistributions::test_chi2_shape, test/distributions/test_distributions.py::TestDistributions::test_dirichlet_log_prob, test/distributions/test_distributions.py::TestDistributions::test_dirichlet_sample, test/distributions/test_distributions.py::TestDistributions::test_dirichlet_shape, test/distributions/test_distributions.py::TestDistributions::test_enumerate_support_type, test/distributions/test_distributions.py::TestDistributions::test_fishersnedecor, test/distributions/test_distributions.py::TestDistributions::test_gamma_gpu_sample, test/distributions/test_distributions.py::TestDistributions::test_gamma_gpu_shape, test/distributions/test_distributions.py::TestDistributions::test_gamma_shape, test/distributions/test_distributions.py::TestDistributions::test_generalized_pareto, test/distributions/test_distributions.py::TestDistributions::test_geometric_log_prob_and_entropy, test/distributions/test_distributions.py::TestDistributions::test_gumbel, test/distributions/test_distributions.py::TestDistributions::test_gumbel_sample, test/distributions/test_distributions.py::TestDistributions::test_halfnormal_sample, test/distributions/test_distributions.py::TestDistributions::test_independent_shape, test/distributions/test_distributions.py::TestDistributions::test_inversegamma, test/distributions/test_distributions.py::TestDistributions::test_kumaraswamy_mean_variance, test/distributions/test_distributions.py::TestDistributions::test_laplace_sample, test/distributions/test_distributions.py::TestDistributions::test_lazy_property_grad, test/distributions/test_distributions.py::TestDistributions::test_lognormal, test/distributions/test_distributions.py::TestDistributions::test_lognormal_logprob, test/distributions/test_distributions.py::TestDistributions::test_lowrank_multivariate_normal_moments, test/distributions/test_distributions.py::TestDistributions::test_lowrank_multivariate_normal_shape, test/distributions/test_distributions.py::TestDistributions::test_mixture_same_family_normal_log_prob, test/distributions/test_distributions.py::TestDistributions::test_mixture_same_family_shape, test/distributions/test_distributions.py::TestDistributions::test_mode, test/distributions/test_distributions.py::TestDistributions::test_multinomial_1d, test/distributions/test_distributions.py::TestDistributions::test_multinomial_2d, test/distributions/test_distributions.py::TestDistributions::test_multivariate_normal_log_prob, test/distributions/test_distributions.py::TestDistributions::test_multivariate_normal_properties, test/distributions/test_distributions.py::TestDistributions::test_multivariate_normal_sample, test/distributions/test_distributions.py::TestDistributions::test_negative_binomial, test/distributions/test_distributions.py::TestDistributions::test_negative_binomial_log_prob_vectorized_count, test/distributions/test_distributions.py::TestDistributions::test_one_hot_categorical_1d, test/distributions/test_distributions.py::TestDistributions::test_pareto_sample, test/distributions/test_distributions.py::TestDistributions::test_poisson_sample, test/distributions/test_distributions.py::TestDistributions::test_relaxed_one_hot_categorical_1d, test/distributions/test_distributions.py::TestDistributions::test_rounded_relaxed_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_studentT_log_prob, test/distributions/test_distributions.py::TestDistributions::test_uniform, test/distributions/test_distributions.py::TestDistributions::test_vonmises_sample, test/distributions/test_distributions.py::TestDistributions::test_wishart_properties, test/distributions/test_distributions.py::TestRsample::test_beta_wrt_beta, test/distributions/test_distributions.py::TestDistributionShapes::test_bernoulli_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_binomial_shape_vectorized_n, test/distributions/test_distributions.py::TestDistributionShapes::test_cauchy_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_chi2_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_continuous_bernoulli_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_exponential_shape_scalar_param, test/distributions/test_distributions.py::TestDistributionShapes::test_gamma_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_geometric_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_kumaraswamy_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_laplace_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_mixture_same_family_mean_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_pareto_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_studentT_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_uniform_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_wishart_shape_scalar_params, test/distributions/test_distributions.py::TestKL::test_kl_edgecases, test/distributions/test_distributions.py::TestKL::test_kl_multivariate_normal_batched, test/distributions/test_distributions.py::TestKL::test_kl_shape, test/distributions/test_distributions.py::TestKL::test_kl_transformed, test/distributions/test_distributions.py::TestConstraints::test_support_constraints, test/distributions/test_distributions.py::TestNumericalStability::test_bernoulli_with_logits_underflow, test/distributions/test_distributions.py::TestNumericalStability::test_continuous_bernoulli_with_logits_underflow, test/distributions/test_distributions.py::TestNumericalStability::test_multinomial_log_prob, test/distributions/test_distributions.py::TestLazyLogitsInitialization::test_lazy_probs_initialization, test/distributions/test_distributions.py::TestAgainstScipy::test_cdf, test/distributions/test_distributions.py::TestAgainstScipy::test_mean, test/distributions/test_distributions.py::TestFunctors::test_cat_transform_non_uniform, test/distributions/test_distributions.py::TestValidation::test_warning_unimplemented_constraints 2025-07-17T08:04:18.4515289Z 2025-07-17T08:04:18.4515592Z Running test_cpp_extensions_open_device_registration 1/1 ... [2025-07-17 08:04:18.444743] 2025-07-17T08:04:19.9653164Z -- The CXX compiler identification is Clang 12.0.1 2025-07-17T08:04:20.0798938Z -- The C compiler identification is Clang 12.0.1 2025-07-17T08:04:20.1051764Z -- Detecting CXX compiler ABI info 2025-07-17T08:04:20.3086592Z -- Detecting CXX compiler ABI info - done 2025-07-17T08:04:20.3223876Z -- Check for working CXX compiler: /opt/cache/bin/c++ - skipped 2025-07-17T08:04:20.3232443Z -- Detecting CXX compile features 2025-07-17T08:04:20.3244579Z -- Detecting CXX compile features - done 2025-07-17T08:04:20.3436345Z -- Detecting C compiler ABI info 2025-07-17T08:04:20.4927170Z -- Detecting C compiler ABI info - done 2025-07-17T08:04:20.5056566Z -- Check for working C compiler: /opt/cache/bin/cc - skipped 2025-07-17T08:04:20.5060031Z -- Detecting C compile features 2025-07-17T08:04:20.5064832Z -- Detecting C compile features - done 2025-07-17T08:04:20.7223862Z CMake Warning at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:22 (message): 2025-07-17T08:04:20.7224792Z static library kineto_LIBRARY-NOTFOUND not found. 2025-07-17T08:04:20.7225186Z Call Stack (most recent call first): 2025-07-17T08:04:20.7225900Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:125 (append_torchlib_if_found) 2025-07-17T08:04:20.7226637Z CMakeLists.txt:27 (find_package) 2025-07-17T08:04:20.7226855Z 2025-07-17T08:04:20.7226968Z  2025-07-17T08:04:20.7232535Z -- Found Torch: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch.so 2025-07-17T08:04:20.7303036Z -- Configuring done (1.0s) 2025-07-17T08:04:20.7434070Z -- Generating done (0.0s) 2025-07-17T08:04:20.7447467Z -- Build files have been written to: /var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/build 2025-07-17T08:04:20.8914604Z [ 5%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/device.cpp.o 2025-07-17T08:04:20.8917226Z [ 11%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/memory.cpp.o 2025-07-17T08:04:20.9963727Z [ 17%] Linking CXX shared library libopenreg.so 2025-07-17T08:04:21.0773081Z [ 17%] Built target openreg 2025-07-17T08:04:21.0873595Z [ 23%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegExtra.cpp.o 2025-07-17T08:04:21.0875309Z [ 29%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegMinimal.cpp.o 2025-07-17T08:04:21.0880836Z [ 35%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Minimal.cpp.o 2025-07-17T08:04:21.0885954Z [ 47%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegDeviceAllocator.cpp.o 2025-07-17T08:04:21.0887583Z [ 47%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Extra.cpp.o 2025-07-17T08:04:21.0893034Z [ 58%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegFunctions.cpp.o 2025-07-17T08:04:21.0894688Z [ 58%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGenerator.cpp.o 2025-07-17T08:04:21.0898555Z [ 64%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGuard.cpp.o 2025-07-17T08:04:21.2924991Z [ 70%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHooks.cpp.o 2025-07-17T08:04:21.3212112Z [ 76%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHostAllocator.cpp.o 2025-07-17T08:04:21.3488341Z [ 82%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegSerialization.cpp.o 2025-07-17T08:04:21.8828534Z [ 88%] Linking CXX shared library libtorch_openreg.so 2025-07-17T08:04:22.4045406Z [ 88%] Built target torch_openreg 2025-07-17T08:04:22.4141945Z [ 94%] Building CXX object torch_openreg/csrc/CMakeFiles/torch_bindings.dir/Module.cpp.o 2025-07-17T08:04:23.0224593Z [100%] Linking CXX shared library libtorch_bindings.so 2025-07-17T08:04:23.1688113Z [100%] Built target torch_bindings 2025-07-17T08:04:23.1758816Z Install the project... 2025-07-17T08:04:23.1786619Z -- Install configuration: "" 2025-07-17T08:04:23.2377337Z running install 2025-07-17T08:04:23.2395272Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-07-17T08:04:23.2396076Z !! 2025-07-17T08:04:23.2396204Z 2025-07-17T08:04:23.2396324Z ******************************************************************************** 2025-07-17T08:04:23.2396725Z Please avoid running ``setup.py`` directly. 2025-07-17T08:04:23.2397132Z Instead, use pypa/build, pypa/installer or other 2025-07-17T08:04:23.2397495Z standards-based tools. 2025-07-17T08:04:23.2397701Z 2025-07-17T08:04:23.2397933Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-07-17T08:04:23.2398423Z or your builds will no longer be supported. 2025-07-17T08:04:23.2398666Z 2025-07-17T08:04:23.2399198Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-07-17T08:04:23.2399740Z ******************************************************************************** 2025-07-17T08:04:23.2399996Z 2025-07-17T08:04:23.2400074Z !! 2025-07-17T08:04:23.2400296Z self.initialize_options() 2025-07-17T08:04:23.2530664Z running build 2025-07-17T08:04:23.2530963Z running build_py 2025-07-17T08:04:23.2618213Z creating build/lib.linux-x86_64-cpython-313/torch_openreg 2025-07-17T08:04:23.2619998Z copying torch_openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg 2025-07-17T08:04:23.2628139Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-07-17T08:04:23.2630220Z copying torch_openreg/openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-07-17T08:04:23.2636912Z copying torch_openreg/openreg/random.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-07-17T08:04:23.2648187Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:23.2649403Z copying torch_openreg/lib/libopenreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:23.2664460Z copying torch_openreg/lib/libtorch_openreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:23.2785743Z copying torch_openreg/lib/libtorch_bindings.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:23.2825362Z running build_ext 2025-07-17T08:04:23.2949198Z building 'torch_openreg._C' extension 2025-07-17T08:04:23.2951052Z creating build/temp.linux-x86_64-cpython-313/torch_openreg/csrc 2025-07-17T08:04:23.2954702Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/include/python3.13 -c torch_openreg/csrc/stub.c -o build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -g -Wall -Werror 2025-07-17T08:04:23.4734558Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -L/var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/torch_openreg/lib -ltorch_bindings -o build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -Wl,-rpath,$ORIGIN/lib 2025-07-17T08:04:23.4973238Z running install_lib 2025-07-17T08:04:23.5064982Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages 2025-07-17T08:04:23.5069090Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg 2025-07-17T08:04:23.5070769Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/__init__.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg 2025-07-17T08:04:23.5072597Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg 2025-07-17T08:04:23.5074168Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/openreg/__init__.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg 2025-07-17T08:04:23.5075936Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/openreg/random.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg 2025-07-17T08:04:23.5077305Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-07-17T08:04:23.5078818Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libopenreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-07-17T08:04:23.5080796Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_openreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-07-17T08:04:23.5100721Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_bindings.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-07-17T08:04:23.5106618Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg 2025-07-17T08:04:23.5112322Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/__init__.py to __init__.cpython-313.pyc 2025-07-17T08:04:23.5115836Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg/__init__.py to __init__.cpython-313.pyc 2025-07-17T08:04:23.5121915Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg/random.py to random.cpython-313.pyc 2025-07-17T08:04:23.5127401Z running install_egg_info 2025-07-17T08:04:23.5319245Z running egg_info 2025-07-17T08:04:23.5395916Z creating torch_openreg.egg-info 2025-07-17T08:04:23.5397335Z writing torch_openreg.egg-info/PKG-INFO 2025-07-17T08:04:23.5401049Z writing dependency_links to torch_openreg.egg-info/dependency_links.txt 2025-07-17T08:04:23.5403016Z writing requirements to torch_openreg.egg-info/requires.txt 2025-07-17T08:04:23.5404177Z writing top-level names to torch_openreg.egg-info/top_level.txt 2025-07-17T08:04:23.5405760Z writing manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-07-17T08:04:23.5491944Z reading manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-07-17T08:04:23.5498781Z writing manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-07-17T08:04:23.5501270Z Copying torch_openreg.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg-0.0.1-py3.13.egg-info 2025-07-17T08:04:23.5507211Z running install_scripts 2025-07-17T08:04:23.8472514Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:04:23.8475104Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_extensions_open_device_registration.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:04:23.847264] 2025-07-17T08:04:30.3708716Z 2025-07-17T08:04:30.3710194Z test_cpp_extensions_open_device_registration 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_open_device_registration_1.1_5b85fe74af06c094_.log 2025-07-17T08:04:30.3713498Z Running 3 items in this shard: test/test_cpp_extensions_open_device_registration.py::TestCppExtensionOpenRegistration::test_open_device_scalar_type_fallback, test/test_cpp_extensions_open_device_registration.py::TestCppExtensionOpenRegistration::test_open_device_tensor_type_fallback, test/test_cpp_extensions_open_device_registration.py::TestCppExtensionOpenRegistration::test_open_device_tensorlist_type_fallback 2025-07-17T08:04:30.3715410Z 2025-07-17T08:04:30.3715656Z Running test_transformers_privateuse1 1/1 ... [2025-07-17 08:04:30.371067] 2025-07-17T08:04:31.7599163Z -- The CXX compiler identification is Clang 12.0.1 2025-07-17T08:04:31.8343464Z -- The C compiler identification is Clang 12.0.1 2025-07-17T08:04:31.8424678Z -- Detecting CXX compiler ABI info 2025-07-17T08:04:31.9967761Z -- Detecting CXX compiler ABI info - done 2025-07-17T08:04:32.0105615Z -- Check for working CXX compiler: /opt/cache/bin/c++ - skipped 2025-07-17T08:04:32.0108556Z -- Detecting CXX compile features 2025-07-17T08:04:32.0114344Z -- Detecting CXX compile features - done 2025-07-17T08:04:32.0228971Z -- Detecting C compiler ABI info 2025-07-17T08:04:32.1427895Z -- Detecting C compiler ABI info - done 2025-07-17T08:04:32.1555772Z -- Check for working C compiler: /opt/cache/bin/cc - skipped 2025-07-17T08:04:32.1559324Z -- Detecting C compile features 2025-07-17T08:04:32.1564004Z -- Detecting C compile features - done 2025-07-17T08:04:32.2665902Z CMake Warning at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:22 (message): 2025-07-17T08:04:32.2666718Z static library kineto_LIBRARY-NOTFOUND not found. 2025-07-17T08:04:32.2667088Z Call Stack (most recent call first): 2025-07-17T08:04:32.2667807Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:125 (append_torchlib_if_found) 2025-07-17T08:04:32.2668605Z CMakeLists.txt:27 (find_package) 2025-07-17T08:04:32.2668808Z 2025-07-17T08:04:32.2668938Z  2025-07-17T08:04:32.2676591Z -- Found Torch: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch.so 2025-07-17T08:04:32.2702780Z -- Configuring done (0.7s) 2025-07-17T08:04:32.2820699Z -- Generating done (0.0s) 2025-07-17T08:04:32.2858394Z -- Build files have been written to: /var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/build 2025-07-17T08:04:32.4316835Z [ 5%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/device.cpp.o 2025-07-17T08:04:32.4320456Z [ 11%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/memory.cpp.o 2025-07-17T08:04:32.5302105Z [ 17%] Linking CXX shared library libopenreg.so 2025-07-17T08:04:32.6114501Z [ 17%] Built target openreg 2025-07-17T08:04:32.6215974Z [ 23%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegExtra.cpp.o 2025-07-17T08:04:32.6223323Z [ 29%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegMinimal.cpp.o 2025-07-17T08:04:32.6224795Z [ 35%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Extra.cpp.o 2025-07-17T08:04:32.6229882Z [ 47%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Minimal.cpp.o 2025-07-17T08:04:32.6231516Z [ 47%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegDeviceAllocator.cpp.o 2025-07-17T08:04:32.6237244Z [ 52%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegFunctions.cpp.o 2025-07-17T08:04:32.6238826Z [ 58%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGenerator.cpp.o 2025-07-17T08:04:32.6244024Z [ 64%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGuard.cpp.o 2025-07-17T08:04:32.8238957Z [ 70%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHooks.cpp.o 2025-07-17T08:04:32.8568554Z [ 76%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHostAllocator.cpp.o 2025-07-17T08:04:32.8798357Z [ 82%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegSerialization.cpp.o 2025-07-17T08:04:33.3866235Z [ 88%] Linking CXX shared library libtorch_openreg.so 2025-07-17T08:04:33.8672197Z [ 88%] Built target torch_openreg 2025-07-17T08:04:33.8764733Z [ 94%] Building CXX object torch_openreg/csrc/CMakeFiles/torch_bindings.dir/Module.cpp.o 2025-07-17T08:04:34.4360259Z [100%] Linking CXX shared library libtorch_bindings.so 2025-07-17T08:04:34.5846164Z [100%] Built target torch_bindings 2025-07-17T08:04:34.5917781Z Install the project... 2025-07-17T08:04:34.5947827Z -- Install configuration: "" 2025-07-17T08:04:34.6568740Z running install 2025-07-17T08:04:34.6570096Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-07-17T08:04:34.6570982Z !! 2025-07-17T08:04:34.6571101Z 2025-07-17T08:04:34.6571227Z ******************************************************************************** 2025-07-17T08:04:34.6571613Z Please avoid running ``setup.py`` directly. 2025-07-17T08:04:34.6572035Z Instead, use pypa/build, pypa/installer or other 2025-07-17T08:04:34.6572412Z standards-based tools. 2025-07-17T08:04:34.6572599Z 2025-07-17T08:04:34.6572829Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-07-17T08:04:34.6574037Z or your builds will no longer be supported. 2025-07-17T08:04:34.6574311Z 2025-07-17T08:04:34.6574697Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-07-17T08:04:34.6575215Z ******************************************************************************** 2025-07-17T08:04:34.6575467Z 2025-07-17T08:04:34.6575546Z !! 2025-07-17T08:04:34.6575762Z self.initialize_options() 2025-07-17T08:04:34.6709125Z running build 2025-07-17T08:04:34.6709379Z running build_py 2025-07-17T08:04:34.6797686Z creating build/lib.linux-x86_64-cpython-313/torch_openreg 2025-07-17T08:04:34.6799468Z copying torch_openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg 2025-07-17T08:04:34.6802149Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-07-17T08:04:34.6803430Z copying torch_openreg/openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-07-17T08:04:34.6805901Z copying torch_openreg/openreg/random.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-07-17T08:04:34.6811333Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:34.6812626Z copying torch_openreg/lib/libopenreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:34.6828488Z copying torch_openreg/lib/libtorch_openreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:34.6947438Z copying torch_openreg/lib/libtorch_bindings.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:34.6988921Z running build_ext 2025-07-17T08:04:34.7094591Z building 'torch_openreg._C' extension 2025-07-17T08:04:34.7096430Z creating build/temp.linux-x86_64-cpython-313/torch_openreg/csrc 2025-07-17T08:04:34.7100201Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/include/python3.13 -c torch_openreg/csrc/stub.c -o build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -g -Wall -Werror 2025-07-17T08:04:34.8428815Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -L/var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/torch_openreg/lib -ltorch_bindings -o build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -Wl,-rpath,$ORIGIN/lib 2025-07-17T08:04:34.8663276Z running install_lib 2025-07-17T08:04:34.8758718Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libopenreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-07-17T08:04:34.8761234Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_openreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-07-17T08:04:34.8784869Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_bindings.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-07-17T08:04:34.8791472Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg 2025-07-17T08:04:34.8797248Z running install_egg_info 2025-07-17T08:04:34.8991498Z running egg_info 2025-07-17T08:04:34.9068560Z writing torch_openreg.egg-info/PKG-INFO 2025-07-17T08:04:34.9073875Z writing dependency_links to torch_openreg.egg-info/dependency_links.txt 2025-07-17T08:04:34.9080554Z writing requirements to torch_openreg.egg-info/requires.txt 2025-07-17T08:04:34.9087048Z writing top-level names to torch_openreg.egg-info/top_level.txt 2025-07-17T08:04:34.9173785Z reading manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-07-17T08:04:34.9182849Z writing manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-07-17T08:04:34.9190597Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg-0.0.1-py3.13.egg-info' (and everything under it) 2025-07-17T08:04:34.9192449Z Copying torch_openreg.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg-0.0.1-py3.13.egg-info 2025-07-17T08:04:34.9198820Z running install_scripts 2025-07-17T08:04:35.2083773Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:04:35.2087383Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_transformers_privateuse1.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:04:35.208479] 2025-07-17T08:04:39.8792842Z 2025-07-17T08:04:39.8793825Z test_transformers_privateuse1 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_transformers_privateuse1_1.1_3f5a5829b5653423_.log 2025-07-17T08:04:39.8796724Z Running 3 items in this shard: test/test_transformers_privateuse1.py::TestSDPAPrivateUse1Only::test_fused_sdp_choice_privateuseone, test/test_transformers_privateuse1.py::TestSDPAPrivateUse1Only::test_scaled_dot_product_fused_attention_overrideable, test/test_transformers_privateuse1.py::TestSDPAPrivateUse1Only::test_scaled_dot_product_fused_attention_overrideable_backward 2025-07-17T08:04:39.8798499Z 2025-07-17T08:04:39.8798680Z Running test_openreg 1/1 ... [2025-07-17 08:04:39.879545] 2025-07-17T08:04:41.2686063Z -- The CXX compiler identification is Clang 12.0.1 2025-07-17T08:04:41.3432192Z -- The C compiler identification is Clang 12.0.1 2025-07-17T08:04:41.3515198Z -- Detecting CXX compiler ABI info 2025-07-17T08:04:41.5372308Z -- Detecting CXX compiler ABI info - done 2025-07-17T08:04:41.5510744Z -- Check for working CXX compiler: /opt/cache/bin/c++ - skipped 2025-07-17T08:04:41.5514773Z -- Detecting CXX compile features 2025-07-17T08:04:41.5521621Z -- Detecting CXX compile features - done 2025-07-17T08:04:41.5636949Z -- Detecting C compiler ABI info 2025-07-17T08:04:41.6841488Z -- Detecting C compiler ABI info - done 2025-07-17T08:04:41.6971733Z -- Check for working C compiler: /opt/cache/bin/cc - skipped 2025-07-17T08:04:41.6977456Z -- Detecting C compile features 2025-07-17T08:04:41.6982847Z -- Detecting C compile features - done 2025-07-17T08:04:41.8092518Z CMake Warning at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:22 (message): 2025-07-17T08:04:41.8093320Z static library kineto_LIBRARY-NOTFOUND not found. 2025-07-17T08:04:41.8093707Z Call Stack (most recent call first): 2025-07-17T08:04:41.8094442Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:125 (append_torchlib_if_found) 2025-07-17T08:04:41.8095164Z CMakeLists.txt:27 (find_package) 2025-07-17T08:04:41.8095392Z 2025-07-17T08:04:41.8095501Z  2025-07-17T08:04:41.8100900Z -- Found Torch: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch.so 2025-07-17T08:04:41.8127142Z -- Configuring done (0.7s) 2025-07-17T08:04:41.8243683Z -- Generating done (0.0s) 2025-07-17T08:04:41.8253770Z -- Build files have been written to: /var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/build 2025-07-17T08:04:41.9712114Z [ 5%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/device.cpp.o 2025-07-17T08:04:41.9714285Z [ 11%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/memory.cpp.o 2025-07-17T08:04:42.0719270Z [ 17%] Linking CXX shared library libopenreg.so 2025-07-17T08:04:42.1508818Z [ 17%] Built target openreg 2025-07-17T08:04:42.1612473Z [ 23%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegExtra.cpp.o 2025-07-17T08:04:42.1614106Z [ 29%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegMinimal.cpp.o 2025-07-17T08:04:42.1618761Z [ 35%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Extra.cpp.o 2025-07-17T08:04:42.1621634Z [ 41%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegDeviceAllocator.cpp.o 2025-07-17T08:04:42.1623380Z [ 47%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Minimal.cpp.o 2025-07-17T08:04:42.1630893Z [ 52%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegFunctions.cpp.o 2025-07-17T08:04:42.1632371Z [ 58%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGenerator.cpp.o 2025-07-17T08:04:42.1633715Z [ 64%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGuard.cpp.o 2025-07-17T08:04:42.3427015Z [ 70%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHooks.cpp.o 2025-07-17T08:04:42.3886593Z [ 76%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHostAllocator.cpp.o 2025-07-17T08:04:42.4115824Z [ 82%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegSerialization.cpp.o 2025-07-17T08:04:42.9604140Z [ 88%] Linking CXX shared library libtorch_openreg.so 2025-07-17T08:04:43.4318332Z [ 88%] Built target torch_openreg 2025-07-17T08:04:43.4408052Z [ 94%] Building CXX object torch_openreg/csrc/CMakeFiles/torch_bindings.dir/Module.cpp.o 2025-07-17T08:04:43.9979768Z [100%] Linking CXX shared library libtorch_bindings.so 2025-07-17T08:04:44.1429175Z [100%] Built target torch_bindings 2025-07-17T08:04:44.1499406Z Install the project... 2025-07-17T08:04:44.1526305Z -- Install configuration: "" 2025-07-17T08:04:44.2110170Z running install 2025-07-17T08:04:44.2112352Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-07-17T08:04:44.2113174Z !! 2025-07-17T08:04:44.2113300Z 2025-07-17T08:04:44.2113419Z ******************************************************************************** 2025-07-17T08:04:44.2113803Z Please avoid running ``setup.py`` directly. 2025-07-17T08:04:44.2114194Z Instead, use pypa/build, pypa/installer or other 2025-07-17T08:04:44.2114573Z standards-based tools. 2025-07-17T08:04:44.2114772Z 2025-07-17T08:04:44.2114997Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-07-17T08:04:44.2115483Z or your builds will no longer be supported. 2025-07-17T08:04:44.2115723Z 2025-07-17T08:04:44.2116035Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-07-17T08:04:44.2116568Z ******************************************************************************** 2025-07-17T08:04:44.2116817Z 2025-07-17T08:04:44.2116899Z !! 2025-07-17T08:04:44.2117114Z self.initialize_options() 2025-07-17T08:04:44.2248907Z running build 2025-07-17T08:04:44.2249288Z running build_py 2025-07-17T08:04:44.2338471Z creating build/lib.linux-x86_64-cpython-313/torch_openreg 2025-07-17T08:04:44.2340120Z copying torch_openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg 2025-07-17T08:04:44.2342468Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-07-17T08:04:44.2344031Z copying torch_openreg/openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-07-17T08:04:44.2345589Z copying torch_openreg/openreg/random.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-07-17T08:04:44.2350944Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:44.2352227Z copying torch_openreg/lib/libopenreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:44.2365854Z copying torch_openreg/lib/libtorch_openreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:44.2485331Z copying torch_openreg/lib/libtorch_bindings.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-07-17T08:04:44.2523883Z running build_ext 2025-07-17T08:04:44.2626116Z building 'torch_openreg._C' extension 2025-07-17T08:04:44.2627966Z creating build/temp.linux-x86_64-cpython-313/torch_openreg/csrc 2025-07-17T08:04:44.2631490Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/include/python3.13 -c torch_openreg/csrc/stub.c -o build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -g -Wall -Werror 2025-07-17T08:04:44.3546001Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -L/var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/torch_openreg/lib -ltorch_bindings -o build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -Wl,-rpath,$ORIGIN/lib 2025-07-17T08:04:44.3784746Z running install_lib 2025-07-17T08:04:44.3886837Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libopenreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-07-17T08:04:44.3889414Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_openreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-07-17T08:04:44.3911764Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_bindings.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-07-17T08:04:44.3918532Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg 2025-07-17T08:04:44.3924166Z running install_egg_info 2025-07-17T08:04:44.4120663Z running egg_info 2025-07-17T08:04:44.4199833Z writing torch_openreg.egg-info/PKG-INFO 2025-07-17T08:04:44.4203742Z writing dependency_links to torch_openreg.egg-info/dependency_links.txt 2025-07-17T08:04:44.4206084Z writing requirements to torch_openreg.egg-info/requires.txt 2025-07-17T08:04:44.4207613Z writing top-level names to torch_openreg.egg-info/top_level.txt 2025-07-17T08:04:44.4294281Z reading manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-07-17T08:04:44.4303360Z writing manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-07-17T08:04:44.4305015Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg-0.0.1-py3.13.egg-info' (and everything under it) 2025-07-17T08:04:44.4306721Z Copying torch_openreg.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg-0.0.1-py3.13.egg-info 2025-07-17T08:04:44.4313428Z running install_scripts 2025-07-17T08:04:44.7092625Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:04:44.7097481Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_openreg.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:04:44.709360] 2025-07-17T08:04:56.9903333Z 2025-07-17T08:04:56.9904157Z test_openreg 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_openreg_1.1_4af4457a7d75d0de_.log 2025-07-17T08:04:56.9915814Z Running 41 items in this shard: test/test_openreg.py::TestPrivateUse1::test_backend_dispatchstub, test/test_openreg.py::TestPrivateUse1::test_backend_generate_methods, test/test_openreg.py::TestPrivateUse1::test_backend_module_function, test/test_openreg.py::TestPrivateUse1::test_backend_module_methods, test/test_openreg.py::TestPrivateUse1::test_backend_module_registration, test/test_openreg.py::TestPrivateUse1::test_backend_name, test/test_openreg.py::TestPrivateUse1::test_backend_operator_registration, test/test_openreg.py::TestPrivateUse1::test_backend_packed_sequence_methods, test/test_openreg.py::TestPrivateUse1::test_backend_storage_methods, test/test_openreg.py::TestPrivateUse1::test_backend_tensor_methods, test/test_openreg.py::TestPrivateUse1::test_backend_tensor_type, test/test_openreg.py::TestPrivateUse1::test_backend_type_methods, test/test_openreg.py::TestOpenReg::test_autograd_init, test/test_openreg.py::TestOpenReg::test_compile_autograd_function_aliasing, test/test_openreg.py::TestOpenReg::test_compile_autograd_function_returns_self, test/test_openreg.py::TestOpenReg::test_copy_same_device, test/test_openreg.py::TestOpenReg::test_cross_device_copy, test/test_openreg.py::TestOpenReg::test_cross_diff_devices_copy, test/test_openreg.py::TestOpenReg::test_data_dependent_output, test/test_openreg.py::TestOpenReg::test_event_elapsed_time, test/test_openreg.py::TestOpenReg::test_event_wait_stream, test/test_openreg.py::TestOpenReg::test_expand, test/test_openreg.py::TestOpenReg::test_factory, test/test_openreg.py::TestOpenReg::test_fake_tensor, test/test_openreg.py::TestOpenReg::test_generator, test/test_openreg.py::TestOpenReg::test_manual_seed, test/test_openreg.py::TestOpenReg::test_named_tensor, test/test_openreg.py::TestOpenReg::test_open_device_cpu_serialization, test/test_openreg.py::TestOpenReg::test_open_device_dlpack, test/test_openreg.py::TestOpenReg::test_open_device_numpy_serialization, test/test_openreg.py::TestOpenReg::test_pin_memory, test/test_openreg.py::TestOpenReg::test_printing, test/test_openreg.py::TestOpenReg::test_quantize, test/test_openreg.py::TestOpenReg::test_record_event, test/test_openreg.py::TestOpenReg::test_resize, test/test_openreg.py::TestOpenReg::test_rewrapped_storage, test/test_openreg.py::TestOpenReg::test_rng_state, test/test_openreg.py::TestOpenReg::test_serialization, test/test_openreg.py::TestOpenReg::test_stream_synchronize, test/test_openreg.py::TestOpenReg::test_stream_wait_event, test/test_openreg.py::TestOpenReg::test_stream_wait_stream 2025-07-17T08:04:56.9926689Z 2025-07-17T08:04:56.9926849Z Running test_fx 1/1 ... [2025-07-17 08:04:56.990621] 2025-07-17T08:04:56.9927280Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:04:56.9928283Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:04:56.990989] 2025-07-17T08:10:28.9753263Z 2025-07-17T08:10:28.9754413Z test_fx 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_1.1_d66539681e36cd0b_.log 2025-07-17T08:10:29.0247155Z Running 1259 items in this shard: test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationInput_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationMetadata_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationTorchTensorCall_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_Mutation_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_ReturnList_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_TakeList_cpu, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_FactoryFunctionCall_cpu, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_MutationFactory_cpu, test/test_fx.py::TestCSEPass::test_banned_list, test/test_fx.py::TestCSEPass::test_empty, test/test_fx.py::TestCSEPass::test_immutable_list_multiple_entries, test/test_fx.py::TestCSEPass::test_immutable_list_type, test/test_fx.py::TestCSEPass::test_kwarg, test/test_fx.py::TestCSEPass::test_nested_immutable_list_type, test/test_fx.py::TestCSEPass::test_nochange, test/test_fx.py::TestCSEPass::test_rand_like, test/test_fx.py::TestCSEPass::test_rand_n, test/test_fx.py::TestCSEPass::test_random, test/test_fx.py::TestCSEPass::test_simple, test/test_fx.py::TestCSEPass::test_simple_2, test/test_fx.py::TestCSEPass::test_simple_multiple_same_ops, test/test_fx.py::TestCSEPass::test_two_args, test/test_fx.py::TestCSEPass::test_two_args_default, test/test_fx.py::TestDCE::test_dead_chain, test/test_fx.py::TestDCE::test_dead_getattr, test/test_fx.py::TestDCE::test_dead_placeholder, test/test_fx.py::TestDCE::test_dead_placeholder_with_user, test/test_fx.py::TestDCE::test_impure_custom, test/test_fx.py::TestDCE::test_impure_kwargs, test/test_fx.py::TestDCE::test_impure_nodes_args, test/test_fx.py::TestDCE::test_impure_random, test/test_fx.py::TestDCE::test_keep_collectives, test/test_fx.py::TestDCE::test_keep_collectives_no_overload, test/test_fx.py::TestDCE::test_keep_module_with_side_effects, test/test_fx.py::TestDCE::test_keep_setitem, test/test_fx.py::TestDCE::test_keep_torch_assert, test/test_fx.py::TestDCE::test_simple, test/test_fx.py::TestConstFold::test_check_inline_non_const, test/test_fx.py::TestConstFold::test_check_inline_non_const_mult_return, test/test_fx.py::TestConstFold::test_check_skip_folding_quant_dequant_pattern, test/test_fx.py::TestConstFold::test_const_fold_basic_one_attr_name_collision, test/test_fx.py::TestConstFold::test_const_fold_basic_one_attr_no_name_collision, test/test_fx.py::TestConstFold::test_const_fold_basic_placeholder_reordered, test/test_fx.py::TestConstFold::test_const_fold_basic_two_attr, test/test_fx.py::TestConstFold::test_const_fold_basic_two_attr_three_input, test/test_fx.py::TestConstFold::test_const_fold_has_inlined_call_module_node, test/test_fx.py::TestConstFold::test_const_fold_module_attr, test/test_fx.py::TestConstFold::test_const_fold_multi_const_folded_attrs, test/test_fx.py::TestConstFold::test_const_fold_noop, test/test_fx.py::TestConstFold::test_const_fold_submod_hierarchy, test/test_fx.py::TestConstFold::test_const_fold_tensor_meta, test/test_fx.py::TestConstFold::test_const_fold_unused_placeholder, test/test_fx.py::TestConstFold::test_dict_output, test/test_fx.py::TestConstFold::test_fold_module, test/test_fx.py::TestConstFold::test_retain_node_meta, test/test_fx.py::TestConstFold::test_three_outputs, test/test_fx.py::TestConstFold::test_two_outputs, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_dim_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_ndim_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_nelement_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_numel_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_shape_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_size_const, test/test_fx.py::AnnotationsTest::test_annotate, test/test_fx.py::AnnotationsTest::test_annotations, test/test_fx.py::AnnotationsTest::test_broadcasting1, test/test_fx.py::AnnotationsTest::test_broadcasting2, test/test_fx.py::AnnotationsTest::test_broadcasting3, test/test_fx.py::AnnotationsTest::test_consistency, test/test_fx.py::AnnotationsTest::test_precision, test/test_fx.py::TypeCheckerTest::test_flatten_fully_static, test/test_fx.py::TypeCheckerTest::test_resnet50, test/test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast, test/test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast_2, test/test_fx.py::TypeCheckerTest::test_type_check_add_false, test/test_fx.py::TypeCheckerTest::test_type_check_add_true, test/test_fx.py::TypeCheckerTest::test_type_check_add_with_broadcast, test/test_fx.py::TypeCheckerTest::test_type_check_add_with_scalar, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_broadcast, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_false, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_symbolic, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_2, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_2_fully_static, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_maxpool2d_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_types, test/test_fx.py::TypeCheckerTest::test_type_check_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_flatten3, test/test_fx.py::TypeCheckerTest::test_type_check_flatten_2, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true_param_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_true, test/test_fx.py::TypeCheckerTest::test_type_check_symbolic_inferenceconv2D_maxpool2d_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_transpose_False, test/test_fx.py::TypeCheckerTest::test_type_check_transpose_true, test/test_fx.py::TypeCheckerTest::test_type_maxpool2d_fully_static, test/test_fx.py::TypeCheckerTest::test_type_typechecl_maxpool2d_3dinput, test/test_fx.py::TypeCheckerTest::test_typecheck_basicblock, test/test_fx.py::TestMatcher::test_matcher_with_name_node_map_function, test/test_fx.py::TestMatcher::test_matcher_with_name_node_map_module, test/test_fx.py::TestMatcher::test_split_to_graph_and_name_node_map, test/test_fx.py::TestMatcher::test_subgraph_matcher_ignore_literals, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_attributes, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_list, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_list_bad, test/test_fx.py::TestMatcher::test_variatic_arg_matching, test/test_fx.py::TestPassManager::test_pass_manager, test/test_fx.py::TestPassManager::test_pass_manager_bad_checks, test/test_fx.py::TestPassManager::test_pass_manager_checks, test/test_fx.py::TestPassManager::test_pass_manager_error, test/test_fx.py::TestPassManager::test_this_before_that_pass_constraint, test/test_fx.py::TestPassManager::test_topological_sort, test/test_fx.py::TestSourceMatcher::test_legalize_slice, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_True, test/test_fx.py::TestSubgraphRewriter::test_matching_pattern_with_list_type_arg, test/test_fx.py::TestSubgraphRewriter::test_matching_variable_arguments, test/test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_callback, test/test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_filters, test/test_fx.py::TestSubgraphRewriter::test_replaced_nodes, test/test_fx.py::TestSubgraphRewriter::test_replacement_with_attrs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_annotations_int, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_call_method, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_correct_output_replacement, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_graph_argument_order, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_internal_pattern_nodes_cannot_have_users_that_are_not_matched, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_local_revert, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_multiple_pattern_match, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_nodes_with_kwargs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_is_entire_graph, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_output_pattern_node_can_have_users_that_are_not_matched, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_placeholder_matching, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_preserves_logic, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_consecutive_submodules, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_duplicated_outputs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_multiple_outputs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replaces_referenced_submodules, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_single_pattern_match, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_traced_as_callable, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_oneliner_pattern, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_overlapping_matches, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_trivial_replacement, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_args, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_results, test/test_fx.py::TestFX::test_all_input_nodes, test/test_fx.py::TestFX::test_annotation_with_future, test/test_fx.py::TestFX::test_annotations_empty_tuple, test/test_fx.py::TestFX::test_annotations_with_forward_references, test/test_fx.py::TestFX::test_annotations_with_no_forward_references, test/test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_internal_forward_references, test/test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_no_internal_forward_references, test/test_fx.py::TestFX::test_args_kwargs, test/test_fx.py::TestFX::test_args_kwargs_no_self, test/test_fx.py::TestFX::test_assert, test/test_fx.py::TestFX::test_ast_rewriter_reassigns_submodules, test/test_fx.py::TestFX::test_ast_rewriter_rewrites_assert, test/test_fx.py::TestFX::test_ast_rewriter_rewrites_assert_with_message, test/test_fx.py::TestFX::test_ast_rewriter_wrap, test/test_fx.py::TestFX::test_ast_rewriter_wrap_fn_directly, test/test_fx.py::TestFX::test_ast_rewriter_wrap_with_submodule, test/test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator, test/test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator_and_transformed, test/test_fx.py::TestFX::test_autowrap_functions, test/test_fx.py::TestFX::test_concrete_arg_none_assert, test/test_fx.py::TestFX::test_construct_root_dict, test/test_fx.py::TestFX::test_control_flow_tracing, test/test_fx.py::TestFX::test_copy_it, test/test_fx.py::TestFX::test_copy_no_remap, test/test_fx.py::TestFX::test_ctx_mgr, test/test_fx.py::TestFX::test_custom_codegen, test/test_fx.py::TestFX::test_custom_codegen_with_transformer, test/test_fx.py::TestFX::test_custom_import, test/test_fx.py::TestFX::test_custom_proxy_dynamic_value, test/test_fx.py::TestFX::test_custom_proxy_input_dependent_control_flow, test/test_fx.py::TestFX::test_custom_proxy_type, test/test_fx.py::TestFX::test_custom_proxy_type_literal, test/test_fx.py::TestFX::test_custom_traceback_not_raised_when_exception_source_is_submodule, test/test_fx.py::TestFX::test_custom_traceback_raised_when_exception_source_is_graphmodule, test/test_fx.py::TestFX::test_deepcopy_graph_with_tracer_cls, test/test_fx.py::TestFX::test_deepcopy_graphmodule, test/test_fx.py::TestFX::test_deepcopy_graphmodule_with_transform, test/test_fx.py::TestFX::test_deepcopy_no_recursion, test/test_fx.py::TestFX::test_deepcopy_recursion_depth, test/test_fx.py::TestFX::test_deepcopy_tracer, test/test_fx.py::TestFX::test_deepcopy_with_submods_params, test/test_fx.py::TestFX::test_delete_unused_submodules_leaf, test/test_fx.py::TestFX::test_delete_unused_values, test/test_fx.py::TestFX::test_dict, test/test_fx.py::TestFX::test_direct_param_use, test/test_fx.py::TestFX::test_disallow_override, test/test_fx.py::TestFX::test_ellipsis, test/test_fx.py::TestFX::test_empty_graph_codegen, test/test_fx.py::TestFX::test_enum, test/test_fx.py::TestFX::test_erase_node_error, test/test_fx.py::TestFX::test_example_shape_prop, test/test_fx.py::TestFX::test_find_uses, test/test_fx.py::TestFX::test_fn_type_annotation_empty, test/test_fx.py::TestFX::test_fn_type_annotations, test/test_fx.py::TestFX::test_fx_and_or, test/test_fx.py::TestFX::test_fx_create_arg, test/test_fx.py::TestFX::test_fx_shifts, test/test_fx.py::TestFX::test_fx_stateless, test/test_fx.py::TestFX::test_get_torch_func_signature, test/test_fx.py::TestFX::test_getitem, test/test_fx.py::TestFX::test_getitem_subproc, test/test_fx.py::TestFX::test_graph_edit_with_proxy, test/test_fx.py::TestFX::test_graph_fns, test/test_fx.py::TestFX::test_graph_module, test/test_fx.py::TestFX::test_graph_module_init_buffer_param_copied_dict_init, test/test_fx.py::TestFX::test_graph_module_init_buffer_param_copied_mod_init, test/test_fx.py::TestFX::test_graph_module_replicate_for_dp, test/test_fx.py::TestFX::test_graph_unique_names, test/test_fx.py::TestFX::test_graph_unique_names_manual, test/test_fx.py::TestFX::test_immutable_dict_pytree_ops, test/test_fx.py::TestFX::test_immutable_list_pytree_ops, test/test_fx.py::TestFX::test_imul_code_print, test/test_fx.py::TestFX::test_inf_nan, test/test_fx.py::TestFX::test_inf_nan_kwds, test/test_fx.py::TestFX::test_informative_co_filename, test/test_fx.py::TestFX::test_inline_graph, test/test_fx.py::TestFX::test_insert_arg, test/test_fx.py::TestFX::test_insertion_point, test/test_fx.py::TestFX::test_interpreter, test/test_fx.py::TestFX::test_interpreter_default_args, test/test_fx.py::TestFX::test_interpreter_gc_values, test/test_fx.py::TestFX::test_interpreter_noop_resnet18, test/test_fx.py::TestFX::test_interpreter_not_enough_args, test/test_fx.py::TestFX::test_interpreter_onthefly_swap, test/test_fx.py::TestFX::test_interpreter_other_graph, test/test_fx.py::TestFX::test_interpreter_partial_eval, test/test_fx.py::TestFX::test_interpreter_run_node_override, test/test_fx.py::TestFX::test_interpreter_star_args, test/test_fx.py::TestFX::test_interpreter_with_codegen, test/test_fx.py::TestFX::test_layout, test/test_fx.py::TestFX::test_leaf_module, test/test_fx.py::TestFX::test_lineno_map, test/test_fx.py::TestFX::test_matmul_tracing, test/test_fx.py::TestFX::test_metadata_on_ph, test/test_fx.py::TestFX::test_module_deepcopy_edit_nodes, test/test_fx.py::TestFX::test_move_before, test/test_fx.py::TestFX::test_multi_insert_point, test/test_fx.py::TestFX::test_multiple_default_args, test/test_fx.py::TestFX::test_named_tuple_inlined, test/test_fx.py::TestFX::test_namedtuple_return_qualname, test/test_fx.py::TestFX::test_namedtuple_return_trace, test/test_fx.py::TestFX::test_native_callable, test/test_fx.py::TestFX::test_nn_module_stack, test/test_fx.py::TestFX::test_no_mutation, test/test_fx.py::TestFX::test_node_tagging, test/test_fx.py::TestFX::test_nonetype_annotation, test/test_fx.py::TestFX::test_partial_trace, test/test_fx.py::TestFX::test_pickle_custom_import, test/test_fx.py::TestFX::test_pickle_graphmodule, test/test_fx.py::TestFX::test_pickle_nonetype_annotation, test/test_fx.py::TestFX::test_pickle_torch_custom_ops, test/test_fx.py::TestFX::test_prepend_self, test/test_fx.py::TestFX::test_pretty_print, test/test_fx.py::TestFX::test_pretty_print_graph, test/test_fx.py::TestFX::test_pretty_print_node, test/test_fx.py::TestFX::test_pretty_print_targets, test/test_fx.py::TestFX::test_print_graph, test/test_fx.py::TestFX::test_profiler_ranges_side_effect, test/test_fx.py::TestFX::test_proxy_deepcopy_with_tracer, test/test_fx.py::TestFX::test_proxy_deepcopy_without_tracer, test/test_fx.py::TestFX::test_pytree, test/test_fx.py::TestFX::test_pytree_concrete, test/test_fx.py::TestFX::test_reassign_args_kwargs_uses, test/test_fx.py::TestFX::test_regular_and_default_args, test/test_fx.py::TestFX::test_remove_uses, test/test_fx.py::TestFX::test_remove_uses_with_custom_filter, test/test_fx.py::TestFX::test_replace_input, test/test_fx.py::TestFX::test_replace_uses, test/test_fx.py::TestFX::test_reserved_getattr, test/test_fx.py::TestFX::test_return_tuple, test/test_fx.py::TestFX::test_return_type_exists, test/test_fx.py::TestFX::test_return_type_exists_pre_pep585, test/test_fx.py::TestFX::test_script_method_trace, test/test_fx.py::TestFX::test_script_tensor_constant, test/test_fx.py::TestFX::test_sequential, test/test_fx.py::TestFX::test_shape_prop_aggregate, test/test_fx.py::TestFX::test_shape_prop_layout, test/test_fx.py::TestFX::test_shape_prop_layout_3d, test/test_fx.py::TestFX::test_shape_prop_unbacked_sym, test/test_fx.py::TestFX::test_single_default_arg, test/test_fx.py::TestFX::test_snake_case, test/test_fx.py::TestFX::test_sqrt, test/test_fx.py::TestFX::test_stack_traces, test/test_fx.py::TestFX::test_stack_traces_with_transformer, test/test_fx.py::TestFX::test_string_literal_return, test/test_fx.py::TestFX::test_submodule_manipulation_API, test/test_fx.py::TestFX::test_symbolic_trace_assert, test/test_fx.py::TestFX::test_symbolic_trace_sequential, test/test_fx.py::TestFX::test_tensor_attribute, test/test_fx.py::TestFX::test_tensor_attribute_coalseced, test/test_fx.py::TestFX::test_tensor_constant, test/test_fx.py::TestFX::test_throw_out_variant, test/test_fx.py::TestFX::test_torch_custom_ops, test/test_fx.py::TestFX::test_torch_fx_getattr, test/test_fx.py::TestFX::test_torch_fx_len, test/test_fx.py::TestFX::test_torch_op_overloads, test/test_fx.py::TestFX::test_torchbind_class_attribute_in_fx, test/test_fx.py::TestFX::test_torchbind_class_attribute_in_fx_tensor_arg, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_dict_int_keys, test/test_fx.py::TestFX::test_trace_dict_proxy_keys, test/test_fx.py::TestFX::test_trace_fn_constant, test/test_fx.py::TestFX::test_trace_function, test/test_fx.py::TestFX::test_trace_multiple_funcs, test/test_fx.py::TestFX::test_trace_return_dataclass, test/test_fx.py::TestFX::test_trace_return_dataclass_nested, test/test_fx.py::TestFX::test_trace_return_namedtuple, test/test_fx.py::TestFX::test_tracing_graphmodules_as_leaf_submodules, test/test_fx.py::TestFX::test_transformer_multi_outputs, test/test_fx.py::TestFX::test_transformer_noop, test/test_fx.py::TestFX::test_transformer_op_swap, test/test_fx.py::TestFX::test_transformer_preserves_nn_module_stack_for_get_attr, test/test_fx.py::TestFX::test_tuple_no_subscript, test/test_fx.py::TestFX::test_typename_print, test/test_fx.py::TestFX::test_typename_print_pre_pep585, test/test_fx.py::TestFX::test_unpack, test/test_fx.py::TestFX::test_unpack_dict_better_error, test/test_fx.py::TestFX::test_unpack_list_better_error, test/test_fx.py::TestFX::test_update_args_api, test/test_fx.py::TestFX::test_update_args_kwargs_yells_at_you, test/test_fx.py::TestFX::test_update_kwargs_api, test/test_fx.py::TestFX::test_user_friendly_call_provenance_with_function, test/test_fx.py::TestFX::test_user_friendly_call_provenance_with_module, test/test_fx.py::TestFX::test_varargs_concrete, test/test_fx.py::TestFX::test_wrap, test/test_fx.py::TestFX::test_wrap_decorated_function, test/test_fx.py::TestFX::test_wrap_fn_directly, test/test_fx.py::TestFX::test_wrap_with_submodule, test/test_fx.py::TestFX::test_wrapped_method, test/test_fx.py::TestFX::test_wrapped_retrace, test/test_fx.py::TestFX::test_wrapped_via_decorator, test/test_fx.py::TestFX::test_wrapped_via_decorator_and_transformed, test/test_fx.py::TestFX::test_wrong_target_type, test/test_fx.py::TestFX::test_wrong_topo, test/test_fx.py::TestFXAPIBackwardCompatibility::test_adding_side_effect_function, test/test_fx.py::TestFXAPIBackwardCompatibility::test_class_member_back_compat, test/test_fx.py::TestFXAPIBackwardCompatibility::test_function_back_compat, test/test_fx.py::TestFXAPIBackwardCompatibility::test_preserve_unused_attr_after_unpickle, test/test_fx.py::TestFXAPIBackwardCompatibility::test_public_api_surface, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_affine_grid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_alpha_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_batch_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_bilinear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy, test/test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy_with_logits, test/test_fx.py::TestFunctionalTracing::test_nn_functional_celu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_celu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_channel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_tbc, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_embedding_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_similarity, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cross_entropy, test/test_fx.py::TestFunctionalTracing::test_nn_functional_ctc_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_elu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_elu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_embedding, test/test_fx.py::TestFunctionalTracing::test_nn_functional_embedding_bag, test/test_fx.py::TestFunctionalTracing::test_nn_functional_feature_alpha_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gaussian_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_glu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_grid_sample, test/test_fx.py::TestFunctionalTracing::test_nn_functional_group_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gumbel_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardshrink, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardsigmoid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardswish, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hinge_embedding_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_huber_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_instance_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_interpolate, test/test_fx.py::TestFunctionalTracing::test_nn_functional_kl_div, test/test_fx.py::TestFunctionalTracing::test_nn_functional_l1_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_layer_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_linear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_local_response_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_log_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_logsigmoid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_margin_ranking_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_mish, test/test_fx.py::TestFunctionalTracing::test_nn_functional_mse_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multi_head_attention_forward, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multi_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_soft_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_native_channel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_normalize, test/test_fx.py::TestFunctionalTracing::test_nn_functional_one_hot, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pad, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pairwise_distance, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pdist, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_unshuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_poisson_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_prelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu6, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rms_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_scaled_dot_product_attention, test/test_fx.py::TestFunctionalTracing::test_nn_functional_selu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_selu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_silu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_smooth_l1_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_soft_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softmin, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softplus, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softshrink, test/test_fx.py::TestFunctionalTracing::test_nn_functional_threshold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_threshold_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_with_distance_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_unfold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_bilinear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_nearest, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_H_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_T_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___getitem___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___radd___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rdiv___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmatmul___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmod___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmul___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rpow___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rsub___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__batch_norm_with_update_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__chunk_cat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__native_batch_norm_legit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__segment_reduce_lengths_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__segment_reduce_offsets_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__softmax_backward_data_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__unsafe_masked_index_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__unsafe_masked_index_put_accumulate_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__upsample_bilinear2d_aa_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_abs_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_acos_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_acosh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addbmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addcdiv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addcmul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmm_decomposed_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_alias_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_all_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_allclose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_aminmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_angle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_any_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_arange_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argsort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argwhere_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_partial_views_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_asin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_asinh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atan2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_baddbmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bernoulli_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bfloat16_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_block_diag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bool_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_shapes_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_to_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bucketize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_byte_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cartesian_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cauchy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cdist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cdouble_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ceil_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cfloat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_chalf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_char_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_inverse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_chunk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_max_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_min_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clone_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_column_stack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_combinations_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_complex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_conj_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_conj_physical_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_constant_pad_nd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_contiguous_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_copysign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_corrcoef_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cos_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cosh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_count_nonzero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cov_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cross_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cummax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cummin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumprod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumulative_trapezoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_deg2rad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diag_embed_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagflat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diff_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_digamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_floor_rounding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_no_rounding_mode_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_trunc_rounding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_double_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_einsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_permuted_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_eq_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_equal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erfc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erfinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exp2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expm1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exponential_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_eye_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fftshift_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifftshift_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flatten_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flip_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fliplr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flipud_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_float_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_float_power_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_floor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_floor_divide_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_frac_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_frexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_full_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_full_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gather_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ge_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_geometric_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_geqrf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gradient_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_grid_sampler_2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_half_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_heaviside_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histogram_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histogramdd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hypot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_i0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_igamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_igammac_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_put_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_inner_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_int_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isclose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isfinite_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isinf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isnan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isneginf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isposinf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isreal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_item_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_2inputs_2outputs_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_4inputs_with_extra_args_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_binary_return_by_ref_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_unary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_kron_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_kthvalue_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ldexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_le_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lerp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lgamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cholesky_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cholesky_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cond_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cross_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_det_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_diagonal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eig_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigvals_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigvalsh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_householder_product_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_inv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_inv_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lstsq_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lstsq_grad_oriented_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_factor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_factor_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_power_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_hermitian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_multi_dot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_norm_subgradients_at_zero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_hermitian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_singular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_qr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_slogdet_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_triangular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_svd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_svdvals_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_tensorinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_tensorsolve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vander_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vecdot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vector_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linspace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linspace_tensor_overload_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log10_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log1p_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_normal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_softmax_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logaddexp2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logaddexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logcumsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logdet_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_and_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_not_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_or_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_xor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logspace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logspace_tensor_overload_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_long_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_unpack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mH_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mT_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_argmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_argmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_cumprod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_cumsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_log_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_logaddexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_logsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_median_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_normalize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_softmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_std_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_var_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_matmul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_matrix_exp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_pool2d_with_indices_backward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_reduction_no_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_reduction_with_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_maximum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_median_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_meshgrid_list_of_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_meshgrid_variadic_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_reduction_no_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_reduction_with_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_minimum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mode_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_movedim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_msort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_multinomial_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nan_to_num_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanmean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanmedian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanquantile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nansum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_narrow_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_narrow_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_batch_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_dropout_backward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_layer_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ne_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_neg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_empty_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_empty_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_full_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_ones_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_zeros_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nextafter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_alpha_dropout_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_batch_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_binary_cross_entropy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_celu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_channel_shuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cosine_embedding_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cosine_similarity_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cross_entropy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_ctc_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_elu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_embedding_bag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_embedding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_fractional_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_fractional_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_gaussian_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_gelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_glu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_grid_sample_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_group_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardsigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardswish_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardtanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hinge_embedding_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_huber_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_instance_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_area_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_bicubic_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_linear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_nearest_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_trilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_kl_div_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_l1_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_layer_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_leaky_relu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_linear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_local_response_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_logsigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_margin_ranking_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool1d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool2d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool3d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_mish_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_mse_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multi_head_attention_forward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multi_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multilabel_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_normalize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_circular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_constant_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_reflect_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_replicate_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_replicate_negative_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pairwise_distance_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pdist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pixel_shuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pixel_unshuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_poisson_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_prelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_relu6_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_relu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_rms_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_rrelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_selu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_silu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_smooth_l1_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_soft_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softmin_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softplus_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softsign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_tanhshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_threshold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_triplet_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_unfold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_upsample_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_upsample_nearest_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nonzero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nonzero_static_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_fro_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_inf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_nuc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_in_place_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_number_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ones_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ones_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ormqr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_outer_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pca_lowrank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_permute_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_permute_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pinverse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polar_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_4_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_positive_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pow_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_put_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_qr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_quantile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rad2deg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rand_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randint_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randint_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randn_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ravel_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_real_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reciprocal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_remainder_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_renorm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_repeat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_repeat_interleave_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reshape_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reshape_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resize__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resize_as__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resolve_conj_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resolve_neg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_roll_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rot90_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_neg_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rsqrt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rsub_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scalar_tensor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_searchsorted_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_select_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sgn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_short_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_bartlett_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_blackman_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_cosine_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_exponential_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_gaussian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_general_cosine_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_general_hamming_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_hamming_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_hann_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_kaiser_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_nuttall_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signbit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sinc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sinh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_slice_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_slice_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_softmax_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sparse_mm_reduce_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sparse_sampled_addmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_airy_ai_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_j0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_j1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_y0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_y1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_u_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_v_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_w_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_entr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_erfcx_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_hermite_polynomial_h_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_hermite_polynomial_he_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i0e_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i1e_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_laguerre_polynomial_l_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_legendre_polynomial_p_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_log_ndtr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_i0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_i1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_k0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_k1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_ndtr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_ndtri_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_scaled_modified_bessel_k0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_scaled_modified_bessel_k1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_spherical_bessel_j0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_xlog1py_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_zeta_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_list_args_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_with_sizes_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_with_sizes_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sqrt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_square_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_multiple_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_stack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_mean_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_stft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sub_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sum_to_size_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_svd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_svd_lowrank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_t_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_take_along_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_take_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tensor_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tensordot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_to_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_to_sparse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_topk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_transpose_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_transpose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trapezoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trapz_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_triangular_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tril_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_triu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_true_divide_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trunc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unbind_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unbind_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unflatten_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unfold_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unfold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_uniform_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unique_consecutive_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unique_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsafe_chunk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsafe_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsqueeze_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsqueeze_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_mean_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vdot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_as_complex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_where_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_xlogy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zero__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zeros_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zeros_like_cpu_float32, test/test_fx.py::TestVisionTracing::test_torchvision_models_alexnet, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_base, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_small, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_tiny, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet121, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet161, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet169, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet201, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_mobilenet_v3_large_320_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_mobilenet_v3_large_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fcos_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_keypointrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_maskrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_maskrcnn_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_retinanet_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_retinanet_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_ssd300_vgg16, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_ssdlite320_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b0, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b1, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b2, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b3, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b4, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b5, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b6, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_l, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_m, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_googlenet, test/test_fx.py::TestVisionTracing::test_torchvision_models_inception_v3, test/test_fx.py::TestVisionTracing::test_torchvision_models_maxvit_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet0_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet0_75, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet1_3, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v3_small, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_16gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_1_6gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_32gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_3_2gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_400mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_800mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_8gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_128gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_16gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_1_6gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_32gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_3_2gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_400mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_800mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_8gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet152, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet18, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet34, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext101_32x8d, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext101_64x4d, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext50_32x4d, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_fcn_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_fcn_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_lraspp_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x0_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x1_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x2_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_squeezenet1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_squeezenet1_1, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg11, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg11_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg13, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg13_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg16_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg19, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg19_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mc3_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mvit_v1_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mvit_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_r2plus1d_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_r3d_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_s3d, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_b_16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_b_32, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_h_14, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_l_16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_l_32, test/test_fx.py::TestVisionTracing::test_torchvision_models_wide_resnet101_2, test/test_fx.py::TestVisionTracing::test_torchvision_models_wide_resnet50_2 2025-07-17T08:10:29.0726747Z 2025-07-17T08:10:29.0727058Z Running dynamo/test_activation_checkpointing 1/1 ... [2025-07-17 08:10:28.977448] 2025-07-17T08:10:29.0727579Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:10:29.0728785Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_activation_checkpointing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:10:28.977797] 2025-07-17T08:10:35.4174575Z 2025-07-17T08:10:35.4175734Z dynamo/test_activation_checkpointing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_activation_checkpointing_1.1_a604c30de6a552c7_.log 2025-07-17T08:10:35.4176622Z 2025-07-17T08:10:35.4178078Z Running dynamo/test_precompile_context 1/1 ... [2025-07-17 08:10:35.417640] 2025-07-17T08:10:35.4178578Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:10:35.4182323Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_precompile_context.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:10:35.417946] 2025-07-17T08:10:41.7833991Z 2025-07-17T08:10:41.7835347Z dynamo/test_precompile_context 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_precompile_context_1.1_b36be6b66f3f1cd6_.log 2025-07-17T08:10:41.7836134Z 2025-07-17T08:10:41.7837651Z Running test_quantization 9/9 ... [2025-07-17 08:10:41.783567] 2025-07-17T08:10:41.7838329Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:10:41.7841853Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_quantization.py', '-m', 'serial', '--shard-id=9', '--num-shards=9', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:10:41.783913] 2025-07-17T08:10:46.5545637Z 2025-07-17T08:10:46.5546757Z test_quantization 9/9 was successful, full logs can be found in artifacts with path test/test-reports/test_quantization_9.9_2f4b2854844ada99_.log 2025-07-17T08:10:46.5547523Z Running 0 items in this shard: 2025-07-17T08:10:46.5547740Z 2025-07-17T08:10:46.5549844Z Running test_linalg 4/5 ... [2025-07-17 08:10:46.554814] 2025-07-17T08:10:46.5550498Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:10:46.5554563Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_linalg.py', '-m', 'serial', '--shard-id=4', '--num-shards=5', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:10:46.555170] 2025-07-17T08:10:53.0283222Z 2025-07-17T08:10:53.0284436Z test_linalg 4/5 was successful, full logs can be found in artifacts with path test/test-reports/test_linalg_4.5_5f508e6de2f3b80e_.log 2025-07-17T08:10:53.0285680Z Running 2 items in this shard: test/test_linalg.py::TestLinalgCPU::test_svd_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_svd_cpu_float64 2025-07-17T08:10:53.0286572Z 2025-07-17T08:10:53.0287146Z Running test_linalg 5/5 ... [2025-07-17 08:10:53.028554] 2025-07-17T08:10:53.0287828Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:10:53.0291670Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_linalg.py', '-m', 'serial', '--shard-id=5', '--num-shards=5', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:10:53.028889] 2025-07-17T08:10:56.6982746Z 2025-07-17T08:10:56.6983594Z test_linalg 5/5 was successful, full logs can be found in artifacts with path test/test-reports/test_linalg_5.5_46ea4514bf345580_.log 2025-07-17T08:10:56.6984297Z Running 0 items in this shard: 2025-07-17T08:10:56.6984502Z 2025-07-17T08:10:56.6987188Z Running dynamo/cpython/3_13/test_list 1/1 ... [2025-07-17 08:10:56.698494] 2025-07-17T08:10:56.6987696Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:10:56.6990516Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_list.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:10:56.698833] 2025-07-17T08:10:59.8176209Z 2025-07-17T08:10:59.8177449Z dynamo/cpython/3_13/test_list 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_list_1.1_d3b53e3bc1bf15b5_.log 2025-07-17T08:10:59.8178391Z Running 0 items in this shard: 2025-07-17T08:10:59.8178650Z 2025-07-17T08:10:59.8179212Z Running functorch/test_vmap 1/4 ... [2025-07-17 08:10:59.817735] 2025-07-17T08:10:59.8179994Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:10:59.8183903Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_vmap.py', '-m', 'serial', '--shard-id=1', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:10:59.818117] 2025-07-17T08:11:04.4390616Z 2025-07-17T08:11:04.4391951Z functorch/test_vmap 1/4 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_1.4_68405797e3c90819_.log 2025-07-17T08:11:04.4393184Z Running 0 items in this shard: 2025-07-17T08:11:04.4393388Z 2025-07-17T08:11:04.4393582Z Running test_nestedtensor 1/1 ... [2025-07-17 08:11:04.439106] 2025-07-17T08:11:04.4393993Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:04.4396929Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_nestedtensor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:04.439447] 2025-07-17T08:11:09.7611218Z 2025-07-17T08:11:09.7612628Z test_nestedtensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_nestedtensor_1.1_e56a3bc82f5c718d_.log 2025-07-17T08:11:09.7613881Z Running 1 items in this shard: test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_linear_backward_memory_usage_cpu_float32 2025-07-17T08:11:09.7614589Z 2025-07-17T08:11:09.7614982Z Running test_binary_ufuncs 1/4 ... [2025-07-17 08:11:09.761306] 2025-07-17T08:11:09.7615545Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:09.7618850Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_binary_ufuncs.py', '-m', 'serial', '--shard-id=1', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:09.761647] 2025-07-17T08:11:15.8341252Z 2025-07-17T08:11:15.8342449Z test_binary_ufuncs 1/4 was successful, full logs can be found in artifacts with path test/test-reports/test_binary_ufuncs_1.4_e488f9751bcbd32c_.log 2025-07-17T08:11:15.8343236Z Running 0 items in this shard: 2025-07-17T08:11:15.8344718Z 2025-07-17T08:11:15.8344959Z Running test_binary_ufuncs 2/4 ... [2025-07-17 08:11:15.834326] 2025-07-17T08:11:15.8345385Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:15.8349161Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_binary_ufuncs.py', '-m', 'serial', '--shard-id=2', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:15.834669] 2025-07-17T08:11:21.9574660Z 2025-07-17T08:11:21.9575613Z test_binary_ufuncs 2/4 was successful, full logs can be found in artifacts with path test/test-reports/test_binary_ufuncs_2.4_0e02504ceb96c6af_.log 2025-07-17T08:11:21.9576549Z Running 0 items in this shard: 2025-07-17T08:11:21.9576741Z 2025-07-17T08:11:21.9577094Z Running test_foreach 1/1 ... [2025-07-17 08:11:21.957571] 2025-07-17T08:11:21.9577547Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:21.9581251Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_foreach.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:21.957909] 2025-07-17T08:11:30.1343022Z 2025-07-17T08:11:30.1343966Z test_foreach 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_foreach_1.1_3c61fcbe829f7aac_.log 2025-07-17T08:11:30.1344748Z Running 0 items in this shard: 2025-07-17T08:11:30.1344957Z 2025-07-17T08:11:30.1347324Z Running dynamo/cpython/3_13/test_generator_stop 1/1 ... [2025-07-17 08:11:30.134563] 2025-07-17T08:11:30.1347907Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:30.1352055Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_generator_stop.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:30.134934] 2025-07-17T08:11:33.2035149Z 2025-07-17T08:11:33.2036268Z dynamo/cpython/3_13/test_generator_stop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_generator_stop_1.1_f8c45a8ea0cdeda4_.log 2025-07-17T08:11:33.2037612Z Running 0 items in this shard: 2025-07-17T08:11:33.2037804Z 2025-07-17T08:11:33.2038558Z Running dynamo/cpython/3_13/test_exception_variations 1/1 ... [2025-07-17 08:11:33.203675] 2025-07-17T08:11:33.2039082Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:33.2042958Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_exception_variations.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:33.204048] 2025-07-17T08:11:36.2726954Z 2025-07-17T08:11:36.2728376Z dynamo/cpython/3_13/test_exception_variations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_exception_variations_1.1_1102d4663218f5e1_.log 2025-07-17T08:11:36.2729549Z Running 0 items in this shard: 2025-07-17T08:11:36.2729745Z 2025-07-17T08:11:36.2731273Z Running dynamo/cpython/3_13/test_int_literal 1/1 ... [2025-07-17 08:11:36.272916] 2025-07-17T08:11:36.2731830Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:36.2735049Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_int_literal.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:36.273251] 2025-07-17T08:11:39.3918142Z 2025-07-17T08:11:39.3919778Z dynamo/cpython/3_13/test_int_literal 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_int_literal_1.1_70a17a2ca98368c0_.log 2025-07-17T08:11:39.3921435Z Running 0 items in this shard: 2025-07-17T08:11:39.3921706Z 2025-07-17T08:11:39.3923725Z Running dynamo/cpython/3_13/test_with 1/1 ... [2025-07-17 08:11:39.392171] 2025-07-17T08:11:39.3924430Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:39.3929842Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_with.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:39.392650] 2025-07-17T08:11:42.5112324Z 2025-07-17T08:11:42.5113411Z dynamo/cpython/3_13/test_with 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_with_1.1_0044d5b8fef33dc1_.log 2025-07-17T08:11:42.5114395Z Running 0 items in this shard: 2025-07-17T08:11:42.5114601Z 2025-07-17T08:11:42.5116789Z Running dynamo/cpython/3_13/test_numeric_tower 1/1 ... [2025-07-17 08:11:42.511505] 2025-07-17T08:11:42.5117298Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:42.5121113Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_numeric_tower.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:42.511863] 2025-07-17T08:11:45.5803343Z 2025-07-17T08:11:45.5804595Z dynamo/cpython/3_13/test_numeric_tower 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_numeric_tower_1.1_241abd2701a4df5a_.log 2025-07-17T08:11:45.5805615Z Running 0 items in this shard: 2025-07-17T08:11:45.5805821Z 2025-07-17T08:11:45.5807445Z Running dynamo/cpython/3_13/test_ordered_dict 1/1 ... [2025-07-17 08:11:45.580575] 2025-07-17T08:11:45.5807944Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:45.5811806Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_ordered_dict.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:45.580925] 2025-07-17T08:11:48.6994672Z 2025-07-17T08:11:48.6995762Z dynamo/cpython/3_13/test_ordered_dict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_ordered_dict_1.1_e62ef4506b225f33_.log 2025-07-17T08:11:48.6996934Z Running 0 items in this shard: 2025-07-17T08:11:48.6997125Z 2025-07-17T08:11:48.6998729Z Running dynamo/cpython/3_13/test_baseexception 1/1 ... [2025-07-17 08:11:48.699703] 2025-07-17T08:11:48.6999252Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:48.7002837Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_baseexception.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:48.700038] 2025-07-17T08:11:51.7688365Z 2025-07-17T08:11:51.7689475Z dynamo/cpython/3_13/test_baseexception 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_baseexception_1.1_7b1bd5e4d19ad6a2_.log 2025-07-17T08:11:51.7690563Z Running 0 items in this shard: 2025-07-17T08:11:51.7690798Z 2025-07-17T08:11:51.7691093Z Running dynamo/cpython/3_13/test_int 1/1 ... [2025-07-17 08:11:51.768932] 2025-07-17T08:11:51.7691601Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:51.7695193Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_int.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:51.769271] 2025-07-17T08:11:54.8879992Z 2025-07-17T08:11:54.8880994Z dynamo/cpython/3_13/test_int 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_int_1.1_6f8111f10580f4d0_.log 2025-07-17T08:11:54.8881872Z Running 0 items in this shard: 2025-07-17T08:11:54.8882099Z 2025-07-17T08:11:54.8884148Z Running dynamo/cpython/3_13/test_itertools 1/1 ... [2025-07-17 08:11:54.888230] 2025-07-17T08:11:54.8884621Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:54.8888155Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_itertools.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:54.888582] 2025-07-17T08:11:58.0072375Z 2025-07-17T08:11:58.0074012Z dynamo/cpython/3_13/test_itertools 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_itertools_1.1_bc39c2aa81f3c56c_.log 2025-07-17T08:11:58.0075577Z Running 0 items in this shard: 2025-07-17T08:11:58.0075900Z 2025-07-17T08:11:58.0077667Z Running dynamo/cpython/3_13/test_userlist 1/1 ... [2025-07-17 08:11:58.007549] 2025-07-17T08:11:58.0078464Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:11:58.0081882Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_userlist.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:11:58.007930] 2025-07-17T08:12:01.0765745Z 2025-07-17T08:12:01.0767360Z dynamo/cpython/3_13/test_userlist 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_userlist_1.1_73280a013fd86d80_.log 2025-07-17T08:12:01.0768957Z Running 0 items in this shard: 2025-07-17T08:12:01.0769221Z 2025-07-17T08:12:01.0771545Z Running dynamo/cpython/3_13/test_cmath 1/1 ... [2025-07-17 08:12:01.076917] 2025-07-17T08:12:01.0772272Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:01.0776894Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_cmath.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:01.077370] 2025-07-17T08:12:04.2461067Z 2025-07-17T08:12:04.2462869Z dynamo/cpython/3_13/test_cmath 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_cmath_1.1_90c18202c7f6906b_.log 2025-07-17T08:12:04.2464382Z Running 0 items in this shard: 2025-07-17T08:12:04.2464659Z 2025-07-17T08:12:04.2466480Z Running dynamo/cpython/3_13/test_math 1/1 ... [2025-07-17 08:12:04.246457] 2025-07-17T08:12:04.2467182Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:04.2472334Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_math.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:04.246888] 2025-07-17T08:12:07.4156007Z 2025-07-17T08:12:07.4157201Z dynamo/cpython/3_13/test_math 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_math_1.1_a049e35a74b8afce_.log 2025-07-17T08:12:07.4158092Z Running 0 items in this shard: 2025-07-17T08:12:07.4158282Z 2025-07-17T08:12:07.4160184Z Running dynamo/cpython/3_13/test_operator 1/1 ... [2025-07-17 08:12:07.415821] 2025-07-17T08:12:07.4160855Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:07.4164324Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_operator.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:07.416155] 2025-07-17T08:12:10.5349892Z 2025-07-17T08:12:10.5351442Z dynamo/cpython/3_13/test_operator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_operator_1.1_4fbdf04ee7ee94c9_.log 2025-07-17T08:12:10.5353106Z Running 0 items in this shard: 2025-07-17T08:12:10.5353382Z 2025-07-17T08:12:10.5355489Z Running dynamo/cpython/3_13/test_userdict 1/1 ... [2025-07-17 08:12:10.535354] 2025-07-17T08:12:10.5356254Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:10.5361128Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_userdict.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:10.535787] 2025-07-17T08:12:13.6043955Z 2025-07-17T08:12:13.6045664Z dynamo/cpython/3_13/test_userdict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_userdict_1.1_3c6cc6aeaaaf845a_.log 2025-07-17T08:12:13.6047192Z Running 0 items in this shard: 2025-07-17T08:12:13.6047545Z 2025-07-17T08:12:13.6047906Z Running dynamo/cpython/3_13/test_set 1/1 ... [2025-07-17 08:12:13.604578] 2025-07-17T08:12:13.6048594Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:13.6052849Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_set.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:13.605022] 2025-07-17T08:12:16.7738812Z 2025-07-17T08:12:16.7739807Z dynamo/cpython/3_13/test_set 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_set_1.1_a59dbe08f16cd0b3_.log 2025-07-17T08:12:16.7740731Z Running 0 items in this shard: 2025-07-17T08:12:16.7740924Z 2025-07-17T08:12:16.7741372Z Running dynamo/cpython/3_13/test_iter 1/1 ... [2025-07-17 08:12:16.773941] 2025-07-17T08:12:16.7741849Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:16.7745383Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_iter.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:16.774311] 2025-07-17T08:12:19.8427625Z 2025-07-17T08:12:19.8428798Z dynamo/cpython/3_13/test_iter 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_iter_1.1_c8d25401639a8538_.log 2025-07-17T08:12:19.8429733Z Running 0 items in this shard: 2025-07-17T08:12:19.8429925Z 2025-07-17T08:12:19.8432028Z Running dynamo/cpython/3_13/test_bool 1/1 ... [2025-07-17 08:12:19.843019] 2025-07-17T08:12:19.8432485Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:19.8435900Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_bool.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:19.843358] 2025-07-17T08:12:23.0119273Z 2025-07-17T08:12:23.0120400Z dynamo/cpython/3_13/test_bool 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_bool_1.1_6e162cbb62e9757b_.log 2025-07-17T08:12:23.0121419Z Running 0 items in this shard: 2025-07-17T08:12:23.0121650Z 2025-07-17T08:12:23.0123037Z Running dynamo/cpython/3_13/test_sort 1/1 ... [2025-07-17 08:12:23.012102] 2025-07-17T08:12:23.0123566Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:23.0127105Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_sort.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:23.012432] 2025-07-17T08:12:26.0809265Z 2025-07-17T08:12:26.0810297Z dynamo/cpython/3_13/test_sort 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_sort_1.1_aa8e301c33d11bf5_.log 2025-07-17T08:12:26.0811204Z Running 0 items in this shard: 2025-07-17T08:12:26.0811392Z 2025-07-17T08:12:26.0813735Z Running dynamo/cpython/3_13/test_float 1/1 ... [2025-07-17 08:12:26.081196] 2025-07-17T08:12:26.0814220Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:26.0818059Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_float.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:26.081566] 2025-07-17T08:12:29.2001216Z 2025-07-17T08:12:29.2002781Z dynamo/cpython/3_13/test_float 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_float_1.1_c60e7c30715c9444_.log 2025-07-17T08:12:29.2004363Z Running 0 items in this shard: 2025-07-17T08:12:29.2004660Z 2025-07-17T08:12:29.2007057Z Running dynamo/cpython/3_13/test_dict 1/1 ... [2025-07-17 08:12:29.200488] 2025-07-17T08:12:29.2007748Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:29.2012629Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_dict.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:29.200932] 2025-07-17T08:12:32.3197475Z 2025-07-17T08:12:32.3199065Z dynamo/cpython/3_13/test_dict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_dict_1.1_3d053a628c82e0e3_.log 2025-07-17T08:12:32.3200621Z Running 0 items in this shard: 2025-07-17T08:12:32.3200906Z 2025-07-17T08:12:32.3203616Z Running dynamo/cpython/3_13/test_complex 1/1 ... [2025-07-17 08:12:32.320106] 2025-07-17T08:12:32.3204433Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:32.3208976Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_complex.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:32.320563] 2025-07-17T08:12:35.4392189Z 2025-07-17T08:12:35.4393754Z dynamo/cpython/3_13/test_complex 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_complex_1.1_6479e34c8228ec5c_.log 2025-07-17T08:12:35.4395302Z Running 0 items in this shard: 2025-07-17T08:12:35.4395579Z 2025-07-17T08:12:35.4397300Z Running dynamo/cpython/3_13/test_tuple 1/1 ... [2025-07-17 08:12:35.439527] 2025-07-17T08:12:35.4398028Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:35.4403054Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_tuple.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:35.439964] 2025-07-17T08:12:38.6087300Z 2025-07-17T08:12:38.6088699Z dynamo/cpython/3_13/test_tuple 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_tuple_1.1_91e32485f7c45069_.log 2025-07-17T08:12:38.6089609Z Running 0 items in this shard: 2025-07-17T08:12:38.6089814Z 2025-07-17T08:12:38.6091658Z Running test_package 1/1 ... [2025-07-17 08:12:38.608963] 2025-07-17T08:12:38.6092377Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:38.6096011Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_package.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:38.609312] 2025-07-17T08:12:41.8780861Z 2025-07-17T08:12:41.8781905Z test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_package_1.1_e5d0f1ec21a03aa6_.log 2025-07-17T08:12:41.8782626Z Running 0 items in this shard: 2025-07-17T08:12:41.8782815Z 2025-07-17T08:12:41.8785002Z Running test_decomp 1/1 ... [2025-07-17 08:12:41.878305] 2025-07-17T08:12:41.8785622Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:41.8788836Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_decomp.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:41.878636] 2025-07-17T08:12:47.5006110Z 2025-07-17T08:12:47.5007241Z test_decomp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_1.1_b93e0aa08b6c86c5_.log 2025-07-17T08:12:47.5007939Z Running 0 items in this shard: 2025-07-17T08:12:47.5008126Z 2025-07-17T08:12:47.5010777Z Running test_autoload 1/1 ... [2025-07-17 08:12:47.500878] 2025-07-17T08:12:47.5011392Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:47.5014606Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_autoload.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:47.501220] 2025-07-17T08:12:50.5697616Z 2025-07-17T08:12:50.5698762Z test_autoload 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_autoload_1.1_172d4f114629c5ca_.log 2025-07-17T08:12:50.5699485Z Running 0 items in this shard: 2025-07-17T08:12:50.5699673Z 2025-07-17T08:12:50.5701763Z Running test_utils_config_module 1/1 ... [2025-07-17 08:12:50.569981] 2025-07-17T08:12:50.5702418Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:50.5705905Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_utils_config_module.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:50.570318] 2025-07-17T08:12:53.7389182Z 2025-07-17T08:12:53.7390276Z test_utils_config_module 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_utils_config_module_1.1_b1ba5d04f9cf897c_.log 2025-07-17T08:12:53.7391923Z Running 0 items in this shard: 2025-07-17T08:12:53.7392180Z 2025-07-17T08:12:53.7393575Z Running test_mkl_verbose 1/1 ... [2025-07-17 08:12:53.739161] 2025-07-17T08:12:53.7393982Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:53.7397252Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkl_verbose.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:53.739500] 2025-07-17T08:12:56.8079495Z 2025-07-17T08:12:56.8080440Z test_mkl_verbose 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkl_verbose_1.1_2939839d9a9e67a8_.log 2025-07-17T08:12:56.8081483Z Running 0 items in this shard: 2025-07-17T08:12:56.8081729Z 2025-07-17T08:12:56.8083321Z Running dynamo/test_deque_reconstruct 1/1 ... [2025-07-17 08:12:56.808172] 2025-07-17T08:12:56.8083796Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:56.8087193Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_deque_reconstruct.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:56.808491] 2025-07-17T08:12:59.7823159Z 2025-07-17T08:12:59.7824434Z dynamo/test_deque_reconstruct 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_deque_reconstruct_1.1_4f91b3a8c409d2bd_.log 2025-07-17T08:12:59.7825214Z 2025-07-17T08:12:59.7827257Z Running test_license 1/1 ... [2025-07-17 08:12:59.782540] 2025-07-17T08:12:59.7827667Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:12:59.7831249Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_license.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:12:59.782886] 2025-07-17T08:13:02.8513241Z 2025-07-17T08:13:02.8514039Z test_license 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_license_1.1_243908365b5700c8_.log 2025-07-17T08:13:02.8514763Z Running 0 items in this shard: 2025-07-17T08:13:02.8514968Z 2025-07-17T08:13:02.8517295Z Running test_mkldnn_verbose 1/1 ... [2025-07-17 08:13:02.851552] 2025-07-17T08:13:02.8517724Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:02.8521076Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn_verbose.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:02.851882] 2025-07-17T08:13:05.9703464Z 2025-07-17T08:13:05.9704362Z test_mkldnn_verbose 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_verbose_1.1_ac05072277b7a814_.log 2025-07-17T08:13:05.9705144Z Running 0 items in this shard: 2025-07-17T08:13:05.9705372Z 2025-07-17T08:13:05.9707375Z Running dynamo/cpython/3_13/test_unittest/test_assertions 1/1 ... [2025-07-17 08:13:05.970549] 2025-07-17T08:13:05.9707931Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:05.9711080Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_unittest/test_assertions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:05.970874] 2025-07-17T08:13:09.1395394Z 2025-07-17T08:13:09.1396589Z dynamo/cpython/3_13/test_unittest/test_assertions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_unittest.test_assertions_1.1_a1c171220fff4be1_.log 2025-07-17T08:13:09.1397748Z Running 0 items in this shard: 2025-07-17T08:13:09.1397962Z 2025-07-17T08:13:09.1398205Z Running test_comparison_utils 1/1 ... [2025-07-17 08:13:09.139671] 2025-07-17T08:13:09.1398797Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:09.1402178Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_comparison_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:09.139992] 2025-07-17T08:13:12.2584930Z 2025-07-17T08:13:12.2585869Z test_comparison_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_comparison_utils_1.1_543aeb3c0fc53964_.log 2025-07-17T08:13:12.2586653Z Running 0 items in this shard: 2025-07-17T08:13:12.2587059Z 2025-07-17T08:13:12.2589117Z Running test_ops 1/1 ... [2025-07-17 08:13:12.258713] 2025-07-17T08:13:12.2589495Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:12.2593098Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:12.259068] 2025-07-17T08:13:26.0420673Z 2025-07-17T08:13:26.0421836Z test_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_1.1_4e8bfc307d563da7_.log 2025-07-17T08:13:26.0422731Z Running 0 items in this shard: 2025-07-17T08:13:26.0422939Z 2025-07-17T08:13:26.0424762Z Running typing/test_python_operators 1/1 ... [2025-07-17 08:13:26.042275] 2025-07-17T08:13:26.0425476Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:26.0428969Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'typing/test_python_operators.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:26.042622] 2025-07-17T08:13:29.1612309Z 2025-07-17T08:13:29.1613702Z typing/test_python_operators 1/1 was successful, full logs can be found in artifacts with path test/test-reports/typing.test_python_operators_1.1_32c39bf557fb139c_.log 2025-07-17T08:13:29.1614621Z Running 0 items in this shard: 2025-07-17T08:13:29.1614850Z 2025-07-17T08:13:29.1616385Z Running torch_np/test_nep50_examples 1/1 ... [2025-07-17 08:13:29.161440] 2025-07-17T08:13:29.1617096Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:29.1620300Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_nep50_examples.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:29.161772] 2025-07-17T08:13:32.4305560Z 2025-07-17T08:13:32.4306884Z torch_np/test_nep50_examples 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_nep50_examples_1.1_2120de93b223db7b_.log 2025-07-17T08:13:32.4307746Z Running 0 items in this shard: 2025-07-17T08:13:32.4307936Z 2025-07-17T08:13:32.4309879Z Running test_ops_jit 1/1 ... [2025-07-17 08:13:32.430790] 2025-07-17T08:13:32.4310478Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:32.4313867Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_jit.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:32.431129] 2025-07-17T08:13:36.8016303Z 2025-07-17T08:13:36.8017700Z test_ops_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_jit_1.1_69eed66761ec2fb4_.log 2025-07-17T08:13:36.8018534Z Running 0 items in this shard: 2025-07-17T08:13:36.8018734Z 2025-07-17T08:13:36.8020118Z Running dynamo/test_skip_guard_eval_unsafe 1/1 ... [2025-07-17 08:13:36.801797] 2025-07-17T08:13:36.8020843Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:36.8024008Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_skip_guard_eval_unsafe.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:36.802127] 2025-07-17T08:13:39.9767967Z 2025-07-17T08:13:39.9769020Z dynamo/test_skip_guard_eval_unsafe 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_skip_guard_eval_unsafe_1.1_2cd87f7e43725421_.log 2025-07-17T08:13:39.9769804Z 2025-07-17T08:13:39.9771882Z Running functorch/test_ac_logging 1/1 ... [2025-07-17 08:13:39.976988] 2025-07-17T08:13:39.9772336Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:39.9775502Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ac_logging.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:39.977344] 2025-07-17T08:13:43.0958492Z 2025-07-17T08:13:43.0959794Z functorch/test_ac_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ac_logging_1.1_8289b140a1e3929c_.log 2025-07-17T08:13:43.0960637Z Running 0 items in this shard: 2025-07-17T08:13:43.0960847Z 2025-07-17T08:13:43.0962641Z Running test_custom_ops 1/1 ... [2025-07-17 08:13:43.096061] 2025-07-17T08:13:43.0963061Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:43.0966543Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_custom_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:43.096388] 2025-07-17T08:13:47.2161149Z 2025-07-17T08:13:47.2162337Z test_custom_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_custom_ops_1.1_0d6a6c2392eef24a_.log 2025-07-17T08:13:47.2163080Z Running 0 items in this shard: 2025-07-17T08:13:47.2163297Z 2025-07-17T08:13:47.2165208Z Running dynamo/test_interop 1/1 ... [2025-07-17 08:13:47.216331] 2025-07-17T08:13:47.2165950Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:47.2169226Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_interop.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:47.216650] 2025-07-17T08:13:50.3463742Z 2025-07-17T08:13:50.3464704Z dynamo/test_interop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_interop_1.1_1a3b0c90aa6f5446_.log 2025-07-17T08:13:50.3465407Z 2025-07-17T08:13:50.3467769Z Running dynamo/test_resume 1/1 ... [2025-07-17 08:13:50.346579] 2025-07-17T08:13:50.3468194Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:50.3471463Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_resume.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:50.346911] 2025-07-17T08:13:53.3758372Z 2025-07-17T08:13:53.3759599Z dynamo/test_resume 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_resume_1.1_3f16504b01420b19_.log 2025-07-17T08:13:53.3760284Z 2025-07-17T08:13:53.3761847Z Running dynamo/test_sdpa 1/1 ... [2025-07-17 08:13:53.376026] 2025-07-17T08:13:53.3762531Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:53.3766348Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sdpa.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:53.376356] 2025-07-17T08:13:56.5129662Z 2025-07-17T08:13:56.5130530Z dynamo/test_sdpa 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sdpa_1.1_23a6ed3a731f6642_.log 2025-07-17T08:13:56.5131401Z 2025-07-17T08:13:56.5132985Z Running dynamo/test_utils 1/1 ... [2025-07-17 08:13:56.513122] 2025-07-17T08:13:56.5133418Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:56.5137227Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:56.513461] 2025-07-17T08:13:59.4680771Z 2025-07-17T08:13:59.4682042Z dynamo/test_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_utils_1.1_62ee25d4fe84f1ef_.log 2025-07-17T08:13:59.4682980Z 2025-07-17T08:13:59.4685153Z Running profiler/test_kineto 1/1 ... [2025-07-17 08:13:59.468296] 2025-07-17T08:13:59.4685955Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:13:59.4689188Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_kineto.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:13:59.468644] 2025-07-17T08:14:02.5372983Z 2025-07-17T08:14:02.5374115Z profiler/test_kineto 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_kineto_1.1_78f9e40944323452_.log 2025-07-17T08:14:02.5374930Z Running 0 items in this shard: 2025-07-17T08:14:02.5375120Z 2025-07-17T08:14:02.5377157Z Running test_fx_experimental 1/1 ... [2025-07-17 08:14:02.537535] 2025-07-17T08:14:02.5377577Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:02.5381059Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_experimental.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:02.537899] 2025-07-17T08:14:07.0082928Z 2025-07-17T08:14:07.0083855Z test_fx_experimental 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_experimental_1.1_42851c33d8fdee4e_.log 2025-07-17T08:14:07.0084653Z Running 0 items in this shard: 2025-07-17T08:14:07.0084842Z 2025-07-17T08:14:07.0087737Z Running dynamo/test_pre_dispatch 1/1 ... [2025-07-17 08:14:07.008596] 2025-07-17T08:14:07.0088190Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:07.0092120Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_pre_dispatch.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:07.008971] 2025-07-17T08:14:09.9902766Z 2025-07-17T08:14:09.9904237Z dynamo/test_pre_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_pre_dispatch_1.1_af6cbe3498b9f604_.log 2025-07-17T08:14:09.9905588Z 2025-07-17T08:14:09.9908606Z Running cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 ... [2025-07-17 08:14:09.990621] 2025-07-17T08:14:09.9909633Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:09.9914067Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'cpp_extensions/python_agnostic_extension/test/test_python_agnostic.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:09.991047] 2025-07-17T08:14:13.0530403Z 2025-07-17T08:14:13.0531848Z cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp_extensions.python_agnostic_extension.test.test_python_agnostic_1.1_3732a21e0b56336c_.log 2025-07-17T08:14:13.0533085Z Running 0 items in this shard: 2025-07-17T08:14:13.0533278Z 2025-07-17T08:14:13.0535170Z Running dynamo/test_dynamic_shapes 1/1 ... [2025-07-17 08:14:13.053303] 2025-07-17T08:14:13.0535641Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:13.0539006Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_dynamic_shapes.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:13.053677] 2025-07-17T08:14:20.9245572Z 2025-07-17T08:14:20.9246674Z dynamo/test_dynamic_shapes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_dynamic_shapes_1.1_df15e480b1f4a794_.log 2025-07-17T08:14:20.9247650Z 2025-07-17T08:14:20.9249808Z Running dynamo/test_functions 1/1 ... [2025-07-17 08:14:20.924808] 2025-07-17T08:14:20.9250253Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:20.9253953Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_functions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:20.925177] 2025-07-17T08:14:27.2897001Z 2025-07-17T08:14:27.2898450Z dynamo/test_functions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_functions_1.1_4a80ac167d5e1e57_.log 2025-07-17T08:14:27.2899180Z 2025-07-17T08:14:27.2900569Z Running dynamo/test_after_aot 1/1 ... [2025-07-17 08:14:27.289881] 2025-07-17T08:14:27.2901279Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:27.2905025Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_after_aot.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:27.290238] 2025-07-17T08:14:30.4125887Z 2025-07-17T08:14:30.4127083Z dynamo/test_after_aot 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_after_aot_1.1_92a00a586306d3ac_.log 2025-07-17T08:14:30.4127788Z 2025-07-17T08:14:30.4129968Z Running test_optim 2/3 ... [2025-07-17 08:14:30.412788] 2025-07-17T08:14:30.4130387Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:30.4133521Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_optim.py', '-m', 'serial', '--shard-id=2', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:30.413123] 2025-07-17T08:14:34.6830147Z 2025-07-17T08:14:34.6831089Z test_optim 2/3 was successful, full logs can be found in artifacts with path test/test-reports/test_optim_2.3_7aeadad2f5999f2a_.log 2025-07-17T08:14:34.6831791Z Running 0 items in this shard: 2025-07-17T08:14:34.6831992Z 2025-07-17T08:14:34.6834917Z Running test_optim 3/3 ... [2025-07-17 08:14:34.683232] 2025-07-17T08:14:34.6835435Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:34.6838436Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_optim.py', '-m', 'serial', '--shard-id=3', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:34.683578] 2025-07-17T08:14:38.9536993Z 2025-07-17T08:14:38.9538118Z test_optim 3/3 was successful, full logs can be found in artifacts with path test/test-reports/test_optim_3.3_5b1a10b11cd7dd59_.log 2025-07-17T08:14:38.9538815Z Running 0 items in this shard: 2025-07-17T08:14:38.9539011Z 2025-07-17T08:14:38.9541409Z Running test_per_overload_api 1/1 ... [2025-07-17 08:14:38.953923] 2025-07-17T08:14:38.9541918Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:38.9545201Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_per_overload_api.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:38.954272] 2025-07-17T08:14:42.0227125Z 2025-07-17T08:14:42.0228031Z test_per_overload_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_per_overload_api_1.1_53ecaf8c343a39de_.log 2025-07-17T08:14:42.0228819Z Running 0 items in this shard: 2025-07-17T08:14:42.0229007Z 2025-07-17T08:14:42.0231601Z Running test_expanded_weights 1/1 ... [2025-07-17 08:14:42.022985] 2025-07-17T08:14:42.0232036Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:42.0235625Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_expanded_weights.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:42.023359] 2025-07-17T08:14:46.1933499Z 2025-07-17T08:14:46.1934748Z test_expanded_weights 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_expanded_weights_1.1_174e0806076e3358_.log 2025-07-17T08:14:46.1935576Z Running 0 items in this shard: 2025-07-17T08:14:46.1935783Z 2025-07-17T08:14:46.1937525Z Running lazy/test_bindings 1/1 ... [2025-07-17 08:14:46.193568] 2025-07-17T08:14:46.1938204Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:46.1941903Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_bindings.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:46.193906] 2025-07-17T08:14:49.3125114Z 2025-07-17T08:14:49.3126334Z lazy/test_bindings 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_bindings_1.1_07000767b29d3920_.log 2025-07-17T08:14:49.3127119Z Running 0 items in this shard: 2025-07-17T08:14:49.3127309Z 2025-07-17T08:14:49.3129356Z Running dynamo/test_cudagraphs_expandable_segments 1/1 ... [2025-07-17 08:14:49.312731] 2025-07-17T08:14:49.3130080Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:49.3133325Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_cudagraphs_expandable_segments.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:49.313066] 2025-07-17T08:14:52.5595651Z 2025-07-17T08:14:52.5597207Z dynamo/test_cudagraphs_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_expandable_segments_1.1_7191b1066550147d_.log 2025-07-17T08:14:52.5598110Z 2025-07-17T08:14:52.5599819Z Running test_native_functions 1/1 ... [2025-07-17 08:14:52.559793] 2025-07-17T08:14:52.5600527Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:52.5603668Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_native_functions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:52.560123] 2025-07-17T08:14:55.6787093Z 2025-07-17T08:14:55.6788019Z test_native_functions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_native_functions_1.1_7c90087ceab586fa_.log 2025-07-17T08:14:55.6788840Z Running 0 items in this shard: 2025-07-17T08:14:55.6789031Z 2025-07-17T08:14:55.6790799Z Running test_type_hints 1/1 ... [2025-07-17 08:14:55.678918] 2025-07-17T08:14:55.6791207Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:55.6794888Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_type_hints.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:55.679233] 2025-07-17T08:14:58.8480201Z 2025-07-17T08:14:58.8481454Z test_type_hints 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_type_hints_1.1_957e09585bd67f19_.log 2025-07-17T08:14:58.8482836Z Running 0 items in this shard: 2025-07-17T08:14:58.8483112Z 2025-07-17T08:14:58.8483340Z Running dynamo/test_export 1/1 ... [2025-07-17 08:14:58.848065] 2025-07-17T08:14:58.8484141Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:14:58.8486485Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_export.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:14:58.848396] 2025-07-17T08:15:02.0508827Z 2025-07-17T08:15:02.0510117Z dynamo/test_export 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_export_1.1_94e47674e03abfa3_.log 2025-07-17T08:15:02.0510789Z 2025-07-17T08:15:02.0512824Z Running test_import_stats 1/1 ... [2025-07-17 08:15:02.051103] 2025-07-17T08:15:02.0513518Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:02.0517117Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_import_stats.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:02.051450] 2025-07-17T08:15:05.1199990Z 2025-07-17T08:15:05.1201145Z test_import_stats 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_import_stats_1.1_c1f1cfce254dbd9b_.log 2025-07-17T08:15:05.1201912Z Running 0 items in this shard: 2025-07-17T08:15:05.1202128Z 2025-07-17T08:15:05.1204008Z Running test_module_tracker 1/1 ... [2025-07-17 08:15:05.120246] 2025-07-17T08:15:05.1204445Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:05.1208363Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_module_tracker.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:05.120596] 2025-07-17T08:15:08.2892824Z 2025-07-17T08:15:08.2893679Z test_module_tracker 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_module_tracker_1.1_d8fdd41e9f8780b8_.log 2025-07-17T08:15:08.2894461Z Running 0 items in this shard: 2025-07-17T08:15:08.2894684Z 2025-07-17T08:15:08.2897133Z Running test_fx_passes 1/1 ... [2025-07-17 08:15:08.289549] 2025-07-17T08:15:08.2897589Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:08.2901296Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_passes.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:08.289932] 2025-07-17T08:15:11.3583600Z 2025-07-17T08:15:11.3584452Z test_fx_passes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_passes_1.1_9a4f005f16fe470e_.log 2025-07-17T08:15:11.3585208Z Running 0 items in this shard: 2025-07-17T08:15:11.3585431Z 2025-07-17T08:15:11.3588049Z Running dynamo/test_unittest 1/1 ... [2025-07-17 08:15:11.358638] 2025-07-17T08:15:11.3588473Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:11.3592089Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_unittest.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:11.358999] 2025-07-17T08:15:14.4837874Z 2025-07-17T08:15:14.4839263Z dynamo/test_unittest 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_unittest_1.1_391aa6f6dad58b19_.log 2025-07-17T08:15:14.4840511Z 2025-07-17T08:15:14.4842876Z Running test_logging 1/1 ... [2025-07-17 08:15:14.484093] 2025-07-17T08:15:14.4843483Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:14.4848091Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_logging.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:14.484501] 2025-07-17T08:15:17.5528888Z 2025-07-17T08:15:17.5529681Z test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_logging_1.1_14ba3b75d4006598_.log 2025-07-17T08:15:17.5530377Z Running 0 items in this shard: 2025-07-17T08:15:17.5530580Z 2025-07-17T08:15:17.5532834Z Running torch_np/test_basic 1/1 ... [2025-07-17 08:15:17.553123] 2025-07-17T08:15:17.5533437Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:17.5537008Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_basic.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:17.553460] 2025-07-17T08:15:20.6718310Z 2025-07-17T08:15:20.6719221Z torch_np/test_basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_basic_1.1_e488b95e4529f465_.log 2025-07-17T08:15:20.6719996Z Running 0 items in this shard: 2025-07-17T08:15:20.6720185Z 2025-07-17T08:15:20.6722494Z Running test_tensorexpr_pybind 1/1 ... [2025-07-17 08:15:20.672061] 2025-07-17T08:15:20.6722936Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:20.6726197Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensorexpr_pybind.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:20.672378] 2025-07-17T08:15:23.7909160Z 2025-07-17T08:15:23.7910241Z test_tensorexpr_pybind 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorexpr_pybind_1.1_4a39739abb3b6991_.log 2025-07-17T08:15:23.7911078Z Running 0 items in this shard: 2025-07-17T08:15:23.7911270Z 2025-07-17T08:15:23.7913353Z Running test_complex 1/1 ... [2025-07-17 08:15:23.791169] 2025-07-17T08:15:23.7913820Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:23.7917375Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_complex.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:23.791505] 2025-07-17T08:15:26.8599797Z 2025-07-17T08:15:26.8601084Z test_complex 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_complex_1.1_6cd475c6198b9ca8_.log 2025-07-17T08:15:26.8602374Z Running 0 items in this shard: 2025-07-17T08:15:26.8602704Z 2025-07-17T08:15:26.8605313Z Running functorch/test_minifier 1/1 ... [2025-07-17 08:15:26.860349] 2025-07-17T08:15:26.8606051Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:26.8610218Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_minifier.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:26.860759] 2025-07-17T08:15:30.1293606Z 2025-07-17T08:15:30.1294540Z functorch/test_minifier 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_minifier_1.1_ac88c93d03a167ce_.log 2025-07-17T08:15:30.1295373Z Running 0 items in this shard: 2025-07-17T08:15:30.1295566Z 2025-07-17T08:15:30.1297223Z Running test_ops_fwd_gradients 1/1 ... [2025-07-17 08:15:30.129540] 2025-07-17T08:15:30.1297747Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:30.1300703Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_fwd_gradients.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:30.129849] 2025-07-17T08:15:34.6501614Z 2025-07-17T08:15:34.6502977Z test_ops_fwd_gradients 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_fwd_gradients_1.1_1a56a866a7cec28c_.log 2025-07-17T08:15:34.6504412Z Running 0 items in this shard: 2025-07-17T08:15:34.6504760Z 2025-07-17T08:15:34.6507008Z Running dynamo/test_misc 1/1 ... [2025-07-17 08:15:34.650517] 2025-07-17T08:15:34.6507637Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:34.6512345Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_misc.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:34.650922] 2025-07-17T08:15:39.0349176Z 2025-07-17T08:15:39.0350034Z dynamo/test_misc 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_misc_1.1_e2c9fae6a571bfe2_.log 2025-07-17T08:15:39.0350703Z 2025-07-17T08:15:39.0353103Z Running torch_np/numpy_tests/core/test_einsum 1/1 ... [2025-07-17 08:15:39.035120] 2025-07-17T08:15:39.0353680Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:39.0358024Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_einsum.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:39.035445] 2025-07-17T08:15:42.1039163Z 2025-07-17T08:15:42.1040838Z torch_np/numpy_tests/core/test_einsum 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_einsum_1.1_a0743e10672a0612_.log 2025-07-17T08:15:42.1042538Z Running 0 items in this shard: 2025-07-17T08:15:42.1042849Z 2025-07-17T08:15:42.1046349Z Running higher_order_ops/test_invoke_quant 1/1 ... [2025-07-17 08:15:42.104313] 2025-07-17T08:15:42.1047121Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:42.1049988Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'higher_order_ops/test_invoke_quant.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:42.104710] 2025-07-17T08:15:48.5778893Z 2025-07-17T08:15:48.5780241Z higher_order_ops/test_invoke_quant 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_invoke_quant_1.1_53bd67c9fff7236c_.log 2025-07-17T08:15:48.5781149Z Running 0 items in this shard: 2025-07-17T08:15:48.5781349Z 2025-07-17T08:15:48.8572057Z Uploading artifacts took 0.28 seconds 2025-07-17T08:15:48.8576003Z Running cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 ... [2025-07-17 08:15:48.857347] 2025-07-17T08:15:48.8576695Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:48.8579623Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:48.857712] 2025-07-17T08:15:51.9262269Z 2025-07-17T08:15:51.9263981Z cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp_extensions.libtorch_agnostic_extension.test.test_libtorch_agnostic_1.1_3fa778fa8bd1c466_.log 2025-07-17T08:15:51.9265421Z Running 0 items in this shard: 2025-07-17T08:15:51.9265635Z 2025-07-17T08:15:51.9266311Z Running test_stateless 1/1 ... [2025-07-17 08:15:51.926463] 2025-07-17T08:15:51.9266713Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:51.9270517Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_stateless.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:51.926794] 2025-07-17T08:15:55.0453680Z 2025-07-17T08:15:55.0454944Z test_stateless 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_stateless_1.1_7a56a9c1eaef750a_.log 2025-07-17T08:15:55.0455729Z Running 0 items in this shard: 2025-07-17T08:15:55.0455921Z 2025-07-17T08:15:55.0457818Z Running profiler/test_profiler 1/1 ... [2025-07-17 08:15:55.045601] 2025-07-17T08:15:55.0458451Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:55.0461803Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_profiler.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:55.045928] 2025-07-17T08:15:59.5164885Z 2025-07-17T08:15:59.5166388Z profiler/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_profiler_1.1_0986369eb0f4aa75_.log 2025-07-17T08:15:59.5172915Z Running 10 items in this shard: test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_basic_work_in_main_thread_False, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_basic_work_in_main_thread_True, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_close_in_scope_work_in_main_thread_False, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_close_in_scope_work_in_main_thread_True, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_complex_work_in_main_thread_False, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_complex_work_in_main_thread_True, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_multiple_preexisting_work_in_main_thread_False, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_multiple_preexisting_work_in_main_thread_True, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_open_in_scope_work_in_main_thread_False, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_open_in_scope_work_in_main_thread_True 2025-07-17T08:15:59.5178659Z 2025-07-17T08:15:59.5178901Z Running nn/test_multihead_attention 1/1 ... [2025-07-17 08:15:59.516856] 2025-07-17T08:15:59.5179417Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:15:59.5180619Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_multihead_attention.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:15:59.517380] 2025-07-17T08:16:02.6860738Z 2025-07-17T08:16:02.6861710Z nn/test_multihead_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_multihead_attention_1.1_c58289c4ec43396a_.log 2025-07-17T08:16:02.6862589Z Running 0 items in this shard: 2025-07-17T08:16:02.6862778Z 2025-07-17T08:16:02.6865341Z Running torch_np/numpy_tests/core/test_numeric 1/1 ... [2025-07-17 08:16:02.686333] 2025-07-17T08:16:02.6865852Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:02.6869675Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_numeric.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:02.686706] 2025-07-17T08:16:05.9557216Z 2025-07-17T08:16:05.9558938Z torch_np/numpy_tests/core/test_numeric 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_numeric_1.1_f37a60b6549c983b_.log 2025-07-17T08:16:05.9560492Z Running 0 items in this shard: 2025-07-17T08:16:05.9560784Z 2025-07-17T08:16:05.9562283Z Running xpu/test_conv 1/1 ... [2025-07-17 08:16:05.956037] 2025-07-17T08:16:05.9563144Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:05.9568208Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'xpu/test_conv.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:05.956481] 2025-07-17T08:16:09.5585121Z 2025-07-17T08:16:09.5586012Z xpu/test_conv 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_conv_1.1_ebe22d83a384bf47_.log 2025-07-17T08:16:09.5586820Z Running 0 items in this shard: 2025-07-17T08:16:09.5587225Z 2025-07-17T08:16:09.5589286Z Running test_weak 1/1 ... [2025-07-17 08:16:09.558751] 2025-07-17T08:16:09.5589657Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:09.5593022Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_weak.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:09.559080] 2025-07-17T08:16:12.6777371Z 2025-07-17T08:16:12.6778201Z test_weak 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_weak_1.1_42ca056f138e917c_.log 2025-07-17T08:16:12.6778891Z Running 0 items in this shard: 2025-07-17T08:16:12.6779275Z 2025-07-17T08:16:12.6781342Z Running dynamo/test_graph_deduplication 1/1 ... [2025-07-17 08:16:12.677916] 2025-07-17T08:16:12.6781926Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:12.6784954Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_graph_deduplication.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:12.678212] 2025-07-17T08:16:15.8094072Z 2025-07-17T08:16:15.8095122Z dynamo/test_graph_deduplication 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_graph_deduplication_1.1_468b555494e0562f_.log 2025-07-17T08:16:15.8095942Z 2025-07-17T08:16:15.8097723Z Running distributions/test_constraints 1/1 ... [2025-07-17 08:16:15.809593] 2025-07-17T08:16:15.8098272Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:15.8101314Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'distributions/test_constraints.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:15.809910] 2025-07-17T08:16:18.8784510Z 2025-07-17T08:16:18.8785821Z distributions/test_constraints 1/1 was successful, full logs can be found in artifacts with path test/test-reports/distributions.test_constraints_1.1_6abedba93658ab5c_.log 2025-07-17T08:16:18.8786750Z Running 0 items in this shard: 2025-07-17T08:16:18.8787210Z 2025-07-17T08:16:18.8789879Z Running test_tensorboard 1/1 ... [2025-07-17 08:16:18.878738] 2025-07-17T08:16:18.8790592Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:18.8794361Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensorboard.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:18.879134] 2025-07-17T08:16:22.3482399Z 2025-07-17T08:16:22.3483632Z test_tensorboard 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorboard_1.1_2a666160b591dac7_.log 2025-07-17T08:16:22.3484393Z Running 0 items in this shard: 2025-07-17T08:16:22.3484615Z 2025-07-17T08:16:22.3486838Z Running profiler/test_cpp_thread 1/1 ... [2025-07-17 08:16:22.348489] 2025-07-17T08:16:22.3487360Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:22.3491034Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_cpp_thread.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:22.348874] 2025-07-17T08:16:26.4689799Z 2025-07-17T08:16:26.4691024Z profiler/test_cpp_thread 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_cpp_thread_1.1_4d53397fd4c00350_.log 2025-07-17T08:16:26.4691933Z Running 0 items in this shard: 2025-07-17T08:16:26.4692128Z 2025-07-17T08:16:26.4694086Z Running dynamo/test_decorators 1/1 ... [2025-07-17 08:16:26.469198] 2025-07-17T08:16:26.4694595Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:26.4698348Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_decorators.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:26.469576] 2025-07-17T08:16:29.5715159Z 2025-07-17T08:16:29.5716073Z dynamo/test_decorators 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_decorators_1.1_f4790883abcab3b4_.log 2025-07-17T08:16:29.5716819Z 2025-07-17T08:16:29.5719793Z Running functorch/test_ac_knapsack 1/1 ... [2025-07-17 08:16:29.571755] 2025-07-17T08:16:29.5720268Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:29.5723924Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ac_knapsack.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:29.572141] 2025-07-17T08:16:32.6906615Z 2025-07-17T08:16:32.6907615Z functorch/test_ac_knapsack 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ac_knapsack_1.1_eb6c674f2a53765b_.log 2025-07-17T08:16:32.6908465Z Running 0 items in this shard: 2025-07-17T08:16:32.6908653Z 2025-07-17T08:16:32.6910519Z Running dynamo/test_base_hop 1/1 ... [2025-07-17 08:16:32.690895] 2025-07-17T08:16:32.6911021Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:32.6914550Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_base_hop.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:32.691236] 2025-07-17T08:16:39.1396277Z 2025-07-17T08:16:39.1397360Z dynamo/test_base_hop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_base_hop_1.1_4e0ca331a5ba52b3_.log 2025-07-17T08:16:39.1398065Z 2025-07-17T08:16:39.1399482Z Running dynamo/test_sources 1/1 ... [2025-07-17 08:16:39.139777] 2025-07-17T08:16:39.1399914Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:39.1403290Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sources.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:39.140129] 2025-07-17T08:16:42.0813902Z 2025-07-17T08:16:42.0814821Z dynamo/test_sources 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sources_1.1_f44eb61bba38b506_.log 2025-07-17T08:16:42.0815513Z 2025-07-17T08:16:42.0817863Z Running test_datapipe 1/1 ... [2025-07-17 08:16:42.081640] 2025-07-17T08:16:42.0818332Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:42.0822919Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_datapipe.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:42.082018] 2025-07-17T08:16:45.2005690Z 2025-07-17T08:16:45.2006519Z test_datapipe 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_datapipe_1.1_8277b0b1fb449871_.log 2025-07-17T08:16:45.2007469Z Running 0 items in this shard: 2025-07-17T08:16:45.2007661Z 2025-07-17T08:16:45.2010019Z Running functorch/test_logging 1/1 ... [2025-07-17 08:16:45.200814] 2025-07-17T08:16:45.2010505Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:45.2013969Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_logging.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:45.201152] 2025-07-17T08:16:48.4197310Z 2025-07-17T08:16:48.4200282Z functorch/test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_logging_1.1_e0260b0a21cc4b5b_.log 2025-07-17T08:16:48.4202054Z Running 0 items in this shard: 2025-07-17T08:16:48.4202409Z 2025-07-17T08:16:48.4202622Z Running torch_np/test_indexing 1/1 ... [2025-07-17 08:16:48.419996] 2025-07-17T08:16:48.4203038Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:48.4206301Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_indexing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:48.420331] 2025-07-17T08:16:51.4889073Z 2025-07-17T08:16:51.4890226Z torch_np/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_indexing_1.1_d743864c4f7e6c3d_.log 2025-07-17T08:16:51.4891031Z Running 0 items in this shard: 2025-07-17T08:16:51.4891236Z 2025-07-17T08:16:51.4893071Z Running dynamo/test_deviceguard 1/1 ... [2025-07-17 08:16:51.489115] 2025-07-17T08:16:51.4893731Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:51.4897060Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_deviceguard.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:51.489444] 2025-07-17T08:16:54.6177434Z 2025-07-17T08:16:54.6178725Z dynamo/test_deviceguard 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_deviceguard_1.1_1dc255168fedcce7_.log 2025-07-17T08:16:54.6179437Z 2025-07-17T08:16:54.6181571Z Running test_content_store 1/1 ... [2025-07-17 08:16:54.617976] 2025-07-17T08:16:54.6182182Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:54.6185691Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_content_store.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:54.618317] 2025-07-17T08:16:57.6867592Z 2025-07-17T08:16:57.6868788Z test_content_store 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_content_store_1.1_c5c22ddf2bc6d97c_.log 2025-07-17T08:16:57.6869581Z Running 0 items in this shard: 2025-07-17T08:16:57.6869771Z 2025-07-17T08:16:57.6872525Z Running lazy/test_step_closures 1/1 ... [2025-07-17 08:16:57.687042] 2025-07-17T08:16:57.6873155Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:16:57.6876672Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_step_closures.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:16:57.687399] 2025-07-17T08:17:00.7557992Z 2025-07-17T08:17:00.7559072Z lazy/test_step_closures 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_step_closures_1.1_f2d191fb43f65491_.log 2025-07-17T08:17:00.7559896Z Running 0 items in this shard: 2025-07-17T08:17:00.7560085Z 2025-07-17T08:17:00.7561915Z Running test_ops_gradients 1/1 ... [2025-07-17 08:17:00.756005] 2025-07-17T08:17:00.7562571Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:00.7565901Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_gradients.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:00.756327] 2025-07-17T08:17:05.8274382Z 2025-07-17T08:17:05.8275712Z test_ops_gradients 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_gradients_1.1_e9fa7342b481ffaa_.log 2025-07-17T08:17:05.8277208Z Running 0 items in this shard: 2025-07-17T08:17:05.8277500Z 2025-07-17T08:17:05.8279822Z Running test_pruning_op 1/1 ... [2025-07-17 08:17:05.827772] 2025-07-17T08:17:05.8280451Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:05.8292309Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_pruning_op.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:05.828200] 2025-07-17T08:17:08.9469751Z 2025-07-17T08:17:08.9470991Z test_pruning_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_pruning_op_1.1_9fd5e1214fdba4f6_.log 2025-07-17T08:17:08.9471738Z Running 0 items in this shard: 2025-07-17T08:17:08.9472616Z 2025-07-17T08:17:08.9474160Z Running test_set_default_mobile_cpu_allocator 1/1 ... [2025-07-17 08:17:08.947224] 2025-07-17T08:17:08.9474781Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:08.9478313Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_set_default_mobile_cpu_allocator.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:08.947593] 2025-07-17T08:17:11.9660002Z 2025-07-17T08:17:11.9661626Z test_set_default_mobile_cpu_allocator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_set_default_mobile_cpu_allocator_1.1_3c85b07ecb09ae49_.log 2025-07-17T08:17:11.9663322Z Running 0 items in this shard: 2025-07-17T08:17:11.9663623Z 2025-07-17T08:17:11.9665640Z Running test_monitor 1/1 ... [2025-07-17 08:17:11.966368] 2025-07-17T08:17:11.9666252Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:11.9671120Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_monitor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:11.966775] 2025-07-17T08:17:15.0352830Z 2025-07-17T08:17:15.0353790Z test_monitor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_monitor_1.1_2540b5a7a32bf066_.log 2025-07-17T08:17:15.0354518Z Running 0 items in this shard: 2025-07-17T08:17:15.0354710Z 2025-07-17T08:17:15.0357515Z Running dynamo/test_package 1/1 ... [2025-07-17 08:17:15.035567] 2025-07-17T08:17:15.0357958Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:15.0361565Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_package.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:15.035940] 2025-07-17T08:17:21.2905581Z 2025-07-17T08:17:21.2906874Z dynamo/test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_package_1.1_6274552bcca3cbd8_.log 2025-07-17T08:17:21.2907617Z 2025-07-17T08:17:21.2909446Z Running test_segment_reductions 1/1 ... [2025-07-17 08:17:21.290778] 2025-07-17T08:17:21.2909924Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:21.2913821Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_segment_reductions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:21.291122] 2025-07-17T08:17:24.4096609Z 2025-07-17T08:17:24.4097813Z test_segment_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_segment_reductions_1.1_09c0c0c339b9bd31_.log 2025-07-17T08:17:24.4098893Z Running 0 items in this shard: 2025-07-17T08:17:24.4099168Z 2025-07-17T08:17:24.4102106Z Running test_out_dtype_op 1/1 ... [2025-07-17 08:17:24.409936] 2025-07-17T08:17:24.4102617Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:24.4105902Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_out_dtype_op.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:24.410310] 2025-07-17T08:17:27.7791917Z 2025-07-17T08:17:27.7792795Z test_out_dtype_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_out_dtype_op_1.1_2d72bc43e6248cc3_.log 2025-07-17T08:17:27.7793569Z Running 0 items in this shard: 2025-07-17T08:17:27.7793761Z 2025-07-17T08:17:27.7796195Z Running test_cuda_sanitizer 1/1 ... [2025-07-17 08:17:27.779457] 2025-07-17T08:17:27.7796756Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:27.7800874Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_sanitizer.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:27.779830] 2025-07-17T08:17:30.8121811Z 2025-07-17T08:17:30.8123186Z test_cuda_sanitizer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_sanitizer_1.1_2d547fce91a43985_.log 2025-07-17T08:17:30.8124493Z Running 0 items in this shard: 2025-07-17T08:17:30.8124775Z 2025-07-17T08:17:30.8126648Z Running test_model_exports_to_core_aten 1/1 ... [2025-07-17 08:17:30.812461] 2025-07-17T08:17:30.8127403Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:30.8132175Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_model_exports_to_core_aten.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:30.812899] 2025-07-17T08:17:34.1818758Z 2025-07-17T08:17:34.1819871Z test_model_exports_to_core_aten 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_model_exports_to_core_aten_1.1_f19c53a30aa4edf6_.log 2025-07-17T08:17:34.1820804Z Running 0 items in this shard: 2025-07-17T08:17:34.1820993Z 2025-07-17T08:17:34.1823079Z Running test_mkldnn 1/1 ... [2025-07-17 08:17:34.182139] 2025-07-17T08:17:34.1823476Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:34.1827105Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:34.182496] 2025-07-17T08:17:37.5013937Z 2025-07-17T08:17:37.5014745Z test_mkldnn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_1.1_cc76d72708475858_.log 2025-07-17T08:17:37.5015492Z Running 0 items in this shard: 2025-07-17T08:17:37.5015740Z 2025-07-17T08:17:37.5018243Z Running test_jit 2/2 ... [2025-07-17 08:17:37.501669] 2025-07-17T08:17:37.5018861Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:37.5022598Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:37.502031] 2025-07-17T08:17:42.7235697Z 2025-07-17T08:17:42.7237062Z test_jit 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_2.2_3d07723bc8e92390_.log 2025-07-17T08:17:42.7238539Z Running 0 items in this shard: 2025-07-17T08:17:42.7238886Z 2025-07-17T08:17:42.7241569Z Running dynamo/test_compiler_bisector 1/1 ... [2025-07-17 08:17:42.723954] 2025-07-17T08:17:42.7242336Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:42.7246877Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_compiler_bisector.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:42.724349] 2025-07-17T08:17:49.0341119Z 2025-07-17T08:17:49.0342208Z dynamo/test_compiler_bisector 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_compiler_bisector_1.1_f70f1724c6f2f140_.log 2025-07-17T08:17:49.0342993Z 2025-07-17T08:17:49.0344796Z Running dynamo/test_aot_autograd 1/1 ... [2025-07-17 08:17:49.034304] 2025-07-17T08:17:49.0345280Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:49.0349203Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_aot_autograd.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:49.034637] 2025-07-17T08:17:52.1785600Z 2025-07-17T08:17:52.1786946Z dynamo/test_aot_autograd 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_aot_autograd_1.1_7d45cf0347a8d5ce_.log 2025-07-17T08:17:52.1787677Z 2025-07-17T08:17:52.1789300Z Running dynamo/test_callback 1/1 ... [2025-07-17 08:17:52.178758] 2025-07-17T08:17:52.1790002Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:52.1793440Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_callback.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:52.179100] 2025-07-17T08:17:58.4550257Z 2025-07-17T08:17:58.4551159Z dynamo/test_callback 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_callback_1.1_42091b16c9b32eea_.log 2025-07-17T08:17:58.4551840Z 2025-07-17T08:17:58.4553889Z Running dynamo/test_torchrec 1/1 ... [2025-07-17 08:17:58.455221] 2025-07-17T08:17:58.4554382Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:17:58.4557629Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_torchrec.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:17:58.455542] 2025-07-17T08:18:01.5716142Z 2025-07-17T08:18:01.5717393Z dynamo/test_torchrec 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_torchrec_1.1_248bc9ace289aa43_.log 2025-07-17T08:18:01.5718110Z 2025-07-17T08:18:01.5721034Z Running test_matmul_cuda 1/1 ... [2025-07-17 08:18:01.571881] 2025-07-17T08:18:01.5721724Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:01.5725698Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_matmul_cuda.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:01.572246] 2025-07-17T08:18:04.6228122Z 2025-07-17T08:18:04.6229529Z test_matmul_cuda 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_matmul_cuda_1.1_c5f6917aa83482ac_.log 2025-07-17T08:18:04.6230315Z Running 0 items in this shard: 2025-07-17T08:18:04.6230519Z 2025-07-17T08:18:04.6232062Z Running optim/test_swa_utils 1/1 ... [2025-07-17 08:18:04.623016] 2025-07-17T08:18:04.6232772Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:04.6236076Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'optim/test_swa_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:04.623363] 2025-07-17T08:18:07.6353390Z 2025-07-17T08:18:07.6354285Z optim/test_swa_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/optim.test_swa_utils_1.1_1723a5c171ef2e15_.log 2025-07-17T08:18:07.6354976Z 2025-07-17T08:18:07.6357602Z Running test_sparse_semi_structured 1/1 ... [2025-07-17 08:18:07.635584] 2025-07-17T08:18:07.6358060Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:07.6362203Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sparse_semi_structured.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:07.635954] 2025-07-17T08:18:14.1106853Z 2025-07-17T08:18:14.1108138Z test_sparse_semi_structured 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_semi_structured_1.1_e43eb08867abacde_.log 2025-07-17T08:18:14.1108979Z Running 0 items in this shard: 2025-07-17T08:18:14.1109185Z 2025-07-17T08:18:14.1111125Z Running functorch/test_control_flow 1/1 ... [2025-07-17 08:18:14.110898] 2025-07-17T08:18:14.1111663Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:14.1114953Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_control_flow.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:14.111246] 2025-07-17T08:18:18.0828980Z 2025-07-17T08:18:18.0829880Z functorch/test_control_flow 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_control_flow_1.1_02a075ed07b5a127_.log 2025-07-17T08:18:18.0830746Z Running 0 items in this shard: 2025-07-17T08:18:18.0830948Z 2025-07-17T08:18:18.0833515Z Running torch_np/numpy_tests/core/test_scalarmath 1/1 ... [2025-07-17 08:18:18.083175] 2025-07-17T08:18:18.0834036Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:18.0837610Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalarmath.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:18.083523] 2025-07-17T08:18:21.2022166Z 2025-07-17T08:18:21.2023235Z torch_np/numpy_tests/core/test_scalarmath 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalarmath_1.1_cb5377c0e0b8b43e_.log 2025-07-17T08:18:21.2024221Z Running 0 items in this shard: 2025-07-17T08:18:21.2024411Z 2025-07-17T08:18:21.2026022Z Running torch_np/numpy_tests/core/test_getlimits 1/1 ... [2025-07-17 08:18:21.202435] 2025-07-17T08:18:21.2026537Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:21.2029692Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_getlimits.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:21.202762] 2025-07-17T08:18:24.3212768Z 2025-07-17T08:18:24.3214117Z torch_np/numpy_tests/core/test_getlimits 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_getlimits_1.1_16aafc74e7f7f25f_.log 2025-07-17T08:18:24.3215114Z Running 0 items in this shard: 2025-07-17T08:18:24.3215306Z 2025-07-17T08:18:24.3216667Z Running torch_np/numpy_tests/core/test_dtype 1/1 ... [2025-07-17 08:18:24.321510] 2025-07-17T08:18:24.3217170Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:24.3220748Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_dtype.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:24.321858] 2025-07-17T08:18:27.3902410Z 2025-07-17T08:18:27.3903829Z torch_np/numpy_tests/core/test_dtype 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_dtype_1.1_c74e2305efef54a2_.log 2025-07-17T08:18:27.3904768Z Running 0 items in this shard: 2025-07-17T08:18:27.3904961Z 2025-07-17T08:18:27.3906355Z Running functorch/test_vmap_registrations 1/1 ... [2025-07-17 08:18:27.390443] 2025-07-17T08:18:27.3907209Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:27.3910552Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_vmap_registrations.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:27.390777] 2025-07-17T08:18:30.6093710Z 2025-07-17T08:18:30.6094950Z functorch/test_vmap_registrations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_registrations_1.1_75da656b63446211_.log 2025-07-17T08:18:30.6096774Z Running 0 items in this shard: 2025-07-17T08:18:30.6096987Z 2025-07-17T08:18:30.6097331Z Running dynamo/test_comptime 1/1 ... [2025-07-17 08:18:30.609548] 2025-07-17T08:18:30.6097803Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:30.6101033Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_comptime.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:30.609883] 2025-07-17T08:18:33.7385371Z 2025-07-17T08:18:33.7386631Z dynamo/test_comptime 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_comptime_1.1_6475ade380d6699d_.log 2025-07-17T08:18:33.7387349Z 2025-07-17T08:18:33.7389334Z Running torch_np/numpy_tests/core/test_shape_base 1/1 ... [2025-07-17 08:18:33.738753] 2025-07-17T08:18:33.7389844Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:33.7393565Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_shape_base.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:33.739135] 2025-07-17T08:18:36.8578131Z 2025-07-17T08:18:36.8579845Z torch_np/numpy_tests/core/test_shape_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_shape_base_1.1_72c93df264726a1a_.log 2025-07-17T08:18:36.8581548Z Running 0 items in this shard: 2025-07-17T08:18:36.8581808Z 2025-07-17T08:18:36.8583756Z Running nn/test_packed_sequence 1/1 ... [2025-07-17 08:18:36.858165] 2025-07-17T08:18:36.8584226Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:36.8587671Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_packed_sequence.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:36.858544] 2025-07-17T08:18:39.9271628Z 2025-07-17T08:18:39.9273190Z nn/test_packed_sequence 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_packed_sequence_1.1_ef850ab55eb1b476_.log 2025-07-17T08:18:39.9274530Z Running 0 items in this shard: 2025-07-17T08:18:39.9274722Z 2025-07-17T08:18:39.9275754Z Running test_futures 1/1 ... [2025-07-17 08:18:39.927389] 2025-07-17T08:18:39.9276137Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:39.9279914Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_futures.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:39.927726] 2025-07-17T08:18:42.9962247Z 2025-07-17T08:18:42.9963069Z test_futures 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_futures_1.1_e0039b54d589f33b_.log 2025-07-17T08:18:42.9963811Z Running 0 items in this shard: 2025-07-17T08:18:42.9964002Z 2025-07-17T08:18:42.9965739Z Running torch_np/numpy_tests/fft/test_pocketfft 1/1 ... [2025-07-17 08:18:42.996392] 2025-07-17T08:18:42.9966244Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:42.9969905Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/fft/test_pocketfft.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:42.996750] 2025-07-17T08:18:46.0653378Z 2025-07-17T08:18:46.0654517Z torch_np/numpy_tests/fft/test_pocketfft 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.fft.test_pocketfft_1.1_5db66bca5b83dd17_.log 2025-07-17T08:18:46.0655463Z Running 0 items in this shard: 2025-07-17T08:18:46.0655666Z 2025-07-17T08:18:46.0657780Z Running test_serialization 1/1 ... [2025-07-17 08:18:46.065596] 2025-07-17T08:18:46.0658303Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:18:46.0661948Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_serialization.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:18:46.065969] 2025-07-17T08:19:11.8584670Z 2025-07-17T08:19:11.8596131Z test_serialization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_serialization_1.1_dcc52114877412e7_.log 2025-07-17T08:19:11.8597578Z Running 2 items in this shard: test/test_serialization.py::TestSerialization::test_serialization_2gb_file, test/test_serialization.py::TestSerialization::test_serialization_4gb_file 2025-07-17T08:19:11.8598458Z 2025-07-17T08:19:11.8956514Z Running nn/test_dropout 1/1 ... [2025-07-17 08:19:11.891162] 2025-07-17T08:19:11.8963086Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:11.9257618Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_dropout.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:11.925455] 2025-07-17T08:19:17.4158884Z 2025-07-17T08:19:17.4159670Z nn/test_dropout 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_dropout_1.1_83581b33a34d018b_.log 2025-07-17T08:19:17.4160410Z Running 0 items in this shard: 2025-07-17T08:19:17.4160617Z 2025-07-17T08:19:17.4163048Z Running test_dynamic_shapes 1/1 ... [2025-07-17 08:19:17.416145] 2025-07-17T08:19:17.4163488Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:17.4167292Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_dynamic_shapes.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:17.416491] 2025-07-17T08:19:20.9361029Z 2025-07-17T08:19:20.9367206Z test_dynamic_shapes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_dynamic_shapes_1.1_456c30bf73675c36_.log 2025-07-17T08:19:20.9368265Z Running 0 items in this shard: 2025-07-17T08:19:20.9368477Z 2025-07-17T08:19:20.9368791Z Running torch_np/numpy_tests/fft/test_helper 1/1 ... [2025-07-17 08:19:20.936347] 2025-07-17T08:19:20.9369281Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:20.9370625Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/fft/test_helper.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:20.936687] 2025-07-17T08:19:24.0561478Z 2025-07-17T08:19:24.0562879Z torch_np/numpy_tests/fft/test_helper 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.fft.test_helper_1.1_1f70905832089999_.log 2025-07-17T08:19:24.0563795Z Running 0 items in this shard: 2025-07-17T08:19:24.0564004Z 2025-07-17T08:19:24.0565805Z Running torch_np/test_ndarray_methods 1/1 ... [2025-07-17 08:19:24.056371] 2025-07-17T08:19:24.0571581Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:24.0572745Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_ndarray_methods.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:24.056753] 2025-07-17T08:19:27.1751886Z 2025-07-17T08:19:27.1753195Z torch_np/test_ndarray_methods 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_ndarray_methods_1.1_a2eaf1c9d81bc622_.log 2025-07-17T08:19:27.1754064Z Running 0 items in this shard: 2025-07-17T08:19:27.1754255Z 2025-07-17T08:19:27.1756437Z Running torch_np/numpy_tests/lib/test_twodim_base 1/1 ... [2025-07-17 08:19:27.175422] 2025-07-17T08:19:27.1757010Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:27.1760263Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_twodim_base.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:27.175759] 2025-07-17T08:19:30.2942340Z 2025-07-17T08:19:30.2943754Z torch_np/numpy_tests/lib/test_twodim_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_twodim_base_1.1_7902858eba54b509_.log 2025-07-17T08:19:30.2944768Z Running 0 items in this shard: 2025-07-17T08:19:30.2944962Z 2025-07-17T08:19:30.2946250Z Running test_vulkan 1/1 ... [2025-07-17 08:19:30.294463] 2025-07-17T08:19:30.2946940Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:30.2950381Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_vulkan.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:30.294791] 2025-07-17T08:19:33.3633244Z 2025-07-17T08:19:33.3634364Z test_vulkan 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_vulkan_1.1_a834ef28ac25a36d_.log 2025-07-17T08:19:33.3635097Z Running 0 items in this shard: 2025-07-17T08:19:33.3635294Z 2025-07-17T08:19:33.3637465Z Running torch_np/numpy_tests/lib/test_shape_base_ 1/1 ... [2025-07-17 08:19:33.363533] 2025-07-17T08:19:33.3638075Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:33.3641419Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_shape_base_.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:33.363863] 2025-07-17T08:19:36.4831902Z 2025-07-17T08:19:36.4833232Z torch_np/numpy_tests/lib/test_shape_base_ 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_shape_base__1.1_1b4db72529e4050f_.log 2025-07-17T08:19:36.4834229Z Running 0 items in this shard: 2025-07-17T08:19:36.4834425Z 2025-07-17T08:19:36.4836068Z Running test_mkldnn_fusion 1/1 ... [2025-07-17 08:19:36.483405] 2025-07-17T08:19:36.4836520Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:36.4839878Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn_fusion.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:36.483767] 2025-07-17T08:19:39.6033065Z 2025-07-17T08:19:39.6034460Z test_mkldnn_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_fusion_1.1_8f4a934039327a93_.log 2025-07-17T08:19:39.6035865Z Running 0 items in this shard: 2025-07-17T08:19:39.6036203Z 2025-07-17T08:19:39.6038781Z Running dynamo/test_guard_manager 1/1 ... [2025-07-17 08:19:39.603673] 2025-07-17T08:19:39.6042671Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:39.6044507Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_guard_manager.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:39.604078] 2025-07-17T08:19:42.5816696Z 2025-07-17T08:19:42.5818233Z dynamo/test_guard_manager 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_guard_manager_1.1_52fe9a020a3120f8_.log 2025-07-17T08:19:42.5819531Z 2025-07-17T08:19:42.5822012Z Running test_shape_ops 1/1 ... [2025-07-17 08:19:42.581989] 2025-07-17T08:19:42.5822450Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:42.5825960Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_shape_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:42.582339] 2025-07-17T08:19:45.7013798Z 2025-07-17T08:19:45.7206628Z test_shape_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_shape_ops_1.1_c5ef33f8d1403980_.log 2025-07-17T08:19:45.7207589Z Running 0 items in this shard: 2025-07-17T08:19:45.7207969Z 2025-07-17T08:19:45.7208330Z Running torch_np/test_scalars_0D_arrays 1/1 ... [2025-07-17 08:19:45.701545] 2025-07-17T08:19:45.7208810Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:45.7209970Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_scalars_0D_arrays.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:45.702703] 2025-07-17T08:19:48.7715892Z 2025-07-17T08:19:48.7717220Z torch_np/test_scalars_0D_arrays 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_scalars_0D_arrays_1.1_f2274ec57a15bbd5_.log 2025-07-17T08:19:48.7718170Z Running 0 items in this shard: 2025-07-17T08:19:48.7718364Z 2025-07-17T08:19:48.7720171Z Running nn/test_load_state_dict 1/1 ... [2025-07-17 08:19:48.771831] 2025-07-17T08:19:48.7720816Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:48.7724214Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_load_state_dict.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:48.772171] 2025-07-17T08:19:51.8406142Z 2025-07-17T08:19:51.8407406Z nn/test_load_state_dict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_load_state_dict_1.1_ba79d55e6d02b200_.log 2025-07-17T08:19:51.8408245Z Running 0 items in this shard: 2025-07-17T08:19:51.8408465Z 2025-07-17T08:19:51.8410442Z Running test_indexing 1/1 ... [2025-07-17 08:19:51.840838] 2025-07-17T08:19:51.8410967Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:51.8414460Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_indexing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:51.841177] 2025-07-17T08:19:55.0098260Z 2025-07-17T08:19:55.0099416Z test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_indexing_1.1_1ecf9357f41ac256_.log 2025-07-17T08:19:55.0100162Z Running 0 items in this shard: 2025-07-17T08:19:55.0100357Z 2025-07-17T08:19:55.0102838Z Running torch_np/numpy_tests/lib/test_index_tricks 1/1 ... [2025-07-17 08:19:55.010065] 2025-07-17T08:19:55.0103404Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:55.0106684Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_index_tricks.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:55.010398] 2025-07-17T08:19:58.0797894Z 2025-07-17T08:19:58.0799212Z torch_np/numpy_tests/lib/test_index_tricks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_index_tricks_1.1_66409db5ab1ecf76_.log 2025-07-17T08:19:58.0800229Z Running 0 items in this shard: 2025-07-17T08:19:58.0800447Z 2025-07-17T08:19:58.0803937Z Running torch_np/numpy_tests/core/test_dlpack 1/1 ... [2025-07-17 08:19:58.080112] 2025-07-17T08:19:58.0804561Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:19:58.0807866Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_dlpack.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:19:58.080456] 2025-07-17T08:20:01.1489608Z 2025-07-17T08:20:01.1490726Z torch_np/numpy_tests/core/test_dlpack 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_dlpack_1.1_df9f8ccdc43da2be_.log 2025-07-17T08:20:01.1491684Z Running 0 items in this shard: 2025-07-17T08:20:01.1491890Z 2025-07-17T08:20:01.1493999Z Running torch_np/numpy_tests/lib/test_arraypad 1/1 ... [2025-07-17 08:20:01.149199] 2025-07-17T08:20:01.1494515Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:01.1497438Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_arraypad.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:01.149527] 2025-07-17T08:20:04.2181266Z 2025-07-17T08:20:04.2182469Z torch_np/numpy_tests/lib/test_arraypad 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_arraypad_1.1_59ed7d4413d5a6d5_.log 2025-07-17T08:20:04.2183620Z Running 0 items in this shard: 2025-07-17T08:20:04.2183932Z 2025-07-17T08:20:04.2188003Z Running lazy/test_debug_util 1/1 ... [2025-07-17 08:20:04.218211] 2025-07-17T08:20:04.2188615Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:04.2189741Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_debug_util.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:04.218584] 2025-07-17T08:20:07.3375736Z 2025-07-17T08:20:07.3376719Z lazy/test_debug_util 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_debug_util_1.1_d1110ff11d4f6d47_.log 2025-07-17T08:20:07.3377583Z Running 0 items in this shard: 2025-07-17T08:20:07.3377781Z 2025-07-17T08:20:07.3380752Z Running test_xnnpack_integration 1/1 ... [2025-07-17 08:20:07.337841] 2025-07-17T08:20:07.3381252Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:07.3384156Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_xnnpack_integration.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:07.338186] 2025-07-17T08:20:10.4569084Z 2025-07-17T08:20:10.4570718Z test_xnnpack_integration 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_xnnpack_integration_1.1_da8af62103d053e5_.log 2025-07-17T08:20:10.4571631Z Running 0 items in this shard: 2025-07-17T08:20:10.4571899Z 2025-07-17T08:20:10.4572992Z Running test_sparse_csr 1/2 ... [2025-07-17 08:20:10.457107] 2025-07-17T08:20:10.4573620Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:10.4577389Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sparse_csr.py', '-m', 'serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:10.457472] 2025-07-17T08:20:16.1794202Z 2025-07-17T08:20:16.1795065Z test_sparse_csr 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_csr_1.2_cecfbbb6759100c5_.log 2025-07-17T08:20:16.1795810Z Running 0 items in this shard: 2025-07-17T08:20:16.1796026Z 2025-07-17T08:20:16.1797847Z Running test_unary_ufuncs 3/3 ... [2025-07-17 08:20:16.179627] 2025-07-17T08:20:16.1798273Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:16.1801967Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_unary_ufuncs.py', '-m', 'serial', '--shard-id=3', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:16.179957] 2025-07-17T08:20:24.1050874Z 2025-07-17T08:20:24.1052226Z test_unary_ufuncs 3/3 was successful, full logs can be found in artifacts with path test/test-reports/test_unary_ufuncs_3.3_ef1ad578c8987047_.log 2025-07-17T08:20:24.1053569Z Running 0 items in this shard: 2025-07-17T08:20:24.1055668Z 2025-07-17T08:20:24.1055949Z Running nn/test_init 1/1 ... [2025-07-17 08:20:24.105424] 2025-07-17T08:20:24.1056555Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:24.1061411Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_init.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:24.105826] 2025-07-17T08:20:27.5249280Z 2025-07-17T08:20:27.5250530Z nn/test_init 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_init_1.1_3970a56d7ca13ac6_.log 2025-07-17T08:20:27.5251787Z Running 0 items in this shard: 2025-07-17T08:20:27.5252148Z 2025-07-17T08:20:27.5254996Z Running test_function_schema 1/1 ... [2025-07-17 08:20:27.525302] 2025-07-17T08:20:27.5255687Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:27.5260084Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_function_schema.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:27.525703] 2025-07-17T08:20:30.5941890Z 2025-07-17T08:20:30.5942761Z test_function_schema 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_function_schema_1.1_2480b36461660468_.log 2025-07-17T08:20:30.5943541Z Running 0 items in this shard: 2025-07-17T08:20:30.5943729Z 2025-07-17T08:20:30.5946237Z Running torch_np/numpy_tests/core/test_scalar_ctors 1/1 ... [2025-07-17 08:20:30.594450] 2025-07-17T08:20:30.5946761Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:30.5950112Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalar_ctors.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:30.594772] 2025-07-17T08:20:33.6631979Z 2025-07-17T08:20:33.6633108Z torch_np/numpy_tests/core/test_scalar_ctors 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalar_ctors_1.1_8cadbed2f05d95f2_.log 2025-07-17T08:20:33.6634357Z Running 0 items in this shard: 2025-07-17T08:20:33.6634547Z 2025-07-17T08:20:33.6635816Z Running test_sparse 1/2 ... [2025-07-17 08:20:33.663420] 2025-07-17T08:20:33.6636250Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:33.6639523Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sparse.py', '-m', 'serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:33.663738] 2025-07-17T08:20:38.3344498Z 2025-07-17T08:20:38.3345631Z test_sparse 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_1.2_ef676ae3b454f8c7_.log 2025-07-17T08:20:38.3346318Z Running 0 items in this shard: 2025-07-17T08:20:38.3346521Z 2025-07-17T08:20:38.3348457Z Running torch_np/test_reductions 1/1 ... [2025-07-17 08:20:38.334671] 2025-07-17T08:20:38.3348902Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:38.3352482Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_reductions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:38.335011] 2025-07-17T08:20:41.5041301Z 2025-07-17T08:20:41.5042319Z torch_np/test_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_reductions_1.1_2bf3f454b442c35e_.log 2025-07-17T08:20:41.5043171Z Running 0 items in this shard: 2025-07-17T08:20:41.5043381Z 2025-07-17T08:20:41.5045168Z Running profiler/test_profiler_tree 1/1 ... [2025-07-17 08:20:41.504329] 2025-07-17T08:20:41.5054575Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:41.5055803Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_profiler_tree.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:41.504671] 2025-07-17T08:20:44.5732472Z 2025-07-17T08:20:44.5733669Z profiler/test_profiler_tree 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_profiler_tree_1.1_e6dd4450beea7ae7_.log 2025-07-17T08:20:44.5735243Z Running 0 items in this shard: 2025-07-17T08:20:44.5735504Z 2025-07-17T08:20:44.5736408Z Running test_type_promotion 1/1 ... [2025-07-17 08:20:44.573462] 2025-07-17T08:20:44.5736962Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:44.5740632Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_type_promotion.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:44.573833] 2025-07-17T08:20:47.7424181Z 2025-07-17T08:20:47.7425076Z test_type_promotion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_type_promotion_1.1_ea6c0b422dc4604b_.log 2025-07-17T08:20:47.7425958Z Running 0 items in this shard: 2025-07-17T08:20:47.7426212Z 2025-07-17T08:20:47.7428452Z Running dynamo/test_python_autograd 1/1 ... [2025-07-17 08:20:47.742673] 2025-07-17T08:20:47.7428927Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:47.7432559Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_python_autograd.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:47.743017] 2025-07-17T08:20:50.8736933Z 2025-07-17T08:20:50.8737900Z dynamo/test_python_autograd 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_python_autograd_1.1_e7bcb92b4cefb722_.log 2025-07-17T08:20:50.8738665Z 2025-07-17T08:20:53.4412152Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:20:53.4415335Z import pkg_resources 2025-07-17T08:20:53.5135214Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:20:53.5137576Z import pkg_resources 2025-07-17T08:20:53.5139046Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:20:53.5140551Z import pkg_resources 2025-07-17T08:20:53.8128370Z Running dynamo/test_activation_checkpointing 1/1 ... [2025-07-17 08:20:53.812390] 2025-07-17T08:20:53.8129300Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:53.8130251Z Running dynamo/test_precompile_context 1/1 ... [2025-07-17 08:20:53.812464] 2025-07-17T08:20:53.8131122Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:53.8131834Z Running test_quantization 9/9 ... [2025-07-17 08:20:53.812512] 2025-07-17T08:20:53.8132538Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:20:53.8133842Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_activation_checkpointing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:53.812812] 2025-07-17T08:20:53.8136124Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_precompile_context.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:53.812888] 2025-07-17T08:20:53.8138044Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_quantization.py', '-m', 'not serial', '--shard-id=9', '--num-shards=9', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:20:53.812930] 2025-07-17T08:21:00.7001797Z 2025-07-17T08:21:00.7003426Z dynamo/test_precompile_context 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_precompile_context_1.1_c80a9796753fbce0_.log 2025-07-17T08:21:00.7004798Z 2025-07-17T08:21:02.3596339Z 2025-07-17T08:21:02.3597865Z dynamo/test_activation_checkpointing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_activation_checkpointing_1.1_01ded972b1a3e589_.log 2025-07-17T08:21:02.3599276Z 2025-07-17T08:21:03.9763694Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:21:03.9766711Z import pkg_resources 2025-07-17T08:21:04.1011432Z Running test_linalg 4/5 ... [2025-07-17 08:21:04.100696] 2025-07-17T08:21:04.1012199Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:21:04.1014293Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_linalg.py', '-m', 'not serial', '--shard-id=4', '--num-shards=5', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:21:04.101099] 2025-07-17T08:21:05.6472917Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:21:05.6474721Z import pkg_resources 2025-07-17T08:21:05.7706869Z Running test_linalg 5/5 ... [2025-07-17 08:21:05.770324] 2025-07-17T08:21:05.7707559Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:21:05.7710799Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_linalg.py', '-m', 'not serial', '--shard-id=5', '--num-shards=5', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:21:05.770719] 2025-07-17T08:28:47.2091879Z 2025-07-17T08:28:47.2093204Z test_quantization 9/9 was successful, full logs can be found in artifacts with path test/test-reports/test_quantization_9.9_cfd80701aad9ea4e_.log 2025-07-17T08:28:47.2177847Z Running 128 items in this shard: test/test_quantization.py::TestQuantizedOps::test_adaptive_avg_pool, test/test_quantization.py::TestQuantizedOps::test_interpolate, test/test_quantization.py::TestQuantizedOps::test_max_pool3d, test/test_quantization.py::TestQuantizedOps::test_max_pool3d_nhwc, test/test_quantization.py::TestQuantizedLinear::test_qlinear, test/test_quantization.py::TestQuantizedLinear::test_qlinear_add_fp8, test/test_quantization.py::TestQuantizedConv::test_benchmark, test/test_quantization.py::TestQuantizedConv::test_qconv1d_relu_cudnn, test/test_quantization.py::TestQuantizedConv::test_qconv2d_sum_relu_float_output_pt2e, test/test_quantization.py::TestDynamicQuantizedOps::test_qrnncell, test/test_quantization.py::TestQuantizedEmbeddingOps::test_embedding_2d_indices, test/test_quantization.py::TestFakeQuantizeOps::test_fq_module_per_tensor, test/test_quantization.py::TestQuantizedTensor::test_choose_qparams, test/test_quantization.py::TestQuantizedTensor::test_decomposed_quantize_per_channel_group, test/test_quantization.py::TestQuantizedTensor::test_qtensor_channel_float_assignment, test/test_quantization.py::TestQuantizedTensor::test_qtensor_fill_per_channel_nhwc, test/test_quantization.py::TestObserver::test_per_channel_observers_load_state_dict, test/test_quantization.py::TestStaticQuantizedModule::test_batch_norm2d, test/test_quantization.py::TestStaticQuantizedModule::test_conv1d_relu_api, test/test_quantization.py::TestStaticQuantizedModule::test_linear, test/test_quantization.py::TestStaticQuantizedModule::test_linear_tanh, test/test_quantization.py::TestStaticQuantizedModule::test_relu, test/test_quantization.py::TestReferenceQuantizedModule::test_linear_decomposed_weight_custom_qmin_qmax, test/test_quantization.py::TestReferenceQuantizedModule::test_rnn_cell, test/test_quantization.py::TestRecordHistogramObserver::test_observer_scriptable, test/test_quantization.py::TestDistributed::test_observers_preserve_buffers, test/test_quantization.py::TestBackendConfig::test_backend_config_set_name, test/test_quantization.py::TestUtils::test_quantize_weight_clamping_per_channel, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_manual, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_mha_batch_first_attr_is_copied_in_prepare, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_nested3, test/test_quantization.py::TestQuantizeEagerQAT::test_dropout, test/test_quantization.py::TestQuantizeEagerQAT::test_embedding_qat_qconfig_equal, test/test_quantization.py::TestQuantizeEagerQAT::test_train_save_load_eval, test/test_quantization.py::TestQuantizeEagerQATNumerics::test_fixed_qparam_ops, test/test_quantization.py::TestFuseEager::test_fuse_function_customization, test/test_quantization.py::TestFuseEager::test_fusion_sequential_model_eval, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_outputs_linear_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_weights_linear_static, test/test_quantization.py::TestEqualizeEager::test_equalize_fused_linearrelu, test/test_quantization.py::TestFuseFx::test_fusion_pattern_with_matchallnode, test/test_quantization.py::TestFuseFx::test_fusion_pattern_with_multiple_inputs, test/test_quantization.py::TestFuseFx::test_qconfig_fused_module, test/test_quantization.py::TestQuantizeFx::test__convert_to_reference_decomposed_fx, test/test_quantization.py::TestQuantizeFx::test_conv_linear_not_reference, test/test_quantization.py::TestQuantizeFx::test_convert_custom_config_set_observed_to_quantized_mapping, test/test_quantization.py::TestQuantizeFx::test_linear_qint8_activation, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_set_input_quantized_indexes, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_set_non_traceable_module_names, test/test_quantization.py::TestQuantizeFx::test_preserve_attributes, test/test_quantization.py::TestQuantizeFx::test_qconfig_dict_setup, test/test_quantization.py::TestQuantizeFx::test_qconfig_function, test/test_quantization.py::TestQuantizeFx::test_qconfig_mapping_repr, test/test_quantization.py::TestQuantizeFx::test_qconfig_mapping_set_module_name_object_type_order, test/test_quantization.py::TestQuantizeFx::test_quant_output_always_observed, test/test_quantization.py::TestQuantizeFx::test_quantized_model_type, test/test_quantization.py::TestQuantizeFx::test_static_lstm_with_custom_fixed_qparams, test/test_quantization.py::TestQuantizeFx::test_view_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFxOps::test_fixed_qparams_ops_wrong_qconfig, test/test_quantization.py::TestQuantizeFxOps::test_pixel_unshuffle, test/test_quantization.py::TestQuantizeFxOps::test_rnn, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_preserves_logic, test/test_quantization.py::TestGraphUtils::test_customized_equivalet_types_dict, test/test_quantization.py::TestMetaDataPorting::test_metadata_porting_for_dq_no_static_q, test/test_quantization.py::TestMetaDataPorting::test_metadata_porting_for_two_dq, test/test_quantization.py::TestMetaDataPorting::test_no_metadata_porting_through_unknown_ops, test/test_quantization.py::TestMetaDataPorting::test_simple_metadata_porting, test/test_quantization.py::TestQuantizePT2E::test_fold_quantize_per_channel, test/test_quantization.py::TestQuantizePT2E::test_move_exported_model_bn_device_cpu, test/test_quantization.py::TestQuantizePT2E::test_preserve_nn_module_stack, test/test_quantization.py::TestQuantizePT2E::test_quantization_dtype_float32_int16, test/test_quantization.py::TestQuantizePT2E::test_reentrant, test/test_quantization.py::TestQuantizePT2E::test_transform_for_annotation, test/test_quantization.py::TestXNNPACKQuantizer::test_cat_same_node, test/test_quantization.py::TestXNNPACKQuantizer::test_conv1d, test/test_quantization.py::TestXNNPACKQuantizer::test_linear_relu, test/test_quantization.py::TestXNNPACKQuantizer::test_mul_float32_max, test/test_quantization.py::TestXNNPACKQuantizer::test_obs_sharing_ops, test/test_quantization.py::TestXNNPACKQuantizer::test_set_module_type_case_2, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_flatten_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary2, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary_unary, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_lowering_to_x86, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_maxpool2d_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_qat_conv2d, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_qat_conv2d_binary, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_qat_conv2d_unary, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_fusion_literal_args, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_fold_bn_erases_add_node, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_conv_transpose_bn, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_int8_shadows_int8_mod, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_linear_fp16_activations, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_linear_kwargs_shadow, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_match_activations_fqn, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_unsupported_op_copy_skips_shadowing, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_user_defined_function, test/test_quantization.py::TestFXNumericSuiteNShadows::test_add_loggers_functions, test/test_quantization.py::TestFXNumericSuiteNShadows::test_extract_weights_linear, test/test_quantization.py::TestFXNumericSuiteNShadows::test_linear_relu_mod, test/test_quantization.py::TestFXNumericSuiteNShadows::test_qconfig_multi_mapping_repr, test/test_quantization.py::TestEqualizeFx::test_input_weight_equalization_prepare, test/test_quantization.py::TestEqualizeFx::test_input_weight_equalization_weights_bias, test/test_quantization.py::TestSerialization::test_conv2d_graph, test/test_quantization.py::TestQuantizeJitPasses::test_conv_trace, test/test_quantization.py::TestQuantizeJitPasses::test_inplace_option, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_child_qconfig, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_for_if, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_for_reused_weight, test/test_quantization.py::TestQuantizeJitPasses::test_replicate_dequantize, test/test_quantization.py::TestQuantizeJitOps::test_group_norm, test/test_quantization.py::TestQuantizeJitOps::test_quantized_conv, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_convert_dynamic_fp16, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_dynamic_shared_weights, test/test_quantization.py::TestAOMigrationQuantization::test_function_import_quant_type, test/test_quantization.py::TestAOMigrationQuantization::test_function_import_utils, test/test_quantization.py::TestAOMigrationNNQuantized::test_modules_linear, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_import_nn_intrinsic_qat, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_convert, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_fusion_patterns, test/test_quantization.py::TestBitsCPU::test_subclass_cpu, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_extremes_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPU::test_creation_with_zeros_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_empty_cpu_float8_e4m3fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_finfo_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_float8_e8m0fnu_rne_rounding_cpu, test/test_quantization.py::TestFloat8DtypeCPU::test_save_load_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPU::test_to_string_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPUOnlyCPU::test_mul_cpu_float8_e4m3fn 2025-07-17T08:28:47.2260938Z 2025-07-17T08:28:50.4954294Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:28:50.4955913Z import pkg_resources 2025-07-17T08:28:50.6189256Z Running dynamo/cpython/3_13/test_list 1/1 ... [2025-07-17 08:28:50.618516] 2025-07-17T08:28:50.6189821Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:28:50.6193312Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_list.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:28:50.618944] 2025-07-17T08:29:02.6036998Z 2025-07-17T08:29:02.6038240Z dynamo/cpython/3_13/test_list 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_list_1.1_f81d7ec23c964aec_.log 2025-07-17T08:29:02.6058388Z Running 65 items in this shard: test/dynamo/cpython/3_13/test_list.py::ListTest::test_addmul, test/dynamo/cpython/3_13/test_list.py::ListTest::test_append, test/dynamo/cpython/3_13/test_list.py::ListTest::test_basic, test/dynamo/cpython/3_13/test_list.py::ListTest::test_bigrepeat, test/dynamo/cpython/3_13/test_list.py::ListTest::test_clear, test/dynamo/cpython/3_13/test_list.py::ListTest::test_constructor_exception_handling, test/dynamo/cpython/3_13/test_list.py::ListTest::test_constructors, test/dynamo/cpython/3_13/test_list.py::ListTest::test_contains, test/dynamo/cpython/3_13/test_list.py::ListTest::test_contains_fake, test/dynamo/cpython/3_13/test_list.py::ListTest::test_contains_order, test/dynamo/cpython/3_13/test_list.py::ListTest::test_copy, test/dynamo/cpython/3_13/test_list.py::ListTest::test_count, test/dynamo/cpython/3_13/test_list.py::ListTest::test_count_index_remove_crashes, test/dynamo/cpython/3_13/test_list.py::ListTest::test_delitem, test/dynamo/cpython/3_13/test_list.py::ListTest::test_delslice, test/dynamo/cpython/3_13/test_list.py::ListTest::test_deopt_from_append_list, test/dynamo/cpython/3_13/test_list.py::ListTest::test_empty_slice, test/dynamo/cpython/3_13/test_list.py::ListTest::test_equal_operator_modifying_operand, test/dynamo/cpython/3_13/test_list.py::ListTest::test_exhausted_iterator, test/dynamo/cpython/3_13/test_list.py::ListTest::test_extend, test/dynamo/cpython/3_13/test_list.py::ListTest::test_extendedslicing, test/dynamo/cpython/3_13/test_list.py::ListTest::test_free_after_iterating, test/dynamo/cpython/3_13/test_list.py::ListTest::test_getitem, test/dynamo/cpython/3_13/test_list.py::ListTest::test_getitem_error, test/dynamo/cpython/3_13/test_list.py::ListTest::test_getitemoverwriteiter, test/dynamo/cpython/3_13/test_list.py::ListTest::test_getslice, test/dynamo/cpython/3_13/test_list.py::ListTest::test_iadd, test/dynamo/cpython/3_13/test_list.py::ListTest::test_identity, test/dynamo/cpython/3_13/test_list.py::ListTest::test_imul, test/dynamo/cpython/3_13/test_list.py::ListTest::test_index, test/dynamo/cpython/3_13/test_list.py::ListTest::test_init, test/dynamo/cpython/3_13/test_list.py::ListTest::test_insert, test/dynamo/cpython/3_13/test_list.py::ListTest::test_iterator_pickle, test/dynamo/cpython/3_13/test_list.py::ListTest::test_keyword_args, test/dynamo/cpython/3_13/test_list.py::ListTest::test_keywords_in_subclass, test/dynamo/cpython/3_13/test_list.py::ListTest::test_len, test/dynamo/cpython/3_13/test_list.py::ListTest::test_list_index_modifing_operand, test/dynamo/cpython/3_13/test_list.py::ListTest::test_list_resize_overflow, test/dynamo/cpython/3_13/test_list.py::ListTest::test_lt_operator_modifying_operand, test/dynamo/cpython/3_13/test_list.py::ListTest::test_minmax, test/dynamo/cpython/3_13/test_list.py::ListTest::test_no_comdat_folding, test/dynamo/cpython/3_13/test_list.py::ListTest::test_overflow, test/dynamo/cpython/3_13/test_list.py::ListTest::test_pickle, test/dynamo/cpython/3_13/test_list.py::ListTest::test_pop, test/dynamo/cpython/3_13/test_list.py::ListTest::test_preallocation, test/dynamo/cpython/3_13/test_list.py::ListTest::test_remove, test/dynamo/cpython/3_13/test_list.py::ListTest::test_repeat, test/dynamo/cpython/3_13/test_list.py::ListTest::test_repr, test/dynamo/cpython/3_13/test_list.py::ListTest::test_repr_deep, test/dynamo/cpython/3_13/test_list.py::ListTest::test_repr_large, test/dynamo/cpython/3_13/test_list.py::ListTest::test_repr_mutate, test/dynamo/cpython/3_13/test_list.py::ListTest::test_reverse, test/dynamo/cpython/3_13/test_list.py::ListTest::test_reversed, test/dynamo/cpython/3_13/test_list.py::ListTest::test_reversed_pickle, test/dynamo/cpython/3_13/test_list.py::ListTest::test_set_subscript, test/dynamo/cpython/3_13/test_list.py::ListTest::test_setitem, test/dynamo/cpython/3_13/test_list.py::ListTest::test_setitem_error, test/dynamo/cpython/3_13/test_list.py::ListTest::test_setslice, test/dynamo/cpython/3_13/test_list.py::ListTest::test_slice, test/dynamo/cpython/3_13/test_list.py::ListTest::test_slice_assign_iterator, test/dynamo/cpython/3_13/test_list.py::ListTest::test_sort, test/dynamo/cpython/3_13/test_list.py::ListTest::test_step_overflow, test/dynamo/cpython/3_13/test_list.py::ListTest::test_subscript, test/dynamo/cpython/3_13/test_list.py::ListTest::test_tier2_invalidates_iterator, test/dynamo/cpython/3_13/test_list.py::ListTest::test_truth 2025-07-17T08:29:02.6076733Z 2025-07-17T08:29:05.8314736Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:29:05.8317946Z import pkg_resources 2025-07-17T08:29:05.9567838Z Running functorch/test_vmap 1/4 ... [2025-07-17 08:29:05.956337] 2025-07-17T08:29:05.9568549Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:29:05.9570752Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_vmap.py', '-m', 'not serial', '--shard-id=1', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:29:05.956757] 2025-07-17T08:30:30.9884508Z 2025-07-17T08:30:30.9885895Z test_linalg 4/5 was successful, full logs can be found in artifacts with path test/test-reports/test_linalg_4.5_69105fb901efa5f6_.log 2025-07-17T08:30:30.9978152Z Running 251 items in this shard: test/test_linalg.py::TestLinalgCPU::test_1_sized_with_0_strided_cpu_float64, test/test_linalg.py::TestLinalgCPU::test__dyn_quant_matmul_4bit_m_1_k_128_n_11008_cpu, test/test_linalg.py::TestLinalgCPU::test__int4_mm_m_32_k_32_n_48_cpu, test/test_linalg.py::TestLinalgCPU::test__int4_mm_m_32_k_32_n_64_cpu, test/test_linalg.py::TestLinalgCPU::test__int4_mm_m_32_k_64_n_48_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_32_k_32_n_48_compile_True_slice_False_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_32_k_32_n_48_compile_True_slice_True_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_32_k_32_n_64_compile_True_slice_False_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_32_k_64_n_48_compile_False_slice_False_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_32_k_64_n_48_compile_True_slice_False_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_32_k_64_n_64_compile_True_slice_False_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_64_k_32_n_48_compile_True_slice_False_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_64_k_32_n_64_compile_False_slice_False_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_64_k_64_n_64_compile_False_slice_True_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_16_use_transpose_a_False_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_16_use_transpose_a_False_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_16_use_transpose_a_False_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_16_n_16_use_transpose_a_False_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_16_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_16_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_16_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_32_n_16_use_transpose_a_False_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_32_n_16_use_transpose_a_False_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_32_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_32_n_16_use_transpose_a_True_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_32_n_32_use_transpose_a_False_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_0_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_0_n_16_use_transpose_a_True_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_0_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_0_n_32_use_transpose_a_False_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_16_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_16_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_16_n_32_use_transpose_a_False_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_16_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_32_n_16_use_transpose_a_False_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_32_n_16_use_transpose_a_True_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_32_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_32_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_32_n_32_use_transpose_a_False_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_32_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_0_n_16_use_transpose_a_True_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_0_n_16_use_transpose_a_True_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_0_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_0_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_0_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_0_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_0_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_16_n_16_use_transpose_a_False_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_16_n_16_use_transpose_a_False_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_16_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_16_n_16_use_transpose_a_True_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_16_n_32_use_transpose_a_False_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_16_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_16_use_transpose_a_True_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_32_use_transpose_a_False_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_32_use_transpose_a_False_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_k_16_n_16_use_transpose_a_True_use_transpose_b_False_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_k_16_n_16_use_transpose_a_True_use_transpose_b_True_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_k_16_n_32_use_transpose_a_False_use_transpose_b_False_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_k_16_n_32_use_transpose_a_True_use_transpose_b_True_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_k_32_n_16_use_transpose_a_False_use_transpose_b_False_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_k_32_n_32_use_transpose_a_False_use_transpose_b_False_cpu, test/test_linalg.py::TestLinalgCPU::test_addbmm_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_addmm_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_addmm_gelu_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_False_alpha_0_0_beta_0_5_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_False_alpha_0_0_beta_1_0_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_False_alpha_0_2_beta_0_5_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_True_alpha_0_0_beta_0_5_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_True_alpha_0_0_beta_0_5_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_True_alpha_0_2_beta_0_5_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_True_alpha_1_0_beta_0_0_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_0_0_beta_0_5_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_0_0_beta_1_0_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_0_2_beta_0_0_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_0_2_beta_1_0_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_0_2_beta_1_0_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_1_0_beta_0_0_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_1_0_beta_0_0_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_True_alpha_0_2_beta_0_0_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_relu_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_sizes_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_addmv_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmv_rowmajor_colmajor_incx_incy_lda_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_addr_float_and_complex_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addr_float_and_complex_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_addr_float_and_complex_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addr_integral_cpu_int64, test/test_linalg.py::TestLinalgCPU::test_addr_type_promotion_cpu, test/test_linalg.py::TestLinalgCPU::test_baddbmm_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_baddbmm_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_baddbmm_input_dtypes_compatibility_cpu_int32, test/test_linalg.py::TestLinalgCPU::test_blas_alpha_beta_empty_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_blas_alpha_beta_empty_cpu_int8, test/test_linalg.py::TestLinalgCPU::test_blas_mv_large_input_cpu, test/test_linalg.py::TestLinalgCPU::test_blas_nan_out_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_bmm_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_bmm_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_cholesky_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_cholesky_errors_and_warnings_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_cholesky_errors_and_warnings_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_cholesky_ex_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_cholesky_ex_non_pd_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_cholesky_ex_non_pd_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_batched_broadcasting_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_batched_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_batched_many_batches_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_ck_blas_library_cpu, test/test_linalg.py::TestLinalgCPU::test_compile_int4_mm_m_64_k_64_n_64_cpu, test/test_linalg.py::TestLinalgCPU::test_cond_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_cond_errors_and_warnings_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_corner_cases_of_cublasltmatmul_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_corner_cases_of_cublasltmatmul_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_corner_cases_of_cublasltmatmul_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_corner_cases_of_cublasltmatmul_cpu_int8, test/test_linalg.py::TestLinalgCPU::test_det_logdet_slogdet_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_dot_vs_numpy_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_eig_errors_and_warnings_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_eig_numpy_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_eigh_errors_and_warnings_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_eigh_lwork_lapack_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_eigvalsh_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_einsum_corner_cases_cpu, test/test_linalg.py::TestLinalgCPU::test_einsum_random_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_einsum_sublist_format_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_32_k_64_cpu, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_36_k_35_cpu, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_36_k_36_cpu, test/test_linalg.py::TestLinalgCPU::test_geqrf_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_geqrf_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_inv_ex_info_device_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_inv_ex_singular_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_inv_ex_singular_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_inv_ex_singular_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_inverse_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_inverse_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_inverse_errors_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_inverse_errors_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_inverse_errors_large_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_inverse_many_batches_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_inverse_many_batches_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_kron_errors_and_warnings_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_kron_errors_and_warnings_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_ldl_factor_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_linalg_cross_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_linalg_lstsq_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_linalg_lstsq_input_checks_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_linalg_lu_cpu_errors_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_linalg_lu_cpu_errors_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_linalg_lu_solve_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_linalg_lu_solve_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_linalg_lu_solve_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_linalg_matrix_exp_boundary_cases_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_linalg_matrix_exp_boundary_cases_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_linalg_matrix_exp_compare_with_taylor_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_linalg_matrix_exp_no_warnings_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_linalg_matrix_exp_perverse_nan_values_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_linalg_qr_autograd_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_linalg_solve_triangular_broadcasting_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_linalg_solve_triangular_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_linalg_solve_triangular_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_linalg_solve_triangular_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_linear_algebra_scalar_raises_cpu, test/test_linalg.py::TestLinalgCPU::test_lobpcg_basic_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_lu_solve_batched_broadcasting_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_lu_solve_batched_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_lu_solve_batched_many_batches_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_lu_solve_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_lu_solve_large_matrices_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_lu_solve_large_matrices_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_matmul_offline_mgpu_tunableop_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_matmul_small_brute_force_1d_Nd_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_matmul_small_brute_force_2d_Nd_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_matrix_norm_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_matrix_power_non_negative_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_matrix_rank_basic_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_mm_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_mm_cpu_int64, test/test_linalg.py::TestLinalgCPU::test_mm_submatrix_offline_tunableop_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_multi_dot_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_norm_bfloat16_and_half_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_norm_dtype_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_norm_dtype_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_nuclear_norm_out_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_old_cholesky_batched_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_old_cholesky_batched_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_old_cholesky_batched_many_batches_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_old_cholesky_empty_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_ormqr_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_ormqr_errors_and_warnings_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_ormqr_errors_and_warnings_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_outer_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_outer_cpu_int64, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_bfloat16_bool, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_bool_int64, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_bool_int8, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_complex128_bfloat16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_complex128_int64, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_complex128_uint8, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_complex64_bool, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_complex64_int32, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_complex64_int8, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_float16_float16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_float16_float32, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_float16_int16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_float32_bfloat16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int16_float16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int16_float64, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int16_int16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int16_int8, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int32_complex64, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int32_float16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int32_int32, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int32_uint8, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int64_int8, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int8_bool, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int8_int32, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_uint8_complex128, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_uint8_int16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_uint8_int32, test/test_linalg.py::TestLinalgCPU::test_pinv_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_qr_error_cases_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_qr_vs_numpy_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_rotating_buffer_tunableop_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_scaled_gemm_offline_tunableop_cpu_float8_e5m2fnuz, test/test_linalg.py::TestLinalgCPU::test_scaled_gemm_tunableop_cpu_float8_e5m2fnuz, test/test_linalg.py::TestLinalgCPU::test_solve_batched_broadcasting_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_strided_mm_bmm_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_svd_memory_allocation_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_symeig_removed_error_cpu, test/test_linalg.py::TestLinalgCPU::test_tensordot_out_kernel_errors_with_autograd_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_tensordot_out_kernel_errors_with_autograd_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_tensorinv_singular_input_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_tensorsolve_empty_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_triangular_solve_batched_many_batches_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_triangular_solve_out_errors_and_warnings_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_vector_norm_extreme_values_cpu, test/test_linalg.py::TestLinalgCPU::test_vector_norm_reduce_over_1D_vector_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_vector_norm_reduce_over_1D_vector_cpu_float64 2025-07-17T08:30:31.0068803Z 2025-07-17T08:30:34.2126089Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:30:34.2129201Z import pkg_resources 2025-07-17T08:30:34.3385371Z Running test_nestedtensor 1/1 ... [2025-07-17 08:30:34.338114] 2025-07-17T08:30:34.3386130Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:30:34.3388587Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_nestedtensor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:30:34.338510] 2025-07-17T08:32:17.3970138Z 2025-07-17T08:32:17.3971990Z test_linalg 5/5 was successful, full logs can be found in artifacts with path test/test-reports/test_linalg_5.5_2c4a675dbef5ac0f_.log 2025-07-17T08:32:17.4064757Z Running 244 items in this shard: test/test_linalg.py::TestLinalgCPU::test_1_sized_with_0_strided_cpu_float32, test/test_linalg.py::TestLinalgCPU::test__dyn_quant_matmul_4bit_m_32_k_128_n_4096_cpu, test/test_linalg.py::TestLinalgCPU::test__dyn_quant_matmul_4bit_m_32_k_64_n_11008_cpu, test/test_linalg.py::TestLinalgCPU::test__dyn_quant_pack_4bit_weight_k_256_n_32_cpu, test/test_linalg.py::TestLinalgCPU::test__dyn_quant_pack_4bit_weight_k_64_n_32_cpu, test/test_linalg.py::TestLinalgCPU::test__dyn_quant_pack_4bit_weight_k_64_n_64_cpu, test/test_linalg.py::TestLinalgCPU::test__int4_mm_m_64_k_64_n_64_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_32_k_64_n_48_compile_False_slice_True_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_32_k_64_n_48_compile_True_slice_True_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_64_k_32_n_48_compile_False_slice_False_cpu, test/test_linalg.py::TestLinalgCPU::test__int8_mm_m_64_k_64_n_48_compile_False_slice_True_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_16_use_transpose_a_True_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_32_use_transpose_a_False_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_0_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_16_n_16_use_transpose_a_False_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_16_n_16_use_transpose_a_False_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_16_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_16_n_32_use_transpose_a_False_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_16_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_32_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_32_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_32_n_32_use_transpose_a_False_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_32_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_32_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_0_k_32_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_0_n_16_use_transpose_a_False_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_0_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_0_n_16_use_transpose_a_True_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_0_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_0_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_0_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_0_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_16_n_16_use_transpose_a_False_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_16_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_16_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_16_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_16_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_16_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_32_n_16_use_transpose_a_False_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_32_n_16_use_transpose_a_False_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_32_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_32_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_17_k_32_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_0_n_16_use_transpose_a_False_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_0_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_0_n_32_use_transpose_a_False_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_0_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_16_n_16_use_transpose_a_False_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_16_n_16_use_transpose_a_False_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_16_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_16_n_32_use_transpose_a_True_use_transpose_b_True_non_contig_type_2_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_16_use_transpose_a_False_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_16_use_transpose_a_False_use_transpose_b_True_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_16_use_transpose_a_False_use_transpose_b_True_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_0_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_16_use_transpose_a_True_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_32_use_transpose_a_False_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_cpu_m_8_k_32_n_32_use_transpose_a_True_use_transpose_b_False_non_contig_type_1_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_k_16_n_16_use_transpose_a_False_use_transpose_b_True_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_k_32_n_16_use_transpose_a_True_use_transpose_b_True_cpu, test/test_linalg.py::TestLinalgCPU::test__int_mm_k_32_n_32_use_transpose_a_False_use_transpose_b_True_cpu, test/test_linalg.py::TestLinalgCPU::test_addbmm_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_addbmm_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_gelu_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_False_alpha_0_0_beta_1_0_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_False_alpha_0_2_beta_0_0_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_False_alpha_0_2_beta_1_0_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_True_alpha_0_0_beta_1_0_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_True_alpha_0_2_beta_0_0_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_True_alpha_1_0_beta_0_5_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_False_transpose_b_True_alpha_1_0_beta_1_0_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_0_0_beta_0_0_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_0_0_beta_0_0_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_0_0_beta_0_5_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_0_2_beta_0_5_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_False_alpha_1_0_beta_0_5_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_True_alpha_0_0_beta_0_0_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_True_alpha_0_0_beta_0_5_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_True_alpha_0_2_beta_0_0_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_True_alpha_0_2_beta_0_0_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_True_alpha_0_2_beta_0_5_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmm_mv_transpose_a_True_transpose_b_True_alpha_0_2_beta_0_5_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_addmm_relu_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_relu_tunableop_rocm_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmm_sizes_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_addmv_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_addmv_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_addr_integral_cpu_int16, test/test_linalg.py::TestLinalgCPU::test_addr_integral_cpu_int8, test/test_linalg.py::TestLinalgCPU::test_blas_alpha_beta_empty_cpu_int16, test/test_linalg.py::TestLinalgCPU::test_blas_nan_out_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_blas_nan_out_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_blas_nan_out_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_cholesky_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_cholesky_errors_and_warnings_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_cholesky_ex_non_pd_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_cholesky_inverse_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_cholesky_inverse_errors_and_warnings_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_backward_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_batched_broadcasting_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_batched_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_batched_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_batched_many_batches_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_batched_many_batches_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_out_errors_and_warnings_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_out_errors_and_warnings_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_cholesky_solve_out_errors_and_warnings_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_compile_dyn_quant_matmul_4bit_m_1_k_128_n_4096_cpu, test/test_linalg.py::TestLinalgCPU::test_compile_dyn_quant_matmul_4bit_m_32_k_64_n_11008_cpu, test/test_linalg.py::TestLinalgCPU::test_compile_int4_mm_m_32_k_64_n_48_cpu, test/test_linalg.py::TestLinalgCPU::test_compile_int4_mm_m_32_k_64_n_64_cpu, test/test_linalg.py::TestLinalgCPU::test_cond_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_corner_cases_of_cublasltmatmul_cpu_uint8, test/test_linalg.py::TestLinalgCPU::test_cross_error_cpu, test/test_linalg.py::TestLinalgCPU::test_cross_with_and_without_dim_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_det_logdet_slogdet_batched_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_dump_results_on_exit_tunableop_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_eig_compare_backends_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_eig_compare_backends_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_eig_with_nan_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_eigh_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_eigh_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_eigh_errors_and_warnings_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_eigh_lower_uplo_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_eigh_lower_uplo_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_eigh_svd_illcondition_matrix_input_should_not_crash_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_eigvals_compare_backends_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_eigvals_numpy_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_eigvalsh_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_eigvalsh_errors_and_warnings_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_einsum_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_32_k_36_cpu, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_35_k_32_cpu, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_35_k_35_cpu, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_35_k_36_cpu, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_35_k_40_cpu, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_36_k_64_cpu, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_40_k_32_cpu, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_40_k_36_cpu, test/test_linalg.py::TestLinalgCPU::test_fp16_mv_transposed_first_argument_arm_cpu_m_64_k_35_cpu, test/test_linalg.py::TestLinalgCPU::test_householder_product_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_inv_errors_and_warnings_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_inverse_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_inverse_errors_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_kron_errors_and_warnings_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_ldl_factor_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_ldl_solve_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_linalg_matrix_exp_batch_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_linalg_matrix_exp_compare_with_taylor_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_linalg_matrix_exp_compare_with_taylor_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_linalg_matrix_exp_perverse_nan_values_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_linalg_matrix_exp_utils_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_linalg_solve_triangular_large_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_lu_solve_batched_broadcasting_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_lu_solve_batched_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_lu_solve_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_lu_solve_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_lu_solve_large_matrices_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_lu_unpack_check_input_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_matmul_small_brute_force_2d_Nd_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_matmul_small_brute_force_3d_Nd_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_matrix_rank_atol_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_matrix_rank_atol_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_matrix_rank_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_matrix_rank_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_matrix_rank_empty_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_matrix_rank_out_errors_and_warnings_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_mm_cpu_float16, test/test_linalg.py::TestLinalgCPU::test_mm_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_mm_empty_inputs_mixed_dtype_errors_cpu, test/test_linalg.py::TestLinalgCPU::test_multi_dot_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_norm_complex_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_norm_fro_2_equivalence_old_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_norm_matrix_degenerate_shapes_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_norm_vector_degenerate_shapes_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_nuclear_norm_axes_small_brute_force_old_cpu, test/test_linalg.py::TestLinalgCPU::test_nuclear_norm_exceptions_old_cpu, test/test_linalg.py::TestLinalgCPU::test_nuclear_norm_out_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_old_cholesky_batched_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_old_cholesky_batched_upper_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_old_cholesky_batched_upper_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_ormqr_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_ormqr_errors_and_warnings_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_outer_cpu_bfloat16, test/test_linalg.py::TestLinalgCPU::test_outer_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_outer_cpu_int16, test/test_linalg.py::TestLinalgCPU::test_outer_cpu_int8, test/test_linalg.py::TestLinalgCPU::test_outer_cpu_uint8, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_bfloat16_float16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_bfloat16_int16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_bfloat16_uint8, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_bool_bfloat16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_bool_float64, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_bool_int32, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_complex128_bool, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_complex128_float32, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_complex64_int16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_complex64_uint8, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_float16_bfloat16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_float16_complex128, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_float16_complex64, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_float16_float64, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_float32_complex64, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_float32_uint8, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_float64_int16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int32_bfloat16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int64_bfloat16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int64_complex128, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int64_complex64, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_int64_float32, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_uint8_float16, test/test_linalg.py::TestLinalgCPU::test_outer_type_promotion_cpu_uint8_int8, test/test_linalg.py::TestLinalgCPU::test_pinv_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_pinv_errors_and_warnings_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_pinv_errors_and_warnings_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_pinverse_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_pinverse_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_qr_batched_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_qr_batched_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_qr_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_qr_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_qr_vs_numpy_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_renorm_cpu, test/test_linalg.py::TestLinalgCPU::test_scaled_gemm_offline_tunableop_cpu_float8_e4m3fnuz, test/test_linalg.py::TestLinalgCPU::test_slogdet_errors_and_warnings_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_solve_batched_broadcasting_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_solve_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_solve_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_tensorinv_empty_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_tensorinv_errors_and_warnings_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_tensorinv_singular_input_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_tensorsolve_cpu_complex64, test/test_linalg.py::TestLinalgCPU::test_tensorsolve_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_tensorsolve_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_tensorsolve_empty_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_triangular_solve_batched_broadcasting_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_triangular_solve_cpu_complex128, test/test_linalg.py::TestLinalgCPU::test_triangular_solve_cpu_float64, test/test_linalg.py::TestLinalgCPU::test_triangular_solve_large_cpu_float32, test/test_linalg.py::TestLinalgCPU::test_vdot_invalid_args_cpu, test/test_linalg.py::TestLinalgCPU::test_vdot_vs_numpy_cpu_complex64 2025-07-17T08:32:17.4151683Z 2025-07-17T08:32:20.6163947Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:32:20.6165590Z import pkg_resources 2025-07-17T08:32:20.7421620Z Running test_binary_ufuncs 1/4 ... [2025-07-17 08:32:20.741791] 2025-07-17T08:32:20.7422346Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:32:20.7425703Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_binary_ufuncs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:32:20.742201] 2025-07-17T08:35:41.3788110Z 2025-07-17T08:35:41.3789047Z test_nestedtensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_nestedtensor_1.1_2a41c8b2bb5871cc_.log 2025-07-17T08:35:41.4671548Z Running 1574 items in this shard: test/test_nestedtensor.py::TestNestedTensor::test_2d_nested_tensor_batch_size_2_max_seq_len_3_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_2d_nested_tensor_batch_size_2_max_seq_len_3_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_2d_nested_tensor_batch_size_2_max_seq_len_5_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_2d_nested_tensor_batch_size_2_max_seq_len_5_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_2d_nested_tensor_batch_size_4_max_seq_len_3_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_2d_nested_tensor_batch_size_4_max_seq_len_3_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_2d_nested_tensor_batch_size_4_max_seq_len_5_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_2d_nested_tensor_batch_size_4_max_seq_len_5_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_batch_size_2_max_seq_len_3_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_batch_size_2_max_seq_len_3_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_batch_size_2_max_seq_len_5_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_batch_size_2_max_seq_len_5_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_batch_size_4_max_seq_len_3_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_batch_size_4_max_seq_len_3_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_batch_size_4_max_seq_len_5_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_batch_size_4_max_seq_len_5_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_float_batch_size_2_max_seq_len_3_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_float_batch_size_2_max_seq_len_3_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_float_batch_size_2_max_seq_len_5_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_float_batch_size_2_max_seq_len_5_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_float_batch_size_4_max_seq_len_3_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_float_batch_size_4_max_seq_len_3_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_float_batch_size_4_max_seq_len_5_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_float_batch_size_4_max_seq_len_5_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_cat, test/test_nestedtensor.py::TestNestedTensor::test_copy_, test/test_nestedtensor.py::TestNestedTensor::test_default_nested_tensor, test/test_nestedtensor.py::TestNestedTensor::test_dim, test/test_nestedtensor.py::TestNestedTensor::test_fill_, test/test_nestedtensor.py::TestNestedTensor::test_is_contiguous, test/test_nestedtensor.py::TestNestedTensor::test_like_functions_ones_like, test/test_nestedtensor.py::TestNestedTensor::test_like_functions_randn_like, test/test_nestedtensor.py::TestNestedTensor::test_like_functions_zeros_like, test/test_nestedtensor.py::TestNestedTensor::test_nested_namespace, test/test_nestedtensor.py::TestNestedTensor::test_nested_tensor, test/test_nestedtensor.py::TestNestedTensor::test_nested_tensor_matching_dim, test/test_nestedtensor.py::TestNestedTensor::test_nested_view_from_buffer_overflow_errors, test/test_nestedtensor.py::TestNestedTensor::test_numel, test/test_nestedtensor.py::TestNestedTensor::test_repr_string, test/test_nestedtensor.py::TestNestedTensor::test_size, test/test_nestedtensor.py::TestNestedTensor::test_size_dim, test/test_nestedtensor.py::TestNestedTensor::test_stride, test/test_nestedtensor.py::TestNestedTensor::test_to, test/test_nestedtensor.py::TestNestedTensor::test_to_padded_tensor_on_empty_tensor, test/test_nestedtensor.py::TestNestedTensor::test_unbind_0, test/test_nestedtensor.py::TestNestedTensor::test_unbind_1, test/test_nestedtensor.py::TestNestedTensor::test_unbind_3, test/test_nestedtensor.py::TestNestedTensor::test_unbind_4, test/test_nestedtensor.py::TestNestedTensor::test_unbind_dim, test/test_nestedtensor.py::TestNestedTensor::test_zero_, test/test_nestedtensor.py::TestNestedInt::test_comparisons, test/test_nestedtensor.py::TestNestedInt::test_with_factor, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_binary_ops_with_scalar_eq_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_binary_ops_with_scalar_ge_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_bmm_cpu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_bmm_cpu_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_bmm_cuda_cpu_bfloat16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_bmm_cuda_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_bmm_cuda_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_bmm_cuda_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_bmm_noncontiguous_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_bmm_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_clone_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_clone_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_contiguous_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_contiguous_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_detach_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_detach_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_detach_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_device_checks_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_dropout_jagged_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_dropout_jagged_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_dropout_noncontiguous_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_dropout_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_dropout_strided_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_dropout_strided_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_embedding_jagged_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_embedding_strided_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_empty_like_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_empty_like_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_empty_like_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_layer_norm_breaking_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_layer_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_linear_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_linear_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_linear_noncontiguous_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_linear_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_masked_fill_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_masked_fill_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_masked_fill_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_matmul_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_matmul_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_matmul_noncontiguous_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_matmul_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_matmul_nt_with_broadcasted_t_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_matmul_nt_with_broadcasted_t_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_matmul_with_bmm_path_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_matmul_with_bmm_path_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_narrow_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_narrow_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_narrow_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_masked_select_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_add_in_place_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_add_in_place_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_add_transpose_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_add_transpose_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_add_transpose_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_add_transpose_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_chunk_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_chunk_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_chunk_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_128_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_128_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_256_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_256_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_384_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_384_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_8_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_8_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_div_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_div_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_indexing_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_indexing_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_indexing_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_indexing_noncontiguous_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_indexing_noncontiguous_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_indexing_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_mul_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_mul_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_mul_in_place_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_mul_in_place_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_split_with_sizes_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_split_with_sizes_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_split_with_sizes_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_sub_transpose_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_sub_transpose_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_sub_transpose_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_sub_transpose_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_sum_dim_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_reshape_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_reshape_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_reshape_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_scaled_dot_product_attention_input_dim_3_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_scaled_dot_product_attention_input_dim_4_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_False_weights_only_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_False_weights_only_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_False_weights_only_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_False_weights_only_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_False_weights_only_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_False_weights_only_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_True_weights_only_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_True_weights_only_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_True_weights_only_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_True_weights_only_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_True_weights_only_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_True_weights_only_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_softmax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_softmax_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_softmax_noncontiguous_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_softmax_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_squeeze_unsqueeze_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_squeeze_unsqueeze_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_squeeze_unsqueeze_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_dim2_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_dim2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_dim2_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_dim3_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_dim3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_dim3_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_dim4_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_dim4_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_dim4_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_noncontiguous_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_noncontiguous_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_output_size_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_output_size_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_simple_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_simple_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_zero_numel_errors_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_zero_numel_errors_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_zero_numel_errors_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_then_from_padded_tensor_no_transform0213_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_transpose_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_transpose_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_transpose_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_transpose_inference_mode_interaction_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_transpose_inference_mode_interaction_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_transpose_inference_mode_interaction_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_abs__cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_abs_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_cos_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_gelu__cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_gelu_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_isinf_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_isnan_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_isneginf_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_isposinf_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_logical_not_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_neg_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_relu__cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_relu_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_sgn_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_silu__cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_silu_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_sin_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_sqrt_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_tanh__cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_tanh_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unbind_noncontiguous_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unbind_noncontiguous_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unbind_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_view_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_view_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_view_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_view_inference_mode_interaction_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_view_inference_mode_interaction_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_view_inference_mode_interaction_cpu_float64, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_abs_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_accumulate_grad_different_strides_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_as_nested_tensor_propagates_gradients_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_backward_add_strided_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_backward_for_add_op_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_backward_for_sub_op_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_backward_sub_strided_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_dropout_backward_jagged_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_dropout_backward_strided_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_gelu_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_indexing_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_5d_size_128_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_5d_size_2_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_5d_size_32_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_5d_size_4_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_edge_case_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_1023_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_1024_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_128_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_256_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_2_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_32_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_4_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_512_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_513_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_masked_fill_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_bmm_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_bmm_gradcheck_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_from_list_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_from_mask_and_to_padded_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_from_padded_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_from_padded_fused_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_generates_leaf_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_linear_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_linear_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_linear_plus_transpose_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_matmul_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_matmul_gradcheck_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_reshape_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_reshape_gradcheck_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_softmax_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_squeeze_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_squeeze_gradcheck_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_to_padded_tensor_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_transpose_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_transpose_gradcheck_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_unsqueeze_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_unsqueeze_gradcheck_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_relu_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_selu_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_set_requires_grad_from_list_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_set_requires_grad_from_mask_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_split_with_sizes_flow_through_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_to_buffer_series_ops_grad_with_broadcast_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_unbind_flow_through_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_values_grad_with_broadcast_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_apply__cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_False_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_False_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_False_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_False_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_False_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_False_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_True_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_True_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_True_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_True_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_True_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_True_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_False_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_False_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_False_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_False_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_False_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_False_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_True_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_True_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_True_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_True_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_True_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_True_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_False_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_False_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_False_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_False_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_False_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_False_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_True_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_True_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_True_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_True_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_True_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_True_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_False_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_False_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_False_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_False_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_False_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_False_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_True_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_True_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_True_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_True_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_True_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_True_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_False_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_False_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_False_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_False_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_False_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_False_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_True_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_True_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_True_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_True_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_True_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_True_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_strided_requires_grad_False_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_strided_requires_grad_False_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_strided_requires_grad_False_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_strided_requires_grad_False_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_strided_requires_grad_False_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_strided_requires_grad_False_contiguous_True_cpu_float64, 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test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_layer_norm_with_lengths_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_layer_norm_with_lengths_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_layer_norm_with_lengths_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_layer_norm_with_lengths_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_layout_under_torch_dispatch_mode_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_like_shape_empty_like_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_like_shape_randn_like_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_like_value_empty_like_cpu, 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test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_nested_tensor_from_jagged_fx_trace_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_nested_tensor_from_jagged_pass_min_max_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_nested_tensor_from_jagged_pass_min_max_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_njt_cat_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_noncontiguous_pointwise_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_noncontiguous_to_noncontig_transposed_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_noncontiguous_to_noncontig_transposed_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_noncontiguous_to_noncontig_transposed_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_noncontiguous_to_noncontig_with_holes_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_noncontiguous_to_noncontig_with_holes_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_noncontiguous_to_noncontig_with_holes_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_False_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_False_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_False_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_True_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_True_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_True_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_True_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_sum_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_sum_keepdim_False_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_sum_keepdim_False_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_sum_keepdim_False_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_sum_keepdim_True_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_sum_keepdim_True_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_sum_keepdim_True_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_sum_keepdim_True_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_1_different_output_shape_mean_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_1_different_output_shape_mean_keepdim_False_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_1_different_output_shape_mean_keepdim_False_requires_grad_True_components_require_grad_False_cpu_float32, 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test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_sum_keepdim_False_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_sum_keepdim_False_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_sum_keepdim_True_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_sum_keepdim_True_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_sum_keepdim_True_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_sum_keepdim_True_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_permute_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_pin_memory_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_profiler_sequence_nr_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_record_stream_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_reshape_decomp_requires_grad_False_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_reshape_decomp_requires_grad_True_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_autocast_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_backwards_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_backwards_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_compile_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_compile_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_flop_counter_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_with_constant_sequence_length_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_with_constant_sequence_length_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_with_constant_sequence_length_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_with_packed_in_proj_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_with_packed_in_proj_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_serialization_contig_weights_only_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_serialization_contig_weights_only_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_serialization_noncontig_transposed_weights_only_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_serialization_noncontig_transposed_weights_only_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_serialization_noncontig_with_holes_weights_only_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_serialization_noncontig_with_holes_weights_only_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_1_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_1_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_1_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_1_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_greater_than_1_same_output_shape_transpose_offset_1_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_greater_than_1_same_output_shape_transpose_offset_1_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_greater_than_1_same_output_shape_transpose_offset_1_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_greater_than_1_same_output_shape_transpose_offset_1_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_greater_than_1_same_output_shape_transpose_offset_2_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_greater_than_1_same_output_shape_transpose_offset_2_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_greater_than_1_same_output_shape_transpose_offset_2_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_greater_than_1_same_output_shape_transpose_offset_2_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_transpose_non_ragged_dim_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_transpose_non_ragged_dim_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_transpose_non_ragged_dim_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_transpose_non_ragged_dim_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_with_lengths_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_with_lengths_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_with_lengths_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_with_lengths_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_reduce_batch_dim_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_reduce_batch_dim_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_reduce_batch_dim_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_reduce_batch_dim_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_specialize_dynamic_shape_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_specialize_dynamic_shape_recompile_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_split_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_split_with_sizes_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_squeeze_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_batch_and_non_batch_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_batch_and_non_batch_keepdim_False_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_batch_and_non_batch_keepdim_False_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_batch_and_non_batch_keepdim_False_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_batch_and_non_batch_keepdim_True_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_batch_and_non_batch_keepdim_True_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_batch_and_non_batch_keepdim_True_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_batch_and_non_batch_keepdim_True_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_ragged_and_non_batch_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_ragged_and_non_batch_keepdim_False_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_ragged_and_non_batch_keepdim_False_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_ragged_and_non_batch_keepdim_False_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_ragged_and_non_batch_keepdim_True_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_ragged_and_non_batch_keepdim_True_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_ragged_and_non_batch_keepdim_True_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_ragged_and_non_batch_keepdim_True_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_tensor_attributes_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_threshold_backward_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_copy_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_dtype_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_2_requires_grad_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_2_requires_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_2_requires_grad_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_2_requires_grad_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_2_requires_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_2_requires_grad_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_3_requires_grad_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_3_requires_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_3_requires_grad_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_3_requires_grad_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_3_requires_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_3_requires_grad_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_4_requires_grad_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_4_requires_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_4_requires_grad_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_4_requires_grad_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_4_requires_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_4_requires_grad_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_2_requires_grad_False_cpu_bool, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_2_requires_grad_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_2_requires_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_2_requires_grad_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_2_requires_grad_True_cpu_bool, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_2_requires_grad_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_2_requires_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_2_requires_grad_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_3_requires_grad_False_cpu_bool, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_3_requires_grad_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_3_requires_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_3_requires_grad_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_3_requires_grad_True_cpu_bool, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_3_requires_grad_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_3_requires_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_3_requires_grad_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_4_requires_grad_False_cpu_bool, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_4_requires_grad_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_4_requires_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_4_requires_grad_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_4_requires_grad_True_cpu_bool, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_4_requires_grad_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_4_requires_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_4_requires_grad_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unary_pointwise_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unary_pointwise_transposed_inputs_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_backward_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_backward_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_backward_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_lengths_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_lengths_ragged_idx_0_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_lengths_ragged_idx_1_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_lengths_ragged_idx_2_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_lengths_ragged_idx_3_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_lengths_ragged_idx_equals_2_bad_dim_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_transpose_ragged_idx_2_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_transpose_ragged_idx_3_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_transpose_ragged_idx_last_dim_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unsafe_view_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_view_ragged_idx_not_one_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_views_inherit_ragged_dim_cpu, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward___radd___cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward___rdiv___cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward___rmod___cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward___rmul___cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward___rpow___cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward___rsub___cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_abs_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_acos_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_acosh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_add_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_amax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_amin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_angle_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_asin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_asinh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_atan2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_atan_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_atanh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_bfloat16_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_bmm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_cdouble_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_ceil_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_cfloat_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_chalf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_chunk_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_clamp_max_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_clamp_min_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_clone_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_complex_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_conj_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_conj_physical_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_copysign_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_cos_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_cosh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_deg2rad_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_digamma_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_div_floor_rounding_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_div_no_rounding_mode_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_div_trunc_rounding_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_double_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_erf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_erfc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_erfinv_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_exp2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_exp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_expm1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_fill_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_float_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_float_power_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_floor_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_fmax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_fmin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_fmod_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_frac_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_frexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_half_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_hypot_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_i0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_index_put_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_ldexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_lgamma_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_linalg_vector_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_log10_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_log1p_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_log2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_log_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_logaddexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_logit_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_amax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_amin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_logsumexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_mean_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_prod_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_select_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_std_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_sum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_var_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_matmul_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_max_binary_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_max_reduction_with_dim_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_maximum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_mean_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_min_binary_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_min_reduction_with_dim_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_minimum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_mul_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nan_to_num_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nanmean_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nansum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_narrow_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_neg_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_celu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_elu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_embedding_bag_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_embedding_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_hardshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_hardsigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_hardtanh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_linear_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_logsigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_mish_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_prelu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_relu6_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_relu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_rms_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_rrelu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_selu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_silu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_softplus_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_softshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_softsign_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_tanhshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_threshold_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_polar_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_polygamma_polygamma_n_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_polygamma_polygamma_n_1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_polygamma_polygamma_n_2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_polygamma_polygamma_n_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_polygamma_polygamma_n_4_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_positive_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_pow_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_prod_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_rad2deg_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_real_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_reciprocal_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_remainder_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_round_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_round_decimals_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_round_decimals_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_round_decimals_neg_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_rsqrt_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_rsub_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_select_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_sgn_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_sigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_sign_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_sin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_sinc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_sinh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_entr_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_erfcx_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_i0e_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_i1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_i1e_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_log_ndtr_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_ndtr_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_ndtri_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_xlog1py_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_split_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_split_with_sizes_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_sqrt_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_square_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_squeeze_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_std_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_std_unbiased_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_sub_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_sum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_tan_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_tanh_cpu_float32, 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test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_angle_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_asin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_asinh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_atan2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_atan_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_atanh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_bfloat16_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_bmm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_cdouble_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_ceil_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_cfloat_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_chalf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_chunk_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_clamp_max_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_clamp_min_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_clone_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_complex_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_conj_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_conj_physical_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_copysign_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_cos_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_cosh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_deg2rad_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_digamma_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_div_floor_rounding_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_div_no_rounding_mode_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_div_trunc_rounding_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_double_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_erf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_erfc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_erfinv_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_exp2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_exp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_expm1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_fill_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_float_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_float_power_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_floor_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_fmax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_fmin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_fmod_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_frac_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_frexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_half_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_hypot_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_i0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_index_put_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_ldexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_lgamma_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_linalg_vector_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_log10_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_log1p_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_log2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_log_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_logaddexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_logit_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_amax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_amin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_logsumexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_mean_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_prod_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_select_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_std_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_sum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_var_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_matmul_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_max_binary_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_max_reduction_with_dim_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_maximum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_mean_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_min_binary_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_min_reduction_with_dim_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_minimum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_mul_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nan_to_num_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nanmean_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nansum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_narrow_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_neg_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_celu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_elu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_embedding_bag_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_embedding_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_hardshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_hardsigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_hardtanh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_linear_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_logsigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_mish_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_prelu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_relu6_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_relu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_rms_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_rrelu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_selu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_silu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_softplus_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_softshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_softsign_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_tanhshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_threshold_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_polar_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_polygamma_polygamma_n_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_polygamma_polygamma_n_1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_polygamma_polygamma_n_2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_polygamma_polygamma_n_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_polygamma_polygamma_n_4_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_positive_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_pow_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_prod_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_rad2deg_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_real_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_reciprocal_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_remainder_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_round_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_round_decimals_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_round_decimals_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_round_decimals_neg_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_rsqrt_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_rsub_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_select_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sgn_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sign_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sinc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sinh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_entr_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_erfcx_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_i0e_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_i1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_i1e_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_log_ndtr_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_ndtr_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_ndtri_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_xlog1py_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_split_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_split_with_sizes_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sqrt_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_square_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_squeeze_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_std_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_std_unbiased_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sub_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_tan_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_tanh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_to_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_true_divide_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_trunc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_unflatten_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_unsqueeze_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_var_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_var_unbiased_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_where_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_xlogy_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward___radd___cpu_float32, 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test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_amax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_amin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_angle_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_any_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_argmax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_argmin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_asin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_asinh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_atan2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_atan_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_atanh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_bfloat16_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_bmm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_bool_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_byte_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_cdouble_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_ceil_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_cfloat_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_chalf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_char_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_chunk_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_clamp_max_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_clamp_min_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_clone_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_complex_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_conj_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_conj_physical_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_copysign_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_cos_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_cosh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_count_nonzero_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_deg2rad_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_digamma_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_div_floor_rounding_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_div_no_rounding_mode_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_div_trunc_rounding_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_double_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_eq_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_erf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_erfc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_erfinv_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_exp2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_exp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_expm1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_fill_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_float_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_float_power_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_floor_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_floor_divide_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_fmax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_fmin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_fmod_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_frac_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_frexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_ge_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_gt_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_half_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_heaviside_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_hypot_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_i0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_igamma_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_igammac_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_index_put_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_int_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_isclose_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_isfinite_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_isinf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_isnan_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_isneginf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_isposinf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_isreal_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_jiterator_binary_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_jiterator_binary_return_by_ref_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_jiterator_unary_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_ldexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_le_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_lgamma_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_linalg_vector_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_log10_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_log1p_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_log2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_log_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_logaddexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_logical_and_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_logical_not_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_logical_or_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_logical_xor_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_logit_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_long_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_lt_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_amax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_amin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_argmax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_argmin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_logsumexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_mean_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_prod_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_select_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_std_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_sum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_var_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_matmul_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_max_binary_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_max_reduction_with_dim_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_maximum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_mean_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_min_binary_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_min_reduction_with_dim_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_minimum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_mul_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nan_to_num_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nanmean_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nansum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_narrow_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_ne_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_neg_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nextafter_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_celu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_elu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_embedding_bag_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_embedding_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_hardshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_hardsigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_hardtanh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_linear_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_logsigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_mish_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_prelu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_relu6_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_relu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_rms_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_rrelu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_selu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_silu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_softplus_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_softshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_softsign_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_tanhshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_threshold_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_polar_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_polygamma_polygamma_n_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_polygamma_polygamma_n_1_cpu_float32, 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test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_softplus_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_softshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_softsign_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_tanhshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_threshold_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_polar_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_polygamma_polygamma_n_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_polygamma_polygamma_n_1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_polygamma_polygamma_n_2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_polygamma_polygamma_n_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_polygamma_polygamma_n_4_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_positive_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_pow_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_prod_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_rad2deg_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_real_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_reciprocal_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_remainder_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_round_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_round_decimals_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_round_decimals_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_round_decimals_neg_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_rsqrt_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_rsub_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_select_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_sgn_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_short_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_sigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_sign_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_signbit_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_sin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_sinc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_sinh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_airy_ai_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_bessel_j0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_bessel_j1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_bessel_y0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_bessel_y1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_chebyshev_polynomial_t_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_chebyshev_polynomial_u_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_chebyshev_polynomial_v_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_chebyshev_polynomial_w_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_entr_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_erfcx_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_hermite_polynomial_h_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_hermite_polynomial_he_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_i0e_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_i1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_i1e_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_laguerre_polynomial_l_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_legendre_polynomial_p_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_log_ndtr_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_modified_bessel_i0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_modified_bessel_i1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_modified_bessel_k0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_modified_bessel_k1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_ndtr_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_ndtri_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_scaled_modified_bessel_k0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_scaled_modified_bessel_k1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_spherical_bessel_j0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_xlog1py_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_zeta_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_split_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_split_with_sizes_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_sqrt_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_square_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_squeeze_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_std_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_std_unbiased_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_sub_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_sum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_tan_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_tanh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_to_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_true_divide_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_trunc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_unflatten_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_unsqueeze_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_var_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_var_unbiased_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_where_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_xlogy_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_nested_tensor_input_mutation_backward_cpu, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_nested_tensor_non_contiguous_mutation_cpu 2025-07-17T08:35:41.5438703Z 2025-07-17T08:35:44.6692542Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:35:44.6695413Z import pkg_resources 2025-07-17T08:35:44.7947772Z Running test_binary_ufuncs 2/4 ... [2025-07-17 08:35:44.794396] 2025-07-17T08:35:44.7948294Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:35:44.7950921Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_binary_ufuncs.py', '-m', 'not serial', '--shard-id=2', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:35:44.794786] 2025-07-17T08:38:08.7716900Z 2025-07-17T08:38:08.7718130Z functorch/test_vmap 1/4 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_1.4_306907e4e7fee953_.log 2025-07-17T08:38:08.7958444Z Running 495 items in this shard: test/functorch/test_vmap.py::TestVmapAPI::test_batch_rule_does_not_need_to_handle_no_batched_input, test/functorch/test_vmap.py::TestVmapAPI::test_fallback_masked_fill, test/functorch/test_vmap.py::TestVmapAPI::test_fallback_warning, test/functorch/test_vmap.py::TestVmapAPI::test_fallback_with_undefined_grad, test/functorch/test_vmap.py::TestVmapAPI::test_grad_unsupported_interaction, test/functorch/test_vmap.py::TestVmapAPI::test_in_dim_not_in_tensor_err_msg, test/functorch/test_vmap.py::TestVmapAPI::test_inplace_fallback_nary_different_levels, test/functorch/test_vmap.py::TestVmapAPI::test_item_throws, test/functorch/test_vmap.py::TestVmapAPI::test_multiple_inputs, test/functorch/test_vmap.py::TestVmapAPI::test_multiple_out_dims, test/functorch/test_vmap.py::TestVmapAPI::test_nested_with_same_map_dim, test/functorch/test_vmap.py::TestVmapAPI::test_non_zero_in_dims, test/functorch/test_vmap.py::TestVmapAPI::test_none_in_dims, test/functorch/test_vmap.py::TestVmapAPI::test_noop_in_inner_vmap, test/functorch/test_vmap.py::TestVmapAPI::test_out_dims_none_tuple, test/functorch/test_vmap.py::TestVmapAPI::test_out_dims_normal_tensor, test/functorch/test_vmap.py::TestVmapAPI::test_pytree_returns_broadcast_simple, test/functorch/test_vmap.py::TestVmapAPI::test_pytree_returns_outdims, test/functorch/test_vmap.py::TestVmapAPI::test_restore_vmap_no_vmapped_inputs, test/functorch/test_vmap.py::TestVmapAPI::test_single_input, test/functorch/test_vmap.py::TestVmapAPI::test_unsupported_op_err_msg, test/functorch/test_vmap.py::TestVmapAPI::test_vmap_autocast_cuda, test/functorch/test_vmap.py::TestVmapOperators::test_T_numpy, test/functorch/test_vmap.py::TestVmapOperators::test_adaptive_avg_pool2d, test/functorch/test_vmap.py::TestVmapOperators::test_arithmetic_div_dunder, test/functorch/test_vmap.py::TestVmapOperators::test_cat, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_0_out_dim_0_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_0_out_dim_1_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_0_out_dim_2_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_1_out_dim_2_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_2_out_dim_0_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_2_out_dim_0_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_2_out_dim_2_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_clone, test/functorch/test_vmap.py::TestVmapOperators::test_expand_as, test/functorch/test_vmap.py::TestVmapOperators::test_fill_and_zero_inplace, test/functorch/test_vmap.py::TestVmapOperators::test_mean, test/functorch/test_vmap.py::TestVmapOperators::test_mode_key, test/functorch/test_vmap.py::TestVmapOperators::test_t, test/functorch/test_vmap.py::TestVmapOperators::test_tensor_split, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_atan, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_floor, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_log10, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_neg, test/functorch/test_vmap.py::TestVmapOperators::test_unsqueeze, test/functorch/test_vmap.py::TestVmapOperators::test_view, test/functorch/test_vmap.py::TestVmapOperators::test_view_as, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_composition_in_dim_1_out_dim_0_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_error_in_dim_1_out_dim_0_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_0_out_dim_0_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_0_out_dim_1_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_0_out_dim_2_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_1_out_dim_0_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_1_out_dim_0_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_2_out_dim_2_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_fallback_check, test/functorch/test_vmap.py::TestVmapOperators::test_weird_matmul_case, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_batch_norm_training_False_track_running_stats_False_affine_False_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_conv_double_backward_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_inplace_on_view_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpyExpMarkDirtyAutogradFunction_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule___rmod___cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule__softmax_backward_data_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_addcdiv_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_addmm_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_addmv_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_amin_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_arange_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_argsort_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_baddbmm_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_bernoulli_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_bitwise_not_cpu_int64, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_bitwise_xor_cpu_int64, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_bool_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_bucketize_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_cauchy_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_ceil_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_cholesky_inverse_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_column_stack_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_combinations_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_constant_pad_nd_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_cov_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_cross_cpu_float32, 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test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_linalg_lu_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_linalg_lu_factor_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_linalg_matrix_norm_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_linalg_matrix_power_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_linalg_matrix_rank_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_linalg_solve_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_linalg_solve_ex_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_linalg_tensorsolve_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_linalg_vander_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_log10_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_log_normal_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_log_softmax_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_logaddexp2_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_logaddexp_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_logical_xor_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_logit_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_lu_solve_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_lu_unpack_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_masked_fill_functorch_Scalar_only_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_masked_log_softmax_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_masked_logaddexp_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_masked_norm_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_masked_scatter_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_masked_softmin_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_masked_std_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_masked_sum_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_matmul_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_max_binary_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_max_pool2d_with_indices_backward_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_max_reduction_no_dim_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_median_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_min_binary_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_minimum_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_multinomial_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_mvlgamma_mvlgamma_p_3_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_mvlgamma_mvlgamma_p_5_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_new_ones_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_adaptive_avg_pool3d_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_adaptive_max_pool2d_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_adaptive_max_pool3d_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_celu_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_conv1d_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_conv2d_no_bias_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_conv2d_stride_groups_with_bias_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_conv2d_strided_padding_dilation_no_bias_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_ctc_loss_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_elu_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_embedding_functorch_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_gaussian_nll_loss_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_hardsigmoid_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_hardtanh_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_interpolate_nearest-exact_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_local_response_norm_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_max_pool2d_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_max_unpool2d_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_nll_loss_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_one_hot_cpu_int64, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_pad_constant_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_pairwise_distance_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_silu_complex_cpu_complex64, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_silu_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_upsample_bilinear_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nn_functional_upsample_nearest_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_nonzero_static_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_normal_in_place_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_polygamma_polygamma_n_0_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_polygamma_polygamma_n_4_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_randn_like_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_ravel_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_remainder_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_repeat_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_resolve_conj_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_resolve_neg_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_scatter_add_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_scatter_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_scatter_reduce_mean_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_scatter_reduce_prod_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_scatter_reduce_sum_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_select_scatter_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_short_functorch_no_channels_last_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_sign_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_signal_windows_exponential_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_signal_windows_general_hamming_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_signal_windows_nuttall_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_sin_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_slice_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_special_bessel_j0_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_special_erfcx_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_special_i0e_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_special_modified_bessel_i1_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_special_modified_bessel_k0_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_special_xlog1py_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_tile_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_to_sparse_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_transpose_copy_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_transpose_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_triangular_solve_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_trunc_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_unbind_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_unflatten_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_unfold_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_unique_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_unravel_index_cpu_int64, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_var_mean_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_var_mean_unbiased_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_view_copy_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_xlogy_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_zero__cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_cond_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_eig_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_eigh_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_lu_solve_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_matrix_power_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_pinv_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_svdvals_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_vander_cpu_float32, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_inplace_manyview_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_log1p_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_median_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_mul_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_randomness_backend0_randomness_same_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_select_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_stack_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_where_cpu, test/functorch/test_vmap.py::TestTransformFailureCPU::test_fails_with_autograd_function_transform_grad_and_value_cpu, test/functorch/test_vmap.py::TestTransformFailureCPU::test_fails_with_autograd_function_transform_jvp_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_alpha_dropout_randomness_error_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_different_batched_input_first_batched_probability_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_same_batched_input_last_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_same_batched_input_last_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_different_batched_input_none_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_different_batched_input_none_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_error_batched_input_first_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_error_batched_input_none_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_same_batched_input_first_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_same_batched_input_last_batched_probability_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_same_batched_input_none_batched_probability_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_chunk_vmap_in_dim_0_out_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_chunk_vmap_in_dim_2_out_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_dropout_randomness_error_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_dropout_randomness_error_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_dropout_randomness_same_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_dropout_randomness_same_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_factory_ops_randomness_different_use_generator_True_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_factory_ops_randomness_same_use_generator_False_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_alpha_dropout_randomness_different_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_alpha_dropout_randomness_error_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_alpha_dropout_randomness_same_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_different_batched_input_first_dim_3_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_different_batched_input_none_dim_3_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_error_batched_input_first_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_same_batched_input_last_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_same_batched_input_none_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_like_functions_randomness_error_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_like_functions_randomness_same_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_multinomial_use_generator_False_randomness_error_batched_call_False_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_multinomial_use_generator_False_randomness_same_batched_call_True_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_multinomial_use_generator_True_randomness_different_batched_call_True_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_multinomial_use_generator_True_randomness_error_batched_call_False_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_False_randomness_different_batched_input_first_batched_other_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_False_randomness_error_batched_input_last_batched_other_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_False_randomness_same_batched_input_first_batched_other_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_False_randomness_same_batched_input_last_batched_other_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_False_randomness_same_batched_input_none_batched_other_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_different_batched_input_last_batched_other_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_error_batched_input_first_batched_other_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_error_batched_input_first_batched_other_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_error_batched_input_last_batched_other_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_error_batched_input_none_batched_other_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_same_batched_input_last_batched_other_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_same_batched_input_none_batched_other_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_unary_inplace_use_generator_False_randomness_different_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_unary_inplace_use_generator_False_randomness_different_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_unary_inplace_use_generator_True_randomness_different_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_unary_inplace_use_generator_True_randomness_different_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_unary_inplace_use_generator_True_randomness_error_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_unary_out_of_place_use_generator_False_randomness_different_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_unary_out_of_place_use_generator_False_randomness_different_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_unary_out_of_place_use_generator_False_randomness_different_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_unary_out_of_place_use_generator_False_randomness_error_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_unary_out_of_place_use_generator_False_randomness_same_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_unary_out_of_place_use_generator_True_randomness_same_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_randperm_randomness_different_use_generator_True_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_randperm_randomness_same_use_generator_False_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_vmap_chunksize_in_dim_1_out_dim_0_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_vmap_chunksize_in_dim_1_out_dim_2_cpu, test/functorch/test_vmap.py::TestVmapDeviceTypeCPU::test_check_tensor_cpu, test/functorch/test_vmap.py::TestVmapNestedTensorCPU::test_fallback_binary_cpu, test/functorch/test_vmap.py::TestVmapNestedTensorCPU::test_fallback_binary_nt_and_batched_dense_cpu, test/functorch/test_vmap.py::TestVmapNestedTensorCPU::test_fallback_unary_cpu, test/functorch/test_vmap.py::TestVmapNestedTensorCPU::test_fallback_with_nt_and_batched_dense_with_nonzero_bdim_raises_cpu, test/functorch/test_vmap.py::TestVmapNestedTensorCPU::test_multilevel_vmap_raises_cpu, test/functorch/test_vmap.py::TestVmapNestedTensorCPU::test_nt_acts_as_dense_in_vmap_cpu 2025-07-17T08:38:08.8188775Z 2025-07-17T08:38:09.5133291Z Uploading artifacts took 0.74 seconds 2025-07-17T08:38:11.9568417Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:38:11.9571503Z import pkg_resources 2025-07-17T08:38:12.0820221Z Running test_foreach 1/1 ... [2025-07-17 08:38:12.081587] 2025-07-17T08:38:12.0820887Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:38:12.0823185Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_foreach.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:38:12.081975] 2025-07-17T08:40:54.2691142Z 2025-07-17T08:40:54.2692081Z test_binary_ufuncs 1/4 was successful, full logs can be found in artifacts with path test/test-reports/test_binary_ufuncs_1.4_a7f4b069db30e6fc_.log 2025-07-17T08:40:54.4096125Z Running 3161 items in this shard: test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___eq___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___gt___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iadd___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iadd___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ilshift___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ilshift___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imul___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imul___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imul___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imul___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ior___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___irshift___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___isub___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___isub___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___isub___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___itruediv___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___itruediv___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ixor___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ixor___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___le___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___le___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___lt___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___lt___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___lt___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___matmul___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___matmul___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___matmul___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___mod___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___mod___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___mul___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___mul___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ne___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ne___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___or___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___pow___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___pow___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___radd___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rand___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rand___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rlshift___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rlshift___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmatmul___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmod___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmod___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmul___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmul___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ror___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ror___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rpow___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rpow___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rrshift___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rshift___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rshift___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rsub___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rsub___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rsub___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rtruediv___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rtruediv___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___sub___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___sub___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___truediv___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___truediv___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___xor___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___xor___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___xor___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___xor___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___xor___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___xor___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_add_with_tail_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_addcmul_scalars_as_floats_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___radd___cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___radd___cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rand___cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rdiv___cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rmod___cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rmul___cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rmul___cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rmul___cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rmul___cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rmul___cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___ror___cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rpow___cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rpow___cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rsub___cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rsub___cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rsub___cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rxor___cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___rxor___cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_complex_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_polar_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing__refs_add_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing__refs_add_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing__refs_add_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing__refs_atan2_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing__refs_atan2_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing__refs_bitwise_and_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing__refs_bitwise_or_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing__refs_bitwise_or_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing__refs_bitwise_right_shift_cpu_int32, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_chebyshev_polynomial_w_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_chebyshev_polynomial_w_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_u_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_v_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_v_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_v_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_xlog1py_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_xlog1py_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_xlog1py_cpu_int8, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_copysign_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_copysign_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_div_floor_rounding_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_div_no_rounding_mode_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_div_no_rounding_mode_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_div_no_rounding_mode_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_div_no_rounding_mode_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_div_trunc_rounding_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_div_trunc_rounding_cpu_float32, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_le_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_le_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_le_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logaddexp_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_and_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_and_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_and_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_or_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_or_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_or_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_xor_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_xor_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_xor_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_lt_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_maximum_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_maximum_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_maximum_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_maximum_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_minimum_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_minimum_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_minimum_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_minimum_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_mul_cpu_complex32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_mul_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_ne_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_ne_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_ne_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_pow_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_pow_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_pow_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_remainder_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_remainder_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_remainder_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_rsub_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_special_xlog1py_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_special_xlog1py_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_special_xlog1py_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_special_zeta_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_sub_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_sub_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_sub_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_true_divide_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_true_divide_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_true_divide_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_true_divide_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_xlogy_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_add_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_add_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_and_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_left_shift_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_xor_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_xor_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_min_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_min_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_copysign_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_copysign_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_copysign_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_complex32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_floor_divide_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmod_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gcd_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gcd_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gcd_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_heaviside_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_hypot_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_igammac_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lcm_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logaddexp_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_nextafter_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_nextafter_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_polar_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_t_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_t_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_t_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_u_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_v_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_v_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_w_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_hermite_polynomial_h_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_hermite_polynomial_h_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_hermite_polynomial_he_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_laguerre_polynomial_l_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_laguerre_polynomial_l_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_legendre_polynomial_p_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_t_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_t_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_v_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_v_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_v_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_w_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_w_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_xlog1py_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_zeta_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_zeta_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_zeta_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_zeta_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_zeta_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_sub_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_sub_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_sub_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_true_divide_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_true_divide_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_true_divide_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_xlogy_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_xlogy_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_xlogy_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_xlogy_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_xlogy_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bfloat16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bfloat16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bfloat16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bfloat16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bool_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bool_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bool_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_bfloat16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_cpow_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_cremainder_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_and_floordiv_script_vs_python_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_nonfinite_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_float32, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_scalar_pow_float_tensor_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_tensor_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_zero_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_zero_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_float_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_float_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_integral_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_idiv_and_ifloordiv_vs_python_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_inplace_division_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lcm_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_weight_scalar_tensor_promotion_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logaddexp2_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logaddexp_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logaddexp_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_bfloat16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_bfloat16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_bfloat16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_bfloat16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_bool_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_bool_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_bool_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex128_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex128_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex128_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex128_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex128_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex128_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex64_bool, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_int32_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_int32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_int32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_int32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_int64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_int64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_int64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_int8_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_int8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_int8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_int8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_uint8_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_uint8_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_uint8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_uint8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_uint8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_uint8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_float32, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_type_promotion_special_shifted_chebyshev_polynomial_w_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_type_promotion_special_xlog1py_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_type_promotion_special_zeta_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_bool_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_bool_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_bool_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float32_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_uint8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_uint8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_bool_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_uint8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_uint8_uint8 2025-07-17T08:40:54.5355482Z 2025-07-17T08:40:57.5702549Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:40:57.5705226Z import pkg_resources 2025-07-17T08:40:57.6963121Z Running dynamo/cpython/3_13/test_generator_stop 1/1 ... [2025-07-17 08:40:57.695884] 2025-07-17T08:40:57.6964086Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:40:57.6966644Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_generator_stop.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:40:57.696302] 2025-07-17T08:41:02.2176102Z 2025-07-17T08:41:02.2177563Z dynamo/cpython/3_13/test_generator_stop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_generator_stop_1.1_e7a15a074a1b5bce_.log 2025-07-17T08:41:02.2180347Z Running 2 items in this shard: test/dynamo/cpython/3_13/test_generator_stop.py::TestPEP479::test_stopiteration_wrapping, test/dynamo/cpython/3_13/test_generator_stop.py::TestPEP479::test_stopiteration_wrapping_context 2025-07-17T08:41:02.2181324Z 2025-07-17T08:41:05.5070552Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:41:05.5073922Z import pkg_resources 2025-07-17T08:41:05.6477028Z Running dynamo/cpython/3_13/test_exception_variations 1/1 ... [2025-07-17 08:41:05.647296] 2025-07-17T08:41:05.6478061Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:41:05.6480107Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_exception_variations.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:41:05.647672] 2025-07-17T08:41:06.9608366Z 2025-07-17T08:41:06.9609607Z test_foreach 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_foreach_1.1_0754c8b89921aaa8_.log 2025-07-17T08:41:07.1111866Z Running 3577 items in this shard: test/test_foreach.py::TestForeachCPU::test_0dim_tensor_overload_cpu_ok_cpu, test/test_foreach.py::TestForeachCPU::test_0dim_tensor_overload_exception_cpu, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_bfloat16, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_complex64, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_float16, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_float32, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_float64, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_int16, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_int32, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_int64, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_int8, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_uint8, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_abs_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_acos_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_add_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_addcdiv_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_addcmul_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_asin_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_atan_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_ceil_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_clamp_max_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_clamp_min_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_copy_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_cos_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_cosh_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_div_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_erf_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_erfc_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_exp_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_expm1_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_floor_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_frac_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_lerp_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_lgamma_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log10_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log1p_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log2_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_max_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_maximum_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_minimum_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_mul_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_neg_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_norm_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_pow_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_reciprocal_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_round_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_rsqrt_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sigmoid_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sign_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sin_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sinh_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sqrt_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sub_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_tan_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_tanh_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_trunc_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_zero_cpu_float32, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_abs_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_abs_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_abs_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_abs_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_acos_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_acos_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_acos_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_acos_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_add_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_add_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_add_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_add_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcdiv_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcdiv_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcdiv_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcdiv_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcmul_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcmul_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcmul_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcmul_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_asin_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_asin_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_asin_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_asin_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_atan_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_atan_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_atan_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_atan_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_ceil_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_ceil_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_ceil_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_ceil_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_max_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_max_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_max_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_max_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_min_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_min_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_min_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_min_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_copy_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_copy_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_copy_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_copy_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_cos_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_cos_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_cos_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_cos_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_cosh_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_cosh_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_cosh_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_cosh_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_div_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_div_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_div_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_div_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_erf_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_erf_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_erf_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_erf_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_erfc_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_erfc_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_erfc_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_erfc_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_exp_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_exp_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_exp_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_exp_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_expm1_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_expm1_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_expm1_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_expm1_outplace_cpu_float64, 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test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sigmoid_cpu_uint8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_bfloat16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_bool, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_complex64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_float16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_float32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_float64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_int16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_int32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_int64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_int8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sign_cpu_uint8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_bfloat16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_bool, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_complex64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_float16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_float32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_float64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_int16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_int32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_int64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_int8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sin_cpu_uint8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_bfloat16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_bool, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_complex64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_float16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_float32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_float64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_int16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_int32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_int64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_int8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sinh_cpu_uint8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_bfloat16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_bool, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_complex64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_float16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_float32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_float64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_int16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_int32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_int64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_int8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_sqrt_cpu_uint8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_bfloat16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_bool, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_complex64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_float16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_float32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_float64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_int16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_int32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_int64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_int8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tan_cpu_uint8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_bfloat16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_bool, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_complex64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_float16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_float32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_float64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_int16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_int32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_int64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_int8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_tanh_cpu_uint8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_bfloat16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_bool, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_complex64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_float16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_float32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_float64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_int16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_int32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_int64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_int8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_trunc_cpu_uint8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_bfloat16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_bool, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_complex64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_float16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_float32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_float64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_int16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_int32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_int64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_int8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_uint8 2025-07-17T08:41:07.2575661Z 2025-07-17T08:41:10.2330626Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:41:10.2333731Z import pkg_resources 2025-07-17T08:41:10.3588744Z Running dynamo/cpython/3_13/test_int_literal 1/1 ... [2025-07-17 08:41:10.358414] 2025-07-17T08:41:10.3589563Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:41:10.3591691Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_int_literal.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:41:10.358800] 2025-07-17T08:41:10.8207313Z 2025-07-17T08:41:10.8209213Z dynamo/cpython/3_13/test_exception_variations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_exception_variations_1.1_bee4fc5dc7d3b634_.log 2025-07-17T08:41:10.8222948Z Running 15 items in this shard: test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_nested, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_nested_else, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_nested_exception_in_else, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_nested_exception_in_except, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_nested_exception_in_finally_no_exception, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_nested_exception_in_finally_with_exception, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_try_except, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_try_except_else, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_try_except_else_finally, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_try_except_else_finally_no_exception, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_try_except_else_no_exception, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_try_except_finally, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_try_except_finally_no_exception, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_try_except_no_exception, test/dynamo/cpython/3_13/test_exception_variations.py::ExceptTestCases::test_try_finally_no_exception 2025-07-17T08:41:10.8234971Z 2025-07-17T08:41:14.0455816Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:41:14.0458658Z import pkg_resources 2025-07-17T08:41:14.1709905Z Running dynamo/cpython/3_13/test_with 1/1 ... [2025-07-17 08:41:14.170563] 2025-07-17T08:41:14.1710746Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:41:14.1713419Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_with.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:41:14.171007] 2025-07-17T08:41:15.0821959Z 2025-07-17T08:41:15.0823427Z dynamo/cpython/3_13/test_int_literal 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_int_literal_1.1_9aa098ec04fde125_.log 2025-07-17T08:41:15.0828355Z Running 6 items in this shard: test/dynamo/cpython/3_13/test_int_literal.py::TestHexOctBin::test_bin_baseline, test/dynamo/cpython/3_13/test_int_literal.py::TestHexOctBin::test_bin_unsigned, test/dynamo/cpython/3_13/test_int_literal.py::TestHexOctBin::test_hex_baseline, test/dynamo/cpython/3_13/test_int_literal.py::TestHexOctBin::test_hex_unsigned, test/dynamo/cpython/3_13/test_int_literal.py::TestHexOctBin::test_oct_baseline, test/dynamo/cpython/3_13/test_int_literal.py::TestHexOctBin::test_oct_unsigned 2025-07-17T08:41:15.0832281Z 2025-07-17T08:41:18.3243901Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:41:18.3246903Z import pkg_resources 2025-07-17T08:41:18.4505519Z Running dynamo/cpython/3_13/test_numeric_tower 1/1 ... [2025-07-17 08:41:18.450070] 2025-07-17T08:41:18.4506450Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:41:18.4508579Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_numeric_tower.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:41:18.450488] 2025-07-17T08:41:20.8964891Z 2025-07-17T08:41:20.8966570Z dynamo/cpython/3_13/test_with 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_with_1.1_a634dd9680e0ed3a_.log 2025-07-17T08:41:20.9001075Z Running 51 items in this shard: test/dynamo/cpython/3_13/test_with.py::FailureTestCase::testAssignmentToNoneError, test/dynamo/cpython/3_13/test_with.py::FailureTestCase::testAssignmentToTupleContainingNoneError, test/dynamo/cpython/3_13/test_with.py::FailureTestCase::testAssignmentToTupleOnlyContainingNoneError, test/dynamo/cpython/3_13/test_with.py::FailureTestCase::testEnterAttributeError1, test/dynamo/cpython/3_13/test_with.py::FailureTestCase::testEnterAttributeError2, test/dynamo/cpython/3_13/test_with.py::FailureTestCase::testEnterThrows, test/dynamo/cpython/3_13/test_with.py::FailureTestCase::testExitAttributeError, test/dynamo/cpython/3_13/test_with.py::FailureTestCase::testExitThrows, test/dynamo/cpython/3_13/test_with.py::FailureTestCase::testNameError, test/dynamo/cpython/3_13/test_with.py::NonexceptionalTestCase::testBoundGenerator, test/dynamo/cpython/3_13/test_with.py::NonexceptionalTestCase::testInlineGeneratorBoundSyntax, test/dynamo/cpython/3_13/test_with.py::NonexceptionalTestCase::testInlineGeneratorBoundToDottedVariable, test/dynamo/cpython/3_13/test_with.py::NonexceptionalTestCase::testInlineGeneratorBoundToExistingVariable, test/dynamo/cpython/3_13/test_with.py::NonexceptionalTestCase::testInlineGeneratorSyntax, test/dynamo/cpython/3_13/test_with.py::NonexceptionalTestCase::testNestedSingleStatements, test/dynamo/cpython/3_13/test_with.py::NonexceptionalTestCase::testUnboundGenerator, test/dynamo/cpython/3_13/test_with.py::NestedNonexceptionalTestCase::testMultipleArgBound, test/dynamo/cpython/3_13/test_with.py::NestedNonexceptionalTestCase::testMultipleArgUnbound, test/dynamo/cpython/3_13/test_with.py::NestedNonexceptionalTestCase::testSingleArgBoundToMultipleElementTupleError, test/dynamo/cpython/3_13/test_with.py::NestedNonexceptionalTestCase::testSingleArgBoundToNonTuple, test/dynamo/cpython/3_13/test_with.py::NestedNonexceptionalTestCase::testSingleArgBoundToSingleElementParenthesizedList, test/dynamo/cpython/3_13/test_with.py::NestedNonexceptionalTestCase::testSingleArgInlineGeneratorSyntax, test/dynamo/cpython/3_13/test_with.py::NestedNonexceptionalTestCase::testSingleArgUnbound, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testErrorsInBool, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testExceptionNormalized, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testMultipleResourcesInSingleStatement, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testNestedExceptionAfterInnerStatement, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testNestedExceptionBeforeInnerStatement, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testNestedSingleStatements, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testRaisedGeneratorExit1, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testRaisedGeneratorExit2, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testRaisedStopIteration1, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testRaisedStopIteration2, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testRaisedStopIteration3, test/dynamo/cpython/3_13/test_with.py::ExceptionalTestCase::testSingleResource, test/dynamo/cpython/3_13/test_with.py::NonLocalFlowControlTestCase::testWithBreak, test/dynamo/cpython/3_13/test_with.py::NonLocalFlowControlTestCase::testWithContinue, test/dynamo/cpython/3_13/test_with.py::NonLocalFlowControlTestCase::testWithRaise, test/dynamo/cpython/3_13/test_with.py::NonLocalFlowControlTestCase::testWithReturn, test/dynamo/cpython/3_13/test_with.py::NonLocalFlowControlTestCase::testWithYield, test/dynamo/cpython/3_13/test_with.py::AssignmentTargetTestCase::testMultipleComplexTargets, test/dynamo/cpython/3_13/test_with.py::AssignmentTargetTestCase::testSingleComplexTarget, test/dynamo/cpython/3_13/test_with.py::AssignmentTargetTestCase::testWithExtendedTargets, test/dynamo/cpython/3_13/test_with.py::ExitSwallowsExceptionTestCase::testExitFalseDoesntSwallowException, test/dynamo/cpython/3_13/test_with.py::ExitSwallowsExceptionTestCase::testExitTrueSwallowsException, test/dynamo/cpython/3_13/test_with.py::NestedWith::testEnterReturnsTuple, test/dynamo/cpython/3_13/test_with.py::NestedWith::testExceptionInEnter, test/dynamo/cpython/3_13/test_with.py::NestedWith::testExceptionInExit, test/dynamo/cpython/3_13/test_with.py::NestedWith::testExceptionInExprList, test/dynamo/cpython/3_13/test_with.py::NestedWith::testExceptionLocation, test/dynamo/cpython/3_13/test_with.py::NestedWith::testNoExceptions 2025-07-17T08:41:20.9038634Z 2025-07-17T08:41:23.1231403Z 2025-07-17T08:41:23.1232934Z dynamo/cpython/3_13/test_numeric_tower 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_numeric_tower_1.1_100306afa6706526_.log 2025-07-17T08:41:23.1237000Z Running 9 items in this shard: test/dynamo/cpython/3_13/test_numeric_tower.py::HashTest::test_binary_floats, test/dynamo/cpython/3_13/test_numeric_tower.py::HashTest::test_bools, test/dynamo/cpython/3_13/test_numeric_tower.py::HashTest::test_complex, test/dynamo/cpython/3_13/test_numeric_tower.py::HashTest::test_decimals, test/dynamo/cpython/3_13/test_numeric_tower.py::HashTest::test_fractions, test/dynamo/cpython/3_13/test_numeric_tower.py::HashTest::test_hash_normalization, test/dynamo/cpython/3_13/test_numeric_tower.py::HashTest::test_integers, test/dynamo/cpython/3_13/test_numeric_tower.py::ComparisonTest::test_complex, test/dynamo/cpython/3_13/test_numeric_tower.py::ComparisonTest::test_mixed_comparisons 2025-07-17T08:41:23.1240072Z 2025-07-17T08:41:24.1491411Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:41:24.1494376Z import pkg_resources 2025-07-17T08:41:24.3008242Z Running dynamo/cpython/3_13/test_ordered_dict 1/1 ... [2025-07-17 08:41:24.300396] 2025-07-17T08:41:24.3009221Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:41:24.3011982Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_ordered_dict.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:41:24.300832] 2025-07-17T08:41:26.3595205Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:41:26.3597450Z import pkg_resources 2025-07-17T08:41:26.4857722Z Running dynamo/cpython/3_13/test_baseexception 1/1 ... [2025-07-17 08:41:26.485288] 2025-07-17T08:41:26.4858371Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:41:26.4860029Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_baseexception.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:41:26.485665] 2025-07-17T08:41:31.1570140Z 2025-07-17T08:41:31.1571824Z dynamo/cpython/3_13/test_baseexception 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_baseexception_1.1_82f9f185f3e64b4e_.log 2025-07-17T08:41:31.1581187Z Running 11 items in this shard: test/dynamo/cpython/3_13/test_baseexception.py::ExceptionClassTests::test_builtins_new_style, test/dynamo/cpython/3_13/test_baseexception.py::ExceptionClassTests::test_inheritance, test/dynamo/cpython/3_13/test_baseexception.py::ExceptionClassTests::test_interface_multi_arg, test/dynamo/cpython/3_13/test_baseexception.py::ExceptionClassTests::test_interface_no_arg, test/dynamo/cpython/3_13/test_baseexception.py::ExceptionClassTests::test_interface_single_arg, test/dynamo/cpython/3_13/test_baseexception.py::ExceptionClassTests::test_setstate_refcount_no_crash, test/dynamo/cpython/3_13/test_baseexception.py::UsageTests::test_catch_BaseException_instance, test/dynamo/cpython/3_13/test_baseexception.py::UsageTests::test_catch_non_BaseException, test/dynamo/cpython/3_13/test_baseexception.py::UsageTests::test_catch_string, test/dynamo/cpython/3_13/test_baseexception.py::UsageTests::test_raise_new_style_non_exception, test/dynamo/cpython/3_13/test_baseexception.py::UsageTests::test_raise_string 2025-07-17T08:41:31.1589535Z 2025-07-17T08:41:34.3337247Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:41:34.3340072Z import pkg_resources 2025-07-17T08:41:34.4588390Z Running dynamo/cpython/3_13/test_int 1/1 ... [2025-07-17 08:41:34.458336] 2025-07-17T08:41:34.4589342Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:41:34.4591173Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_int.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:41:34.458717] 2025-07-17T08:41:41.9349354Z 2025-07-17T08:41:41.9351000Z dynamo/cpython/3_13/test_int 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_int_1.1_c1c3fe4e32b0d03c_.log 2025-07-17T08:41:41.9371091Z Running 46 items in this shard: test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_basic, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_error_message, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_int_base_bad_types, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_int_base_indexable, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_int_base_limits, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_int_memoryview, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_int_returns_int_subclass, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_int_subclass_with_index, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_int_subclass_with_int, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_intconversion, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_invalid_signs, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_issue31619, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_keyword_args, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_no_args, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_non_numeric_input_types, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_small_ints, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_string_float, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_underscores, test/dynamo/cpython/3_13/test_int.py::IntTestCases::test_unicode, test/dynamo/cpython/3_13/test_int.py::IntStrDigitLimitsTests::test_denial_of_service_prevented_int_to_str, test/dynamo/cpython/3_13/test_int.py::IntStrDigitLimitsTests::test_denial_of_service_prevented_str_to_int, test/dynamo/cpython/3_13/test_int.py::IntStrDigitLimitsTests::test_disabled_limit, test/dynamo/cpython/3_13/test_int.py::IntStrDigitLimitsTests::test_int_from_other_bases, test/dynamo/cpython/3_13/test_int.py::IntStrDigitLimitsTests::test_int_max_str_digits_is_per_interpreter, test/dynamo/cpython/3_13/test_int.py::IntStrDigitLimitsTests::test_max_str_digits, test/dynamo/cpython/3_13/test_int.py::IntStrDigitLimitsTests::test_max_str_digits_edge_cases, test/dynamo/cpython/3_13/test_int.py::IntStrDigitLimitsTests::test_power_of_two_bases_unlimited, test/dynamo/cpython/3_13/test_int.py::IntStrDigitLimitsTests::test_sign_not_counted, test/dynamo/cpython/3_13/test_int.py::IntStrDigitLimitsTests::test_underscores_ignored, test/dynamo/cpython/3_13/test_int.py::IntSubclassStrDigitLimitsTests::test_denial_of_service_prevented_int_to_str, test/dynamo/cpython/3_13/test_int.py::IntSubclassStrDigitLimitsTests::test_denial_of_service_prevented_str_to_int, test/dynamo/cpython/3_13/test_int.py::IntSubclassStrDigitLimitsTests::test_disabled_limit, test/dynamo/cpython/3_13/test_int.py::IntSubclassStrDigitLimitsTests::test_int_from_other_bases, test/dynamo/cpython/3_13/test_int.py::IntSubclassStrDigitLimitsTests::test_int_max_str_digits_is_per_interpreter, test/dynamo/cpython/3_13/test_int.py::IntSubclassStrDigitLimitsTests::test_max_str_digits, test/dynamo/cpython/3_13/test_int.py::IntSubclassStrDigitLimitsTests::test_max_str_digits_edge_cases, test/dynamo/cpython/3_13/test_int.py::IntSubclassStrDigitLimitsTests::test_power_of_two_bases_unlimited, test/dynamo/cpython/3_13/test_int.py::IntSubclassStrDigitLimitsTests::test_sign_not_counted, test/dynamo/cpython/3_13/test_int.py::IntSubclassStrDigitLimitsTests::test_underscores_ignored, test/dynamo/cpython/3_13/test_int.py::PyLongModuleTests::test_pylong_int_divmod, test/dynamo/cpython/3_13/test_int.py::PyLongModuleTests::test_pylong_int_to_decimal, test/dynamo/cpython/3_13/test_int.py::PyLongModuleTests::test_pylong_int_to_decimal_2, test/dynamo/cpython/3_13/test_int.py::PyLongModuleTests::test_pylong_misbehavior_error_path_from_str, test/dynamo/cpython/3_13/test_int.py::PyLongModuleTests::test_pylong_misbehavior_error_path_to_str, test/dynamo/cpython/3_13/test_int.py::PyLongModuleTests::test_pylong_roundtrip, test/dynamo/cpython/3_13/test_int.py::PyLongModuleTests::test_pylong_str_to_int 2025-07-17T08:41:41.9389474Z 2025-07-17T08:41:42.0449333Z 2025-07-17T08:41:42.0450512Z dynamo/cpython/3_13/test_ordered_dict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_ordered_dict_1.1_163b2e48a14935a6_.log 2025-07-17T08:41:42.0695889Z Running 295 items in this shard: test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_468, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_abc, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_clear, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_copying, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_delitem, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_delitem_hash_collision, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_detect_deletion_during_iteration, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_dict_clear, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_dict_delitem, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_dict_pop, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_dict_popitem, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_dict_setdefault, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_dict_setitem, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_dict_update, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_equality, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_free_after_iterating, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_fromkeys, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_highly_nested, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_highly_nested_subclass, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_init, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_init_calls, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_issue119004_attribute_error, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_issue24347, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_issue24348, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_issue24667, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_iterators, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_iterators_empty, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_merge_operator, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_move_to_end, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_move_to_end_issue25406, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_ordered_dict_items_result_gc, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_overridden_init, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_override_update, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_pickle_recursive, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_pop, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_popitem, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_popitem_last, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_reduce_not_too_fat, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_reference_loop, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_reinsert, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_repr, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_repr_recursive, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_repr_recursive_values, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_setdefault, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_setitem, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_sizeof, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_sorted_iterators, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_update, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_views, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonOrderedDictTests::test_yaml_linkage, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_abc, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_clear, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_delitem, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_delitem_hash_collision, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_detect_deletion_during_iteration, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_highly_nested, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_highly_nested_subclass, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_init, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_override_update, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_popitem, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_reinsert, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_setitem, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonBuiltinDictTests::test_update, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_468, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_abc, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_clear, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_copying, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_delitem, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_delitem_hash_collision, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_detect_deletion_during_iteration, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_dict_clear, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_dict_delitem, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_dict_pop, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_dict_popitem, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_dict_setdefault, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_dict_setitem, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_dict_update, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_equality, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_free_after_iterating, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_fromkeys, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_highly_nested, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_highly_nested_subclass, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_init, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonOrderedDictTests::test_init_calls, 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test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonGeneralMappingTests::test_write, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_bool, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_constructor, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_get, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_getitem, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_items, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_keys, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_len, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_pop, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_popitem, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_read, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_setdefault, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_update, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_values, test/dynamo/cpython/3_13/test_ordered_dict.py::PurePythonSubclassMappingTests::test_write, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_bool, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_constructor, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_get, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_getitem, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_items, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_keys, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_len, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_pop, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_popitem, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_read, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_setdefault, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_update, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_values, test/dynamo/cpython/3_13/test_ordered_dict.py::CPythonSubclassMappingTests::test_write, test/dynamo/cpython/3_13/test_ordered_dict.py::PySimpleLRUCacheTests::test_add_after_full, test/dynamo/cpython/3_13/test_ordered_dict.py::PySimpleLRUCacheTests::test_change_order_on_get, test/dynamo/cpython/3_13/test_ordered_dict.py::PySimpleLRUCacheTests::test_pop, test/dynamo/cpython/3_13/test_ordered_dict.py::PySimpleLRUCacheTests::test_popitem, test/dynamo/cpython/3_13/test_ordered_dict.py::CSimpleLRUCacheTests::test_add_after_full, test/dynamo/cpython/3_13/test_ordered_dict.py::CSimpleLRUCacheTests::test_change_order_on_get, test/dynamo/cpython/3_13/test_ordered_dict.py::CSimpleLRUCacheTests::test_pop, test/dynamo/cpython/3_13/test_ordered_dict.py::CSimpleLRUCacheTests::test_popitem 2025-07-17T08:41:42.0897737Z 2025-07-17T08:41:45.1324889Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:41:45.1326741Z import pkg_resources 2025-07-17T08:41:45.2579437Z Running dynamo/cpython/3_13/test_itertools 1/1 ... [2025-07-17 08:41:45.257591] 2025-07-17T08:41:45.2580138Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:41:45.2582710Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_itertools.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:41:45.257974] 2025-07-17T08:41:45.2812802Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:41:45.2815646Z import pkg_resources 2025-07-17T08:41:45.4088287Z Running dynamo/cpython/3_13/test_userlist 1/1 ... [2025-07-17 08:41:45.408402] 2025-07-17T08:41:45.4088983Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:41:45.4091080Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_userlist.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:41:45.408803] 2025-07-17T08:41:51.1330039Z 2025-07-17T08:41:51.1331631Z dynamo/cpython/3_13/test_userlist 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_userlist_1.1_ebc2e114929efe02_.log 2025-07-17T08:41:51.1349773Z Running 51 items in this shard: test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_add_specials, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_addmul, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_append, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_bigrepeat, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_clear, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_constructor_exception_handling, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_constructors, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_contains, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_contains_fake, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_contains_order, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_copy, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_count, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_delitem, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_delslice, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_exhausted_iterator, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_extend, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_extendedslicing, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_free_after_iterating, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_getitem, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_getitem_error, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_getitemoverwriteiter, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_getslice, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_iadd, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_imul, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_index, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_init, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_insert, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_len, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_minmax, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_mixedadd, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_mixedcmp, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_pickle, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_pop, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_radd_specials, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_remove, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_repeat, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_repr, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_repr_deep, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_reverse, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_reversed, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_set_subscript, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_setitem, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_setitem_error, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_setslice, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_slice, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_slice_assign_iterator, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_slice_type, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_sort, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_subscript, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_truth, test/dynamo/cpython/3_13/test_userlist.py::UserListTest::test_userlist_copy 2025-07-17T08:41:51.1366063Z 2025-07-17T08:41:54.2861040Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:41:54.2862638Z import pkg_resources 2025-07-17T08:41:54.4162741Z Running dynamo/cpython/3_13/test_cmath 1/1 ... [2025-07-17 08:41:54.415915] 2025-07-17T08:41:54.4163264Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:41:54.4166661Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_cmath.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:41:54.416313] 2025-07-17T08:41:59.6897638Z 2025-07-17T08:41:59.6899325Z dynamo/cpython/3_13/test_cmath 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_cmath_1.1_7868a03c580e90f3_.log 2025-07-17T08:41:59.6912537Z Running 33 items in this shard: test/dynamo/cpython/3_13/test_cmath.py::CMathTests::testAtanSign, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::testAtanhSign, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::testTanhSign, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_abs, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_abs_overflows, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_cmath_matches_math, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_constants, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_infinity_and_nan_constants, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_input_type, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_isfinite, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_isinf, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_isnan, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_phase, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_polar, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_polar_errno, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_rect, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_specific_values, test/dynamo/cpython/3_13/test_cmath.py::CMathTests::test_user_object, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_asymmetry, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_complex_near_zero, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_complex_special, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_complex_values, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_decimals, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_eight_decimal_places, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_fractions, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_identical, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_identical_infinite, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_inf_ninf_nan, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_integers, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_near_zero, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_negative_tolerances, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_reject_complex_tolerances, test/dynamo/cpython/3_13/test_cmath.py::IsCloseTests::test_zero_tolerance 2025-07-17T08:41:59.6922809Z 2025-07-17T08:42:02.8814668Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:42:02.8816361Z import pkg_resources 2025-07-17T08:42:03.0055968Z Running dynamo/cpython/3_13/test_math 1/1 ... [2025-07-17 08:42:03.005174] 2025-07-17T08:42:03.0056663Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:42:03.0058215Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_math.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:42:03.005545] 2025-07-17T08:42:10.7668502Z 2025-07-17T08:42:10.7669562Z dynamo/cpython/3_13/test_itertools 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_itertools_1.1_40a3821ff032589c_.log 2025-07-17T08:42:10.7719571Z Running 139 items in this shard: test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_StopIteration, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_accumulate, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_batched, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_bug_7244, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_chain, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_chain_from_iterable, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_chain_reducible, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_chain_setstate, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_combinations, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_combinations_overflow, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_combinations_result_gc, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_combinations_tuple_reuse, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_combinations_with_replacement, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_combinations_with_replacement_overflow, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_combinations_with_replacement_result_gc, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_combinations_with_replacement_tuple_reuse, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_combinatorics, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_compress, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_count, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_count_threading, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_count_with_step, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_count_with_step_threading, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_cycle, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_cycle_copy_pickle, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_cycle_setstate, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_cycle_unpickle_compat, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_dropwhile, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_filter, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_filterfalse, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_groupby, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_immutable_types, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_islice, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_map, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_pairwise, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_pairwise_reenter, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_pairwise_reenter2, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_pairwise_result_gc, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_permutations, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_permutations_overflow, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_permutations_result_gc, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_permutations_tuple_reuse, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_product, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_product_issue_25021, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_product_overflow, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_product_pickling, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_product_result_gc, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_product_tuple_reuse, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_repeat, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_repeat_with_negative_times, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_starmap, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_takewhile, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_tee, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_tee_concurrent, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_tee_dealloc_segfault, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_tee_del_backward, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_tee_reenter, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_zip, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_zip_longest_bad_iterable, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_zip_longest_pickling, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_zip_longest_result_gc, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_zip_longest_tuple_reuse, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_zip_tuple_reuse, test/dynamo/cpython/3_13/test_itertools.py::TestBasicOps::test_ziplongest, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_accumulate, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_accumulate_reducible, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_accumulate_reducible_none, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_chain, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_chain_from_iterable, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_combinations, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_combinations_with_replacement, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_compress, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_count, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_cycle, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_dropwhile, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_filter, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_filterfalse, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_groupby, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_islice, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_map, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_permutations, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_product, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_repeat, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_stapmap, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_takewhile, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_zip, test/dynamo/cpython/3_13/test_itertools.py::TestExamples::test_zip_longest, test/dynamo/cpython/3_13/test_itertools.py::TestPurePythonRoughEquivalents::test_batched_recipe, test/dynamo/cpython/3_13/test_itertools.py::TestPurePythonRoughEquivalents::test_islice_recipe, test/dynamo/cpython/3_13/test_itertools.py::TestPurePythonRoughEquivalents::test_tee_recipe, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_accumulate, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_batched, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_chain, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_chain_from_iterable, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_combinations, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_combinations_with_replacement, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_compress, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_count, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_cycle, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_dropwhile, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_filter, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_filterfalse, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_groupby, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_islice, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_issue2246, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_map, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_pairwise, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_permutations, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_product, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_repeat, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_starmap, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_takewhile, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_zip, test/dynamo/cpython/3_13/test_itertools.py::TestGC::test_zip_longest, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_accumulate, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_batched, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_chain, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_compress, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_cycle, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_dropwhile, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_filter, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_filterfalse, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_groupby, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_islice, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_map, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_pairwise, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_product, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_starmap, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_takewhile, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_tee, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_zip, test/dynamo/cpython/3_13/test_itertools.py::TestVariousIteratorArgs::test_ziplongest, test/dynamo/cpython/3_13/test_itertools.py::LengthTransparency::test_repeat, test/dynamo/cpython/3_13/test_itertools.py::LengthTransparency::test_repeat_with_negative_times, test/dynamo/cpython/3_13/test_itertools.py::RegressionTests::test_issue30347_1, test/dynamo/cpython/3_13/test_itertools.py::RegressionTests::test_issue30347_2, test/dynamo/cpython/3_13/test_itertools.py::RegressionTests::test_long_chain_of_empty_iterables, test/dynamo/cpython/3_13/test_itertools.py::RegressionTests::test_sf_793826, test/dynamo/cpython/3_13/test_itertools.py::RegressionTests::test_sf_950057, test/dynamo/cpython/3_13/test_itertools.py::SubclassWithKwargsTest::test_keywords_in_subclass 2025-07-17T08:42:10.7766601Z 2025-07-17T08:42:10.9827070Z 2025-07-17T08:42:10.9828353Z dynamo/cpython/3_13/test_math 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_math_1.1_2e7a3ef7a123be89_.log 2025-07-17T08:42:10.9854486Z Running 84 items in this shard: test/dynamo/cpython/3_13/test_math.py::MathTests::testAcos, test/dynamo/cpython/3_13/test_math.py::MathTests::testAcosh, test/dynamo/cpython/3_13/test_math.py::MathTests::testAsin, test/dynamo/cpython/3_13/test_math.py::MathTests::testAsinh, test/dynamo/cpython/3_13/test_math.py::MathTests::testAtan, test/dynamo/cpython/3_13/test_math.py::MathTests::testAtan2, test/dynamo/cpython/3_13/test_math.py::MathTests::testAtanh, test/dynamo/cpython/3_13/test_math.py::MathTests::testCbrt, test/dynamo/cpython/3_13/test_math.py::MathTests::testCeil, test/dynamo/cpython/3_13/test_math.py::MathTests::testComb, test/dynamo/cpython/3_13/test_math.py::MathTests::testConstants, test/dynamo/cpython/3_13/test_math.py::MathTests::testCopysign, test/dynamo/cpython/3_13/test_math.py::MathTests::testCos, test/dynamo/cpython/3_13/test_math.py::MathTests::testCosh, test/dynamo/cpython/3_13/test_math.py::MathTests::testDegrees, test/dynamo/cpython/3_13/test_math.py::MathTests::testDist, test/dynamo/cpython/3_13/test_math.py::MathTests::testExp, test/dynamo/cpython/3_13/test_math.py::MathTests::testExp2, test/dynamo/cpython/3_13/test_math.py::MathTests::testFabs, test/dynamo/cpython/3_13/test_math.py::MathTests::testFactorial, test/dynamo/cpython/3_13/test_math.py::MathTests::testFactorialHugeInputs, test/dynamo/cpython/3_13/test_math.py::MathTests::testFactorialNonIntegers, test/dynamo/cpython/3_13/test_math.py::MathTests::testFloor, test/dynamo/cpython/3_13/test_math.py::MathTests::testFmod, test/dynamo/cpython/3_13/test_math.py::MathTests::testFrexp, test/dynamo/cpython/3_13/test_math.py::MathTests::testFsum, test/dynamo/cpython/3_13/test_math.py::MathTests::testGcd, test/dynamo/cpython/3_13/test_math.py::MathTests::testHypot, test/dynamo/cpython/3_13/test_math.py::MathTests::testHypotAccuracy, test/dynamo/cpython/3_13/test_math.py::MathTests::testIsfinite, test/dynamo/cpython/3_13/test_math.py::MathTests::testIsinf, test/dynamo/cpython/3_13/test_math.py::MathTests::testIsnan, test/dynamo/cpython/3_13/test_math.py::MathTests::testIsqrt, test/dynamo/cpython/3_13/test_math.py::MathTests::testLdexp, test/dynamo/cpython/3_13/test_math.py::MathTests::testLog, test/dynamo/cpython/3_13/test_math.py::MathTests::testLog10, test/dynamo/cpython/3_13/test_math.py::MathTests::testLog1p, test/dynamo/cpython/3_13/test_math.py::MathTests::testLog2, test/dynamo/cpython/3_13/test_math.py::MathTests::testLog2Exact, test/dynamo/cpython/3_13/test_math.py::MathTests::testModf, test/dynamo/cpython/3_13/test_math.py::MathTests::testPerm, test/dynamo/cpython/3_13/test_math.py::MathTests::testPow, test/dynamo/cpython/3_13/test_math.py::MathTests::testRadians, test/dynamo/cpython/3_13/test_math.py::MathTests::testRemainder, test/dynamo/cpython/3_13/test_math.py::MathTests::testSin, test/dynamo/cpython/3_13/test_math.py::MathTests::testSinh, test/dynamo/cpython/3_13/test_math.py::MathTests::testSqrt, test/dynamo/cpython/3_13/test_math.py::MathTests::testSumProd, test/dynamo/cpython/3_13/test_math.py::MathTests::testTan, test/dynamo/cpython/3_13/test_math.py::MathTests::testTanh, test/dynamo/cpython/3_13/test_math.py::MathTests::testTanhSign, test/dynamo/cpython/3_13/test_math.py::MathTests::test_exceptions, test/dynamo/cpython/3_13/test_math.py::MathTests::test_inf_constant, test/dynamo/cpython/3_13/test_math.py::MathTests::test_input_exceptions, test/dynamo/cpython/3_13/test_math.py::MathTests::test_issue39871, test/dynamo/cpython/3_13/test_math.py::MathTests::test_lcm, test/dynamo/cpython/3_13/test_math.py::MathTests::test_math_dist_leak, test/dynamo/cpython/3_13/test_math.py::MathTests::test_mtestfile, test/dynamo/cpython/3_13/test_math.py::MathTests::test_nan_constant, test/dynamo/cpython/3_13/test_math.py::MathTests::test_nextafter, test/dynamo/cpython/3_13/test_math.py::MathTests::test_prod, test/dynamo/cpython/3_13/test_math.py::MathTests::test_sumprod_accuracy, test/dynamo/cpython/3_13/test_math.py::MathTests::test_sumprod_extended_precision_accuracy, test/dynamo/cpython/3_13/test_math.py::MathTests::test_sumprod_stress, test/dynamo/cpython/3_13/test_math.py::MathTests::test_testfile, test/dynamo/cpython/3_13/test_math.py::MathTests::test_trunc, test/dynamo/cpython/3_13/test_math.py::MathTests::test_ulp, test/dynamo/cpython/3_13/test_math.py::IsCloseTests::test_asymmetry, test/dynamo/cpython/3_13/test_math.py::IsCloseTests::test_decimals, test/dynamo/cpython/3_13/test_math.py::IsCloseTests::test_eight_decimal_places, test/dynamo/cpython/3_13/test_math.py::IsCloseTests::test_fractions, test/dynamo/cpython/3_13/test_math.py::IsCloseTests::test_identical, test/dynamo/cpython/3_13/test_math.py::IsCloseTests::test_identical_infinite, test/dynamo/cpython/3_13/test_math.py::IsCloseTests::test_inf_ninf_nan, test/dynamo/cpython/3_13/test_math.py::IsCloseTests::test_integers, test/dynamo/cpython/3_13/test_math.py::IsCloseTests::test_near_zero, test/dynamo/cpython/3_13/test_math.py::IsCloseTests::test_negative_tolerances, test/dynamo/cpython/3_13/test_math.py::IsCloseTests::test_zero_tolerance, test/dynamo/cpython/3_13/test_math.py::FMATests::test_fma_infinities, test/dynamo/cpython/3_13/test_math.py::FMATests::test_fma_nan_results, test/dynamo/cpython/3_13/test_math.py::FMATests::test_fma_overflow, test/dynamo/cpython/3_13/test_math.py::FMATests::test_fma_single_round, test/dynamo/cpython/3_13/test_math.py::FMATests::test_fma_zero_result, test/dynamo/cpython/3_13/test_math.py::FMATests::test_random 2025-07-17T08:42:10.9878753Z 2025-07-17T08:42:13.9708676Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:42:13.9710268Z import pkg_resources 2025-07-17T08:42:14.0947053Z Running dynamo/cpython/3_13/test_operator 1/1 ... [2025-07-17 08:42:14.094312] 2025-07-17T08:42:14.0947646Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:42:14.0950233Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_operator.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:42:14.094691] 2025-07-17T08:42:14.2213837Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:42:14.2216811Z import pkg_resources 2025-07-17T08:42:14.3467081Z Running dynamo/cpython/3_13/test_userdict 1/1 ... [2025-07-17 08:42:14.346263] 2025-07-17T08:42:14.3467856Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:42:14.3469615Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_userdict.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:42:14.346636] 2025-07-17T08:42:19.1690193Z 2025-07-17T08:42:19.1692072Z dynamo/cpython/3_13/test_userdict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_userdict_1.1_db7f2ba65bfbb417_.log 2025-07-17T08:42:19.1705792Z Running 25 items in this shard: test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_all, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_bool, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_clear, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_constructor, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_contains, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_copy, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_eq, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_fromkeys, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_get, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_getitem, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_init, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_items, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_keys, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_len, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_missing, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_mutatingiteration, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_pop, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_popitem, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_read, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_repr, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_repr_deep, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_setdefault, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_update, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_values, test/dynamo/cpython/3_13/test_userdict.py::UserDictTest::test_write 2025-07-17T08:42:19.1717380Z 2025-07-17T08:42:21.6710883Z 2025-07-17T08:42:21.6712105Z dynamo/cpython/3_13/test_operator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_operator_1.1_e6911beb52e6d890_.log 2025-07-17T08:42:21.6751997Z Running 106 items in this shard: test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test___all__, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_abs, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_add, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_attrgetter, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_attrgetter_signature, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_bitwise_and, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_bitwise_or, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_bitwise_xor, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_call, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_concat, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_contains, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_countOf, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_delitem, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_dunder_is_original, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_eq, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_floordiv, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_ge, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_getitem, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_gt, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_iconcat_without_getitem, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_index, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_indexOf, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_inplace, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_invert, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_is, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_is_not, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_itemgetter, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_itemgetter_signature, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_le, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_length_hint, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_lshift, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_lt, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_matmul, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_methodcaller, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_methodcaller_signature, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_mod, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_mul, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_ne, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_neg, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_not_, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_pos, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_pow, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_rshift, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_setitem, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_sub, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_truediv, test/dynamo/cpython/3_13/test_operator.py::PyOperatorTestCase::test_truth, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test___all__, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_abs, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_add, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_attrgetter, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_attrgetter_signature, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_bitwise_and, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_bitwise_or, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_bitwise_xor, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_call, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_concat, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_contains, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_countOf, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_delitem, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_dunder_is_original, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_eq, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_floordiv, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_ge, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_getitem, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_gt, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_iconcat_without_getitem, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_index, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_indexOf, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_inplace, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_invert, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_is, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_is_not, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_itemgetter, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_itemgetter_signature, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_le, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_length_hint, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_lshift, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_lt, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_matmul, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_methodcaller, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_methodcaller_signature, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_mod, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_mul, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_ne, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_neg, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_not_, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_pos, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_pow, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_rshift, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_setitem, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_sub, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_truediv, test/dynamo/cpython/3_13/test_operator.py::COperatorTestCase::test_truth, test/dynamo/cpython/3_13/test_operator.py::PyPyOperatorPickleTestCase::test_attrgetter, test/dynamo/cpython/3_13/test_operator.py::PyPyOperatorPickleTestCase::test_itemgetter, test/dynamo/cpython/3_13/test_operator.py::PyPyOperatorPickleTestCase::test_methodcaller, test/dynamo/cpython/3_13/test_operator.py::PyCOperatorPickleTestCase::test_attrgetter, test/dynamo/cpython/3_13/test_operator.py::PyCOperatorPickleTestCase::test_itemgetter, test/dynamo/cpython/3_13/test_operator.py::PyCOperatorPickleTestCase::test_methodcaller, test/dynamo/cpython/3_13/test_operator.py::CPyOperatorPickleTestCase::test_attrgetter, test/dynamo/cpython/3_13/test_operator.py::CPyOperatorPickleTestCase::test_itemgetter, test/dynamo/cpython/3_13/test_operator.py::CPyOperatorPickleTestCase::test_methodcaller, test/dynamo/cpython/3_13/test_operator.py::CCOperatorPickleTestCase::test_attrgetter, test/dynamo/cpython/3_13/test_operator.py::CCOperatorPickleTestCase::test_itemgetter, test/dynamo/cpython/3_13/test_operator.py::CCOperatorPickleTestCase::test_methodcaller 2025-07-17T08:42:21.6788884Z 2025-07-17T08:42:22.4353862Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:42:22.4356742Z import pkg_resources 2025-07-17T08:42:22.5630589Z Running dynamo/cpython/3_13/test_set 1/1 ... [2025-07-17 08:42:22.562581] 2025-07-17T08:42:22.5631296Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:42:22.5632905Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_set.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:42:22.562983] 2025-07-17T08:42:25.0226993Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:42:25.0229885Z import pkg_resources 2025-07-17T08:42:25.1494120Z Running dynamo/cpython/3_13/test_iter 1/1 ... [2025-07-17 08:42:25.149008] 2025-07-17T08:42:25.1494926Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:42:25.1497954Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_iter.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:42:25.149434] 2025-07-17T08:42:31.6743650Z 2025-07-17T08:42:31.6745046Z dynamo/cpython/3_13/test_iter 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_iter_1.1_8e6c621169290aab_.log 2025-07-17T08:42:31.6763990Z Running 57 items in this shard: test/dynamo/cpython/3_13/test_iter.py::TestCase::test_3720, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_builtin_filter, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_builtin_list, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_builtin_map, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_builtin_max_min, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_builtin_tuple, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_builtin_zip, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_countOf, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_error_iter, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_exception_function, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_exception_locations, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_exception_sequence, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_extending_list_with_iterator_does_not_segfault, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_free_after_iterating, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_in_and_not_in, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_indexOf, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_basic, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_big_range, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_callable, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_class_for, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_class_iter, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_dict, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_empty, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_file, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_for_loop, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_function, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_function_concealing_reentrant_exhaustion, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_function_stop, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_idempotency, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_independence, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_neg_setstate, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_overflow, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_range, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_string, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_iter_tuple, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_mutating_seq_class_exhausted_iter, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_mutating_seq_class_iter_pickle, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_nested_comprehensions_for, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_nested_comprehensions_iter, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_new_style_iter_class, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_reduce_mutating_builtins_iter, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_ref_counting_behavior, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_seq_class_for, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_seq_class_iter, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_sinkstate_callable, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_sinkstate_dict, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_sinkstate_enumerate, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_sinkstate_list, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_sinkstate_range, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_sinkstate_sequence, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_sinkstate_string, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_sinkstate_tuple, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_sinkstate_yield, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_stop_sequence, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_unicode_join_endcase, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_unpack_iter, test/dynamo/cpython/3_13/test_iter.py::TestCase::test_writelines 2025-07-17T08:42:31.6781295Z 2025-07-17T08:42:34.8848684Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:42:34.8850253Z import pkg_resources 2025-07-17T08:42:35.0101363Z Running dynamo/cpython/3_13/test_bool 1/1 ... [2025-07-17 08:42:35.009760] 2025-07-17T08:42:35.0101933Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:42:35.0104820Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_bool.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:42:35.010176] 2025-07-17T08:42:40.4825832Z 2025-07-17T08:42:40.4826931Z dynamo/cpython/3_13/test_bool 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_bool_1.1_473d4c59e9ca08d9_.log 2025-07-17T08:42:40.4836914Z Running 31 items in this shard: test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_blocked, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_bool_called_at_least_once, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_bool_new, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_boolean, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_callable, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_complex, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_contains, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_convert, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_convert_to_bool, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_fileclosed, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_float, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_format, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_from_bytes, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_hasattr, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_int, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_interpreter_convert_to_bool_raises, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_isinstance, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_issubclass, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_keyword_args, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_marshal, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_math, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_operator, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_pickle, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_picklevalues, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_real_and_imag, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_repr, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_sane_len, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_str, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_string, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_subclass, test/dynamo/cpython/3_13/test_bool.py::BoolTest::test_types 2025-07-17T08:42:40.4845585Z 2025-07-17T08:42:43.6882866Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:42:43.6886116Z import pkg_resources 2025-07-17T08:42:43.8142008Z Running dynamo/cpython/3_13/test_sort 1/1 ... [2025-07-17 08:42:43.813737] 2025-07-17T08:42:43.8142895Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:42:43.8145009Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_sort.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:42:43.814128] 2025-07-17T08:42:49.0870923Z 2025-07-17T08:42:49.0872711Z dynamo/cpython/3_13/test_sort 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_sort_1.1_2e30283e24c05c09_.log 2025-07-17T08:42:49.0888809Z Running 21 items in this shard: test/dynamo/cpython/3_13/test_sort.py::TestBase::testStressfully, test/dynamo/cpython/3_13/test_sort.py::TestBase::test_small_stability, test/dynamo/cpython/3_13/test_sort.py::TestBugs::test_bug453523, test/dynamo/cpython/3_13/test_sort.py::TestBugs::test_undetected_mutation, test/dynamo/cpython/3_13/test_sort.py::TestDecorateSortUndecorate::test_baddecorator, test/dynamo/cpython/3_13/test_sort.py::TestDecorateSortUndecorate::test_decorated, test/dynamo/cpython/3_13/test_sort.py::TestDecorateSortUndecorate::test_key_with_exception, test/dynamo/cpython/3_13/test_sort.py::TestDecorateSortUndecorate::test_key_with_mutating_del, test/dynamo/cpython/3_13/test_sort.py::TestDecorateSortUndecorate::test_key_with_mutating_del_and_exception, test/dynamo/cpython/3_13/test_sort.py::TestDecorateSortUndecorate::test_key_with_mutation, test/dynamo/cpython/3_13/test_sort.py::TestDecorateSortUndecorate::test_reverse, test/dynamo/cpython/3_13/test_sort.py::TestDecorateSortUndecorate::test_reverse_stability, test/dynamo/cpython/3_13/test_sort.py::TestDecorateSortUndecorate::test_stability, test/dynamo/cpython/3_13/test_sort.py::TestOptimizedCompares::test_none_in_tuples, test/dynamo/cpython/3_13/test_sort.py::TestOptimizedCompares::test_not_all_tuples, test/dynamo/cpython/3_13/test_sort.py::TestOptimizedCompares::test_safe_object_compare, test/dynamo/cpython/3_13/test_sort.py::TestOptimizedCompares::test_unsafe_float_compare, test/dynamo/cpython/3_13/test_sort.py::TestOptimizedCompares::test_unsafe_latin_compare, test/dynamo/cpython/3_13/test_sort.py::TestOptimizedCompares::test_unsafe_long_compare, test/dynamo/cpython/3_13/test_sort.py::TestOptimizedCompares::test_unsafe_object_compare, test/dynamo/cpython/3_13/test_sort.py::TestOptimizedCompares::test_unsafe_tuple_compare 2025-07-17T08:42:49.0903914Z 2025-07-17T08:42:52.3337029Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:42:52.3339892Z import pkg_resources 2025-07-17T08:42:52.4596891Z Running dynamo/cpython/3_13/test_float 1/1 ... [2025-07-17 08:42:52.459289] 2025-07-17T08:42:52.4597461Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:42:52.4600883Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_float.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:42:52.459699] 2025-07-17T08:42:59.8851259Z 2025-07-17T08:42:59.8853256Z dynamo/cpython/3_13/test_float 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_float_1.1_cf0576e345f31846_.log 2025-07-17T08:42:59.8871274Z Running 50 items in this shard: test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_error_message, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_float, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_float_ceil, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_float_containment, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_float_floor, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_float_memoryview, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_float_mod, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_float_pow, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_float_with_comma, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_floatasratio, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_floatconversion, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_hash, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_hash_nan, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_is_integer, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_keyword_args, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_keywords_in_subclass, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_noargs, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_non_numeric_input_types, test/dynamo/cpython/3_13/test_float.py::GeneralFloatCases::test_underscores, test/dynamo/cpython/3_13/test_float.py::FormatFunctionsTestCase::test_getformat, test/dynamo/cpython/3_13/test_float.py::IEEEFormatTestCase::test_double_specials_do_unpack, test/dynamo/cpython/3_13/test_float.py::IEEEFormatTestCase::test_float_specials_do_unpack, test/dynamo/cpython/3_13/test_float.py::IEEEFormatTestCase::test_serialized_float_rounding, test/dynamo/cpython/3_13/test_float.py::FormatTestCase::test_format, test/dynamo/cpython/3_13/test_float.py::FormatTestCase::test_format_testfile, test/dynamo/cpython/3_13/test_float.py::FormatTestCase::test_issue35560, test/dynamo/cpython/3_13/test_float.py::FormatTestCase::test_issue5864, test/dynamo/cpython/3_13/test_float.py::ReprTestCase::test_repr, test/dynamo/cpython/3_13/test_float.py::ReprTestCase::test_short_repr, test/dynamo/cpython/3_13/test_float.py::RoundTestCase::test_None_ndigits, test/dynamo/cpython/3_13/test_float.py::RoundTestCase::test_format_specials, test/dynamo/cpython/3_13/test_float.py::RoundTestCase::test_inf_nan, test/dynamo/cpython/3_13/test_float.py::RoundTestCase::test_inf_nan_ndigits, test/dynamo/cpython/3_13/test_float.py::RoundTestCase::test_large_n, test/dynamo/cpython/3_13/test_float.py::RoundTestCase::test_matches_float_format, test/dynamo/cpython/3_13/test_float.py::RoundTestCase::test_overflow, test/dynamo/cpython/3_13/test_float.py::RoundTestCase::test_previous_round_bugs, test/dynamo/cpython/3_13/test_float.py::RoundTestCase::test_small_n, test/dynamo/cpython/3_13/test_float.py::InfNanTest::test_inf_as_str, test/dynamo/cpython/3_13/test_float.py::InfNanTest::test_inf_from_str, test/dynamo/cpython/3_13/test_float.py::InfNanTest::test_inf_signs, test/dynamo/cpython/3_13/test_float.py::InfNanTest::test_nan_as_str, test/dynamo/cpython/3_13/test_float.py::InfNanTest::test_nan_from_str, test/dynamo/cpython/3_13/test_float.py::InfNanTest::test_nan_signs, test/dynamo/cpython/3_13/test_float.py::HexFloatTestCase::test_ends, test/dynamo/cpython/3_13/test_float.py::HexFloatTestCase::test_from_hex, test/dynamo/cpython/3_13/test_float.py::HexFloatTestCase::test_invalid_inputs, test/dynamo/cpython/3_13/test_float.py::HexFloatTestCase::test_roundtrip, test/dynamo/cpython/3_13/test_float.py::HexFloatTestCase::test_subclass, test/dynamo/cpython/3_13/test_float.py::HexFloatTestCase::test_whitespace 2025-07-17T08:42:59.8887972Z 2025-07-17T08:43:03.1514737Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:43:03.1517586Z import pkg_resources 2025-07-17T08:43:03.2772528Z Running dynamo/cpython/3_13/test_dict 1/1 ... [2025-07-17 08:43:03.276817] 2025-07-17T08:43:03.2773453Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:43:03.2775613Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_dict.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:43:03.277233] 2025-07-17T08:43:10.0046455Z 2025-07-17T08:43:10.0047837Z test_binary_ufuncs 2/4 was successful, full logs can be found in artifacts with path test/test-reports/test_binary_ufuncs_2.4_70dd9c503e589770_.log 2025-07-17T08:43:10.1393899Z Running 3257 items in this shard: test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___eq___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___eq___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___gt___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___gt___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iadd___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imul___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ior___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ipow___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___irshift___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___irshift___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___irshift___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___isub___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___itruediv___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___itruediv___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ixor___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___le___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___le___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___lshift___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___lt___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___lt___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___lt___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___matmul___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___matmul___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___matmul___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___mod___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___mod___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___mod___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___mul___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___or___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___or___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___or___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___or___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___pow___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___pow___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___radd___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___radd___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rfloordiv___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rlshift___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rlshift___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmatmul___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmatmul___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmatmul___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmod___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmod___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmod___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rmul___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ror___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ror___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ror___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rpow___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rpow___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rrshift___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rrshift___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rsub___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rtruediv___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rxor___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___rxor___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___sub___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___truediv___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___truediv___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___truediv___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___xor___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___xor___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_add_broadcast_empty_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_atan2_edgecases_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___radd___cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___radd___cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___radd___cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_batch_vs_slicing___radd___cpu_int32, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_or_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_or_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_or_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_xor_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_xor_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_xor_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_xor_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_max_binary_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_max_binary_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_maximum_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_maximum_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_min_binary_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_minimum_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_minimum_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_mul_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_mul_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_mul_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_mul_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_mul_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_mul_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ne_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ne_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ne_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_nextafter_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_nextafter_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_nextafter_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_polar_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_pow_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_pow_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_pow_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_pow_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_remainder_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_remainder_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_rsub_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_rsub_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_rsub_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_chebyshev_polynomial_t_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_chebyshev_polynomial_t_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_chebyshev_polynomial_t_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_chebyshev_polynomial_u_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_chebyshev_polynomial_v_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_chebyshev_polynomial_v_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_chebyshev_polynomial_v_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_chebyshev_polynomial_w_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_laguerre_polynomial_l_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_laguerre_polynomial_l_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_legendre_polynomial_p_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_u_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_u_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_v_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_w_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_xlog1py_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_xlog1py_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_zeta_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_sub_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_sub_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_sub_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_xlogy_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_xlogy_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed___radd___cpu_bool, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed___rmul___cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed___ror___cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed___ror___cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed___rpow___cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed___rpow___cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed___rsub___cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed___rsub___cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed___rsub___cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed___rsub___cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed___rsub___cpu_uint8, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_bitwise_or_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_bitwise_or_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_bitwise_right_shift_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_bitwise_right_shift_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_bitwise_xor_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_clamp_max_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_clamp_max_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_clamp_max_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_clamp_min_cpu_int16, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_fmin_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_fmin_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_gcd_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_ge_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_ge_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_ge_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_gt_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_heaviside_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_heaviside_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_heaviside_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_heaviside_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_hypot_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_hypot_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_hypot_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_igamma_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_igamma_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_igammac_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_igammac_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_isclose_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_isclose_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_isclose_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_isclose_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_isclose_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_lcm_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_lcm_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_le_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_le_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_le_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logaddexp_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_and_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_or_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_or_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_xor_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_logical_xor_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_lt_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_lt_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_lt_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_lt_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_maximum_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_maximum_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_minimum_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_minimum_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_mul_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_mul_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_mul_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_ne_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_ne_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_nextafter_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_pow_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_pow_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_rsub_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_rsub_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_rsub_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_rsub_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_special_xlog1py_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_special_xlog1py_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_special_zeta_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_special_zeta_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_special_zeta_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_special_zeta_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_sub_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_sub_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_sub_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_sub_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_true_divide_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_true_divide_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_true_divide_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_true_divide_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_true_divide_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_true_divide_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_xlogy_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_xlogy_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_xlogy_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_xlogy_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed__refs_xlogy_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_add_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_add_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_add_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_and_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_and_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_left_shift_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_left_shift_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_or_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_right_shift_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_right_shift_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_xor_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_xor_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_min_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_min_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_complex_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_copysign_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_copysign_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_copysign_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_uint8, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_int16, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_nextafter_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_nextafter_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_t_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_u_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_u_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_u_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_v_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_v_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_v_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_v_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_w_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_w_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_hermite_polynomial_he_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_hermite_polynomial_he_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_hermite_polynomial_he_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_hermite_polynomial_he_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_laguerre_polynomial_l_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_laguerre_polynomial_l_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_t_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_t_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_u_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_v_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_shifted_chebyshev_polynomial_w_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_xlog1py_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_xlog1py_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_zeta_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_zeta_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_sub_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_sub_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_sub_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_sub_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_sub_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_true_divide_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_true_divide_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_xlogy_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bfloat16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bfloat16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bool_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bool_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_bool_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_float64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_bfloat16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_cuda_tensor_pow_scalar_tensor_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_nonfinite_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_nonfinite_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_scalar_pow_float_tensor_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_scalar_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_scalar_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_scalar_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_tensor_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_tensor_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_tensor_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_float_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_integral_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_integral_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_gcd_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_complex_cpu_complex128_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_complex_cpu_complex64_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_inplace_dunders_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lcm_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_lowp_cpu_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logaddexp_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logaddexp_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logaddexp_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_bfloat16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_bfloat16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_bfloat16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_bool_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex128_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex128_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_complex64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_float16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_float16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_float16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_float16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_float16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_float32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_float32_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_float32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_float32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_float32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_float64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_int16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_int16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_int32_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_int32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_int32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_int32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_int64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_int8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_int8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_int8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_uint8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_and_cpu_uint8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_bfloat16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_bfloat16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_bfloat16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_bfloat16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_bfloat16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_bool_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_bool_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_bool_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_complex128_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_complex128_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_complex128_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_complex64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_complex64_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_complex64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_float16_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_float16_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_float16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_float32_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_float32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_float64_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_float64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_int16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_int16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_int32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_int32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_int32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_int64_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_int64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_int8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_uint8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_uint8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_uint8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_uint8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_uint8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_or_cpu_uint8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_bfloat16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_cpu_bool_int64, 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in artifacts with path test/test-reports/dynamo.cpython.3_13.test_dict_1.1_e8993a60659337c3_.log 2025-07-17T08:43:12.3148153Z Running 112 items in this shard: test/dynamo/cpython/3_13/test_dict.py::DictTest::test_bad_key, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_bool, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_clear, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_constructor, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_container_iterator, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_contains, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_copy, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_copy_fuzz, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_copy_maintains_tracking, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_copy_noncompact, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_dict_contain_use_after_free, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_dict_copy_order, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_dict_items_result_gc, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_dict_items_result_gc_reversed, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_dictitems_contains_use_after_free, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_dictview_mixed_set_operations, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_dictview_set_operations_on_items, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_dictview_set_operations_on_keys, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_empty_presized_dict_in_freelist, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_eq, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_equal_operator_modifying_operand, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_errors_in_view_containment_check, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_free_after_iterating, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_fromkeys, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_fromkeys_operator_modifying_dict_operand, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_fromkeys_operator_modifying_set_operand, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_get, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_getitem, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_init_use_after_free, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_instance_dict_getattr_str_subclass, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_invalid_keyword_arguments, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_itemiterator_pickling, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_items, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_items_symmetric_difference, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_iterator_pickling, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_keys, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_keys_contained, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_len, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_literal_constructor, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_merge_and_mutate, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_merge_operator, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_missing, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_mutating_iteration, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_mutating_iteration_delete, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_mutating_iteration_delete_over_items, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_mutating_iteration_delete_over_values, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_mutating_lookup, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_object_set_item_single_instance_non_str_key, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_oob_indexing_dictiter_iternextitem, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_pop, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_popitem, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_reentrant_insertion, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_repr, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_repr_deep, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_resize1, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_resize2, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_reverse_iterator_for_empty_dict, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_reverse_iterator_for_shared_shared_dicts, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_reversed, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_reverseitemiterator_pickling, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_reverseiterator_pickling, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_reversevaluesiterator_pickling, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_setdefault, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_setdefault_atomic, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_setitem_atomic_at_resize, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_splittable_del, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_splittable_pop, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_splittable_pop_pending, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_splittable_popitem, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_splittable_setdefault, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_splittable_to_generic_combinedtable, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_splittable_update, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_store_evilattr, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_str_nonstr, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_string_keys_can_track_values, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_track_dynamic, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_track_literals, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_track_subtypes, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_tuple_keyerror, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_update, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_values, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_valuesiterator_pickling, test/dynamo/cpython/3_13/test_dict.py::DictTest::test_views_mapping, test/dynamo/cpython/3_13/test_dict.py::CAPITest::test_getitem_knownhash, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_bool, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_constructor, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_get, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_getitem, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_items, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_keys, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_len, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_pop, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_popitem, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_read, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_setdefault, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_update, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_values, test/dynamo/cpython/3_13/test_dict.py::GeneralMappingTests::test_write, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_bool, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_constructor, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_get, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_getitem, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_items, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_keys, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_len, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_pop, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_popitem, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_read, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_setdefault, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_update, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_values, test/dynamo/cpython/3_13/test_dict.py::SubclassMappingTests::test_write 2025-07-17T08:43:12.3213145Z 2025-07-17T08:43:13.2751667Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:43:13.2754640Z import pkg_resources 2025-07-17T08:43:13.4010494Z Running dynamo/cpython/3_13/test_complex 1/1 ... [2025-07-17 08:43:13.400641] 2025-07-17T08:43:13.4011036Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:43:13.4012665Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_complex.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:43:13.400985] 2025-07-17T08:43:15.5764426Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:43:15.5767433Z import pkg_resources 2025-07-17T08:43:15.7020634Z Running dynamo/cpython/3_13/test_tuple 1/1 ... [2025-07-17 08:43:15.701637] 2025-07-17T08:43:15.7021518Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:43:15.7023473Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_tuple.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:43:15.702008] 2025-07-17T08:43:19.1745743Z 2025-07-17T08:43:19.1747586Z dynamo/cpython/3_13/test_complex 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_complex_1.1_5c3fdf146e662082_.log 2025-07-17T08:43:19.1767040Z Running 35 items in this shard: test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test___complex__, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_abs, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_add, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_boolcontext, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_conjugate, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_constructor, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_constructor_from_string, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_constructor_negative_nans_from_string, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_constructor_special_numbers, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_divmod, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_divmod_zero_division, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_floordiv, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_floordiv_zero_division, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_format, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_getnewargs, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_hash, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_mod, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_mod_zero_division, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_mul, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_neg, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_negated_imaginary_literal, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_negative_zero_repr_str, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_overflow, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_plus_minus_0j, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_pos, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_pow, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_pow_with_small_integer_exponents, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_repr_roundtrip, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_repr_str, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_richcompare, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_richcompare_boundaries, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_sub, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_truediv, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_truediv_zero_division, test/dynamo/cpython/3_13/test_complex.py::ComplexTest::test_underscores 2025-07-17T08:43:19.1783818Z 2025-07-17T08:43:22.3591607Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:43:22.3594582Z import pkg_resources 2025-07-17T08:43:22.4267081Z 2025-07-17T08:43:22.4268493Z dynamo/cpython/3_13/test_tuple 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_tuple_1.1_087a5f666258b8a3_.log 2025-07-17T08:43:22.4285998Z Running 36 items in this shard: test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_addmul, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_bigrepeat, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_bug7466, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_constructors, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_contains, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_contains_fake, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_contains_order, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_count, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_free_after_iterating, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_getitem, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_getitem_error, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_getitemoverwriteiter, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_getslice, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_hash_exact, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_hash_optional, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_iadd, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_imul, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_index, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_iterator_pickle, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_keyword_args, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_keywords_in_subclass, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_len, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_lexicographic_ordering, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_minmax, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_no_comdat_folding, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_pickle, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_repeat, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_repr, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_repr_large, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_reversed_pickle, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_subscript, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_track_dynamic, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_track_literals, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_track_subtypes, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_truth, test/dynamo/cpython/3_13/test_tuple.py::TupleTest::test_tupleresizebug 2025-07-17T08:43:22.4302042Z 2025-07-17T08:43:22.4866402Z Running test_package 1/1 ... [2025-07-17 08:43:22.486243] 2025-07-17T08:43:22.4867043Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:43:22.4870893Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_package.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:43:22.486669] 2025-07-17T08:43:22.6744266Z 2025-07-17T08:43:22.6745420Z dynamo/cpython/3_13/test_set 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_set_1.1_acd7a51c7182271c_.log 2025-07-17T08:43:22.6975181Z Running 623 items in this shard: test/dynamo/cpython/3_13/test_set.py::TestSet::test_add, test/dynamo/cpython/3_13/test_set.py::TestSet::test_and, test/dynamo/cpython/3_13/test_set.py::TestSet::test_badcmp, test/dynamo/cpython/3_13/test_set.py::TestSet::test_clear, test/dynamo/cpython/3_13/test_set.py::TestSet::test_constructor_identity, test/dynamo/cpython/3_13/test_set.py::TestSet::test_container_iterator, test/dynamo/cpython/3_13/test_set.py::TestSet::test_contains, test/dynamo/cpython/3_13/test_set.py::TestSet::test_copy, test/dynamo/cpython/3_13/test_set.py::TestSet::test_cyclical_repr, test/dynamo/cpython/3_13/test_set.py::TestSet::test_deepcopy, test/dynamo/cpython/3_13/test_set.py::TestSet::test_difference, test/dynamo/cpython/3_13/test_set.py::TestSet::test_difference_update, test/dynamo/cpython/3_13/test_set.py::TestSet::test_discard, test/dynamo/cpython/3_13/test_set.py::TestSet::test_do_not_rehash_dict_keys, test/dynamo/cpython/3_13/test_set.py::TestSet::test_equality, test/dynamo/cpython/3_13/test_set.py::TestSet::test_free_after_iterating, test/dynamo/cpython/3_13/test_set.py::TestSet::test_gc, test/dynamo/cpython/3_13/test_set.py::TestSet::test_hash, test/dynamo/cpython/3_13/test_set.py::TestSet::test_iand, test/dynamo/cpython/3_13/test_set.py::TestSet::test_init, test/dynamo/cpython/3_13/test_set.py::TestSet::test_inplace_on_self, test/dynamo/cpython/3_13/test_set.py::TestSet::test_intersection, test/dynamo/cpython/3_13/test_set.py::TestSet::test_intersection_update, test/dynamo/cpython/3_13/test_set.py::TestSet::test_ior, test/dynamo/cpython/3_13/test_set.py::TestSet::test_isdisjoint, test/dynamo/cpython/3_13/test_set.py::TestSet::test_isub, test/dynamo/cpython/3_13/test_set.py::TestSet::test_iterator_pickling, test/dynamo/cpython/3_13/test_set.py::TestSet::test_ixor, test/dynamo/cpython/3_13/test_set.py::TestSet::test_len, test/dynamo/cpython/3_13/test_set.py::TestSet::test_new_or_init, test/dynamo/cpython/3_13/test_set.py::TestSet::test_or, test/dynamo/cpython/3_13/test_set.py::TestSet::test_pickling, test/dynamo/cpython/3_13/test_set.py::TestSet::test_pop, test/dynamo/cpython/3_13/test_set.py::TestSet::test_remove, test/dynamo/cpython/3_13/test_set.py::TestSet::test_remove_keyerror_set, test/dynamo/cpython/3_13/test_set.py::TestSet::test_remove_keyerror_unpacking, test/dynamo/cpython/3_13/test_set.py::TestSet::test_rich_compare, test/dynamo/cpython/3_13/test_set.py::TestSet::test_setOfFrozensets, test/dynamo/cpython/3_13/test_set.py::TestSet::test_set_literal, test/dynamo/cpython/3_13/test_set.py::TestSet::test_set_literal_evaluation_order, test/dynamo/cpython/3_13/test_set.py::TestSet::test_set_literal_insertion_order, test/dynamo/cpython/3_13/test_set.py::TestSet::test_sub, test/dynamo/cpython/3_13/test_set.py::TestSet::test_sub_and_super, test/dynamo/cpython/3_13/test_set.py::TestSet::test_subclass_with_custom_hash, test/dynamo/cpython/3_13/test_set.py::TestSet::test_symmetric_difference, test/dynamo/cpython/3_13/test_set.py::TestSet::test_symmetric_difference_update, test/dynamo/cpython/3_13/test_set.py::TestSet::test_union, test/dynamo/cpython/3_13/test_set.py::TestSet::test_uniquification, test/dynamo/cpython/3_13/test_set.py::TestSet::test_update, test/dynamo/cpython/3_13/test_set.py::TestSet::test_weakref, test/dynamo/cpython/3_13/test_set.py::TestSet::test_xor, test/dynamo/cpython/3_13/test_set.py::TestSetSubclass::test_add, test/dynamo/cpython/3_13/test_set.py::TestSetSubclass::test_and, test/dynamo/cpython/3_13/test_set.py::TestSetSubclass::test_badcmp, 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test/dynamo/cpython/3_13/test_set.py::TestCopyingNested::test_deep_copy, test/dynamo/cpython/3_13/test_set.py::TestIdentities::test_binopsVsSubsets, test/dynamo/cpython/3_13/test_set.py::TestIdentities::test_commutativity, test/dynamo/cpython/3_13/test_set.py::TestIdentities::test_exclusion, test/dynamo/cpython/3_13/test_set.py::TestIdentities::test_summations, test/dynamo/cpython/3_13/test_set.py::TestVariousIteratorArgs::test_constructor, test/dynamo/cpython/3_13/test_set.py::TestVariousIteratorArgs::test_inline_methods, test/dynamo/cpython/3_13/test_set.py::TestVariousIteratorArgs::test_inplace_methods, test/dynamo/cpython/3_13/test_set.py::TestWeirdBugs::test_8420_set_merge, test/dynamo/cpython/3_13/test_set.py::TestWeirdBugs::test_iter_and_mutate, test/dynamo/cpython/3_13/test_set.py::TestWeirdBugs::test_merge_and_mutate, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_and_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_eq_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_ge_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_gt_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_iadd_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_ior_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_isub_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_iteration_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_ixor_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_le_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_lt_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_ne_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_or_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_sub_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Set::test_xor_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_and_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_eq_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_ge_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_gt_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_iadd_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_ior_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_isub_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_iteration_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_ixor_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_le_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_lt_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_ne_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_or_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_sub_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Subclass::test_xor_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_and_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_eq_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_ge_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_gt_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_iadd_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_ior_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_isub_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_iteration_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_ixor_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_le_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_lt_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_ne_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_or_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_sub_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Set_Subclass::test_xor_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_and_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_eq_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_ge_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_gt_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_iadd_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_ior_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_isub_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_iteration_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_ixor_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_le_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_lt_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_ne_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_or_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_sub_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestBinaryOpsMutating_Subclass_Set::test_xor_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Set::test_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Set::test_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Set::test_intersection_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Set::test_intersection_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Set::test_isdisjoint_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Set::test_issubset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Set::test_issuperset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Set::test_symmetric_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Set::test_symmetric_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Set::test_union_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Set::test_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Subclass::test_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Subclass::test_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Subclass::test_intersection_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Subclass::test_intersection_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Subclass::test_isdisjoint_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Subclass::test_issubset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Subclass::test_issuperset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Subclass::test_symmetric_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Subclass::test_symmetric_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Subclass::test_union_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Subclass::test_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Subclass::test_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Subclass::test_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Subclass::test_intersection_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Subclass::test_intersection_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Subclass::test_isdisjoint_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Subclass::test_issubset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Subclass::test_issuperset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Subclass::test_symmetric_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Subclass::test_symmetric_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Subclass::test_union_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Subclass::test_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Set::test_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Set::test_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Set::test_intersection_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Set::test_intersection_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Set::test_isdisjoint_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Set::test_issubset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Set::test_issuperset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Set::test_symmetric_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Set::test_symmetric_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Set::test_union_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Subclass_Set::test_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Dict::test_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Dict::test_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Dict::test_intersection_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Dict::test_intersection_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Dict::test_isdisjoint_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Dict::test_issubset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Dict::test_issuperset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Dict::test_symmetric_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Dict::test_symmetric_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Dict::test_union_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_Dict::test_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_List::test_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_List::test_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_List::test_intersection_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_List::test_intersection_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_List::test_isdisjoint_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_List::test_issubset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_List::test_issuperset_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_List::test_symmetric_difference_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_List::test_symmetric_difference_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_List::test_union_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestMethodsMutating_Set_List::test_update_with_mutation, test/dynamo/cpython/3_13/test_set.py::TestGraphs::test_cube, test/dynamo/cpython/3_13/test_set.py::TestGraphs::test_cuboctahedron 2025-07-17T08:43:22.7191625Z 2025-07-17T08:43:25.7231090Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:43:25.7232724Z import pkg_resources 2025-07-17T08:43:25.8480557Z Running test_decomp 1/1 ... [2025-07-17 08:43:25.847634] 2025-07-17T08:43:25.8481129Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:43:25.8483362Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_decomp.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:43:25.848031] 2025-07-17T08:43:25.9994881Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:43:25.9996468Z import pkg_resources 2025-07-17T08:43:26.1238918Z Running test_autoload 1/1 ... [2025-07-17 08:43:26.123512] 2025-07-17T08:43:26.1239369Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:43:26.1242381Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_autoload.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:43:26.123920] 2025-07-17T08:43:30.5960237Z 2025-07-17T08:43:30.5961750Z test_autoload 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_autoload_1.1_64afc5ec094b36d1_.log 2025-07-17T08:43:30.5962737Z Running 1 items in this shard: test/test_autoload.py::TestDeviceBackendAutoload::test_autoload 2025-07-17T08:43:33.8357221Z 2025-07-17T08:43:33.8360051Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:43:33.8362947Z import pkg_resources 2025-07-17T08:43:33.9652121Z Running test_utils_config_module 1/1 ... [2025-07-17 08:43:33.964646] 2025-07-17T08:43:33.9652904Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:43:33.9655022Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_utils_config_module.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:43:33.965130] 2025-07-17T08:43:45.2959486Z 2025-07-17T08:43:45.2960875Z test_utils_config_module 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_utils_config_module_1.1_60f32d4cd06c3356_.log 2025-07-17T08:43:45.2969745Z Running 22 items in this shard: test/test_utils_config_module.py::TestConfigModule::test_alias, test/test_utils_config_module.py::TestConfigModule::test_bad_jk_type, test/test_utils_config_module.py::TestConfigModule::test_base_value_loading, test/test_utils_config_module.py::TestConfigModule::test_codegen_config, test/test_utils_config_module.py::TestConfigModule::test_codegen_config_function, test/test_utils_config_module.py::TestConfigModule::test_dict_copy_semantics, test/test_utils_config_module.py::TestConfigModule::test_env_name_semantics, test/test_utils_config_module.py::TestConfigModule::test_env_name_string_semantics, test/test_utils_config_module.py::TestConfigModule::test_get_hash, test/test_utils_config_module.py::TestConfigModule::test_invalid_config_float, test/test_utils_config_module.py::TestConfigModule::test_invalid_config_int, test/test_utils_config_module.py::TestConfigModule::test_make_closur_patcher, test/test_utils_config_module.py::TestConfigModule::test_multi_env, test/test_utils_config_module.py::TestConfigModule::test_none_override_semantics, test/test_utils_config_module.py::TestConfigModule::test_overrides, test/test_utils_config_module.py::TestConfigModule::test_patch, test/test_utils_config_module.py::TestConfigModule::test_reference_is_default, test/test_utils_config_module.py::TestConfigModule::test_reference_semantics, test/test_utils_config_module.py::TestConfigModule::test_save_config, test/test_utils_config_module.py::TestConfigModule::test_save_config_portable, test/test_utils_config_module.py::TestConfigModule::test_type_loading, test/test_utils_config_module.py::TestConfigModule::test_unittest_patch 2025-07-17T08:43:45.2977752Z 2025-07-17T08:43:48.5307188Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:43:48.5308893Z import pkg_resources 2025-07-17T08:43:48.6551458Z Running test_mkl_verbose 1/1 ... [2025-07-17 08:43:48.654782] 2025-07-17T08:43:48.6551967Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:43:48.6554495Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkl_verbose.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:43:48.655188] 2025-07-17T08:43:56.2306919Z 2025-07-17T08:43:56.2307991Z test_mkl_verbose 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkl_verbose_1.1_5bb989ff4e4a993f_.log 2025-07-17T08:43:56.2309737Z Running 2 items in this shard: test/test_mkl_verbose.py::TestMKLVerbose::test_verbose_off, test/test_mkl_verbose.py::TestMKLVerbose::test_verbose_on 2025-07-17T08:43:56.2310424Z 2025-07-17T08:43:59.4675255Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:43:59.4678169Z import pkg_resources 2025-07-17T08:43:59.5907975Z Running dynamo/test_deque_reconstruct 1/1 ... [2025-07-17 08:43:59.590348] 2025-07-17T08:43:59.5908960Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:43:59.5911034Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_deque_reconstruct.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:43:59.590757] 2025-07-17T08:44:02.7752278Z 2025-07-17T08:44:02.7753707Z dynamo/test_deque_reconstruct 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_deque_reconstruct_1.1_ba8057a7782bb930_.log 2025-07-17T08:44:02.7754557Z 2025-07-17T08:44:05.9477323Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:44:05.9480184Z import pkg_resources 2025-07-17T08:44:06.0732736Z Running test_license 1/1 ... [2025-07-17 08:44:06.072846] 2025-07-17T08:44:06.0733564Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:44:06.0736087Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_license.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:44:06.073257] 2025-07-17T08:44:06.3307942Z 2025-07-17T08:44:06.3308771Z test_decomp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_1.1_de1f0aac7a48ed83_.log 2025-07-17T08:44:06.6900290Z Running 9005 items in this shard: test/test_decomp.py::TestDecompCPU::test_arange_graph_cpu, test/test_decomp.py::TestDecompCPU::test_batch_norm_unflatten_weight_bias_cpu, test/test_decomp.py::TestDecompCPU::test_bernoulli_default_cpu, test/test_decomp.py::TestDecompCPU::test_broadcasting_index_copy_cpu, test/test_decomp.py::TestDecompCPU::test_cat_single_input_cpu, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive__batch_norm_with_update_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__batch_norm_with_update_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__batch_norm_with_update_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__batch_norm_with_update_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive__native_batch_norm_legit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__native_batch_norm_legit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__native_batch_norm_legit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__native_batch_norm_legit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_lengths_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_lengths_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_lengths_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_lengths_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive__upsample_bilinear2d_aa_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__upsample_bilinear2d_aa_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__upsample_bilinear2d_aa_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_int64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_exponential_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_exponential_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_exponential_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_exponential_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float8_e4m3fn, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float8_e4m3fnuz, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float8_e5m2, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float8_e5m2fnuz, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft2_cpu_float32, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_uint8, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_int16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_int64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_gather_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_gather_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_gcd_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_gcd_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_gcd_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_gcd_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_gcd_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_geqrf_cpu_complex128, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_grid_sampler_2d_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_grid_sampler_2d_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_grid_sampler_2d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_grid_sampler_2d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_int8, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_ex_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_ex_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_ex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_ex_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_ex_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_ex_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_ex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_ex_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_solve_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_solve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_solve_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_solve_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_grad_oriented_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_grad_oriented_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_grad_oriented_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_grad_oriented_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_ex_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_ex_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_ex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_ex_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_solve_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_solve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_solve_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_solve_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_power_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_power_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_power_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_power_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_hermitian_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_hermitian_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_hermitian_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_hermitian_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_complex64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_hermitian_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_hermitian_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_hermitian_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_hermitian_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_singular_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_singular_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_singular_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_singular_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_qr_cpu_complex128, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_solve_ex_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_solve_ex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_solve_ex_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_solve_triangular_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_solve_triangular_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_solve_triangular_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_solve_triangular_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svd_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svd_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svd_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svd_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svdvals_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svdvals_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svdvals_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svdvals_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorinv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorinv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorinv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorinv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorsolve_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorsolve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorsolve_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorsolve_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vector_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vector_norm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vector_norm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vector_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vector_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vector_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_log2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_log2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_log2_cpu_complex64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_pool2d_with_indices_backward_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_pool2d_with_indices_backward_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_pool2d_with_indices_backward_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_pool2d_with_indices_backward_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_int16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_maximum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_maximum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mean_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mean_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_median_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_median_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_median_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_median_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_median_cpu_int16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_no_dim_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_no_dim_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_no_dim_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_no_dim_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_with_dim_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_with_dim_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_with_dim_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_with_dim_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_with_dim_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_with_dim_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_with_dim_cpu_int32, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmean_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmedian_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmedian_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmedian_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmedian_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmedian_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmedian_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmedian_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmedian_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmedian_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanquantile_cpu_float32, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_native_dropout_backward_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_dropout_backward_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_layer_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_layer_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_layer_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_layer_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ne_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_ne_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_ne_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_ne_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ne_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_ne_cpu_float32, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_masked_fill_cpu, test/test_decomp.py::TestDecompCPU::test_quick__batch_norm_with_update_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__batch_norm_with_update_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__batch_norm_with_update_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__batch_norm_with_update_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__softmax_backward_data_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__softmax_backward_data_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__softmax_backward_data_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__softmax_backward_data_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick__upsample_bilinear2d_aa_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__upsample_bilinear2d_aa_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__upsample_bilinear2d_aa_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_float32, 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test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bernoulli_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_bernoulli_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_bernoulli_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_bernoulli_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_cauchy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_cauchy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_cauchy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_cauchy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_complex_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_complex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_complex_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_core_backward__softmax_backward_data_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward__unsafe_masked_index_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward__unsafe_masked_index_put_accumulate_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_addcdiv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_addcmul_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_addr_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_alias_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_baddbmm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_bernoulli_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_block_diag_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_clamp_max_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_clamp_min_cpu_float64, 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test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float8_e4m3fn, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float8_e4m3fnuz, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float8_e5m2, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float8_e5m2fnuz, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft2_cpu_bool, 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test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft_cpu_int32, 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test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_bfloat16, 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test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_gcd_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_gcd_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_gcd_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_gcd_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_gcd_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_grid_sampler_2d_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_grid_sampler_2d_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_grid_sampler_2d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_grid_sampler_2d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_hypot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_hypot_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_hypot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_hypot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_int64, 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test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_isneginf_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_isneginf_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_isneginf_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_bfloat16, 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test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp2_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_native_batch_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_native_batch_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_native_batch_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_native_batch_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_native_layer_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_native_layer_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_native_layer_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_native_layer_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_float64, 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test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nextafter_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nextafter_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nextafter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nextafter_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_with_logits_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_with_logits_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_with_logits_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_gelu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_gelu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_gelu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_gelu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_glu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_glu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_glu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_glu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardsigmoid_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardsigmoid_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardsigmoid_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardsigmoid_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardswish_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardswish_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardswish_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardswish_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_huber_loss_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_huber_loss_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_huber_loss_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_huber_loss_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_leaky_relu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_leaky_relu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_leaky_relu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_leaky_relu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_grad_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_grad_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_grad_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_grad_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_grad_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_grad_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_grad_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_grad_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_complex64, 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test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_prelu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_silu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_silu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softplus_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softplus_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softplus_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softplus_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softshrink_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softshrink_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softshrink_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softshrink_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_unfold_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_unfold_cpu_bool, 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test/test_decomp.py::TestDecompCPU::test_quick_norm_fro_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_norm_fro_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_norm_fro_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_norm_fro_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_norm_fro_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_norm_nuc_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_norm_nuc_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_norm_nuc_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_norm_nuc_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_normal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_normal_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_normal_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_normal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_normal_in_place_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_normal_in_place_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_normal_in_place_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_normal_in_place_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_normal_in_place_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_normal_in_place_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_normal_number_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_normal_number_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_normal_number_mean_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_normal_number_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_int8, 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test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_round_decimals_0_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_round_decimals_0_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_complex128, 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test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_float32, 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test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_int8, 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test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_float64, 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test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_complex32, 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test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_tril_indices_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_tril_indices_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_triu_indices_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_triu_indices_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_complex32, 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test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_eval_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_eval_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_train_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_train_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_LSTM_eval_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_LSTM_eval_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_LSTM_train_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_LSTM_train_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_eval_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_eval_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_train_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_train_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_uniform_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_amp_batch_norm_backward_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_contiguous_log_softmax_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_contiguous_softmax_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_elu_backward_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_exponential_non_inf_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_native_layer_norm_cpu_decomp_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_sdpa_nn_functional_scaled_dot_product_attention_cpu_bfloat16, test/test_decomp.py::DecompOneOffTestsCPU::test_sdpa_nn_functional_scaled_dot_product_attention_cpu_float16, test/test_decomp.py::DecompOneOffTestsCPU::test_sdpa_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_decomp.py::DecompOneOffTestsCPU::test_sdpa_nn_functional_scaled_dot_product_attention_cpu_float64, test/test_decomp.py::DecompOneOffTestsCPU::test_threshold_backward_dtype_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_weight_norm_interface_cpu, test/test_decomp.py::HasDecompTest::test_aten_core_operators, test/test_decomp.py::HasDecompTest::test_has_decomposition 2025-07-17T08:44:06.9791687Z 2025-07-17T08:44:09.5669244Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:44:09.5672402Z import pkg_resources 2025-07-17T08:44:09.6919147Z Running test_mkldnn_verbose 1/1 ... [2025-07-17 08:44:09.691423] 2025-07-17T08:44:09.6919990Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:44:09.6921611Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn_verbose.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:44:09.691853] 2025-07-17T08:44:10.6956752Z 2025-07-17T08:44:10.6957837Z test_license 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_license_1.1_b6c0196b448beba4_.log 2025-07-17T08:44:10.6959570Z Running 2 items in this shard: test/test_license.py::TestLicense::test_distinfo_license, test/test_license.py::TestLicense::test_license_for_wheel 2025-07-17T08:44:10.6960750Z 2025-07-17T08:44:13.9538092Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:44:13.9539721Z import pkg_resources 2025-07-17T08:44:14.0793598Z Running dynamo/cpython/3_13/test_unittest/test_assertions 1/1 ... [2025-07-17 08:44:14.077734] 2025-07-17T08:44:14.0794965Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:44:14.0797196Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_unittest/test_assertions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:44:14.078119] 2025-07-17T08:44:17.2183980Z 2025-07-17T08:44:17.2185389Z test_mkldnn_verbose 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_verbose_1.1_673e6f1a4c5ca7c1_.log 2025-07-17T08:44:17.2187741Z Running 2 items in this shard: test/test_mkldnn_verbose.py::TestMKLDNNVerbose::test_verbose_off, test/test_mkldnn_verbose.py::TestMKLDNNVerbose::test_verbose_on 2025-07-17T08:44:17.2188969Z 2025-07-17T08:44:19.9018747Z 2025-07-17T08:44:19.9020912Z dynamo/cpython/3_13/test_unittest/test_assertions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_unittest.test_assertions_1.1_a94845b6e1b0ff4f_.log 2025-07-17T08:44:19.9046602Z Running 35 items in this shard: test/dynamo/cpython/3_13/test_unittest/test_assertions.py::Test_Assertions::testAssertNotRegex, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::Test_Assertions::test_AlmostEqual, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::Test_Assertions::test_AmostEqualWithDelta, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::Test_Assertions::test_assertRaises, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::Test_Assertions::test_assertRaises_frames_survival, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAlmostEqual, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertDictEqual, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertFalse, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertGreater, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertGreaterEqual, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertIn, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertIs, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertIsNone, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertIsNot, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertIsNotNone, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertLess, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertLessEqual, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertMultiLineEqual, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertNotIn, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertNotRegex, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertRaises, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertRaisesRegex, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertRegex, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertSequenceEqual, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertSetEqual, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertTrue, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertWarns, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testAssertWarnsRegex, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testDefault, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testNotAlmostEqual, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::testNotEqual, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::test_assertNotWarns, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::test_baseAssertEqual, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::test_formatMessage_unicode_error, test/dynamo/cpython/3_13/test_unittest/test_assertions.py::TestLongMessage::test_formatMsg 2025-07-17T08:44:19.9070920Z 2025-07-17T08:44:20.4099278Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:44:20.4102162Z import pkg_resources 2025-07-17T08:44:20.5368289Z Running test_comparison_utils 1/1 ... [2025-07-17 08:44:20.536406] 2025-07-17T08:44:20.5369136Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:44:20.5371825Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_comparison_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:44:20.536823] 2025-07-17T08:44:23.0864417Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:44:23.0867400Z import pkg_resources 2025-07-17T08:44:23.2134327Z Running test_ops 1/1 ... [2025-07-17 08:44:23.213043] 2025-07-17T08:44:23.2134761Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:44:23.2137264Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:44:23.213454] 2025-07-17T08:44:25.6106710Z 2025-07-17T08:44:25.6108261Z test_comparison_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_comparison_utils_1.1_019a789987df4d8f_.log 2025-07-17T08:44:25.6113138Z Running 7 items in this shard: test/test_comparison_utils.py::TestComparisonUtils::test_all_equal_no_assert, test/test_comparison_utils.py::TestComparisonUtils::test_all_equal_no_assert_nones, test/test_comparison_utils.py::TestComparisonUtils::test_assert_device, test/test_comparison_utils.py::TestComparisonUtils::test_assert_dtype, test/test_comparison_utils.py::TestComparisonUtils::test_assert_layout, test/test_comparison_utils.py::TestComparisonUtils::test_assert_sizes, test/test_comparison_utils.py::TestComparisonUtils::test_assert_strides 2025-07-17T08:44:25.6117172Z 2025-07-17T08:44:28.8298613Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:44:28.8300209Z import pkg_resources 2025-07-17T08:44:28.9551949Z Running typing/test_python_operators 1/1 ... [2025-07-17 08:44:28.954798] 2025-07-17T08:44:28.9552579Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:44:28.9554629Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'typing/test_python_operators.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:44:28.955169] 2025-07-17T08:44:51.3028528Z 2025-07-17T08:44:51.3030094Z typing/test_python_operators 1/1 was successful, full logs can be found in artifacts with path test/test-reports/typing.test_python_operators_1.1_5afe191663f4fa4f_.log 2025-07-17T08:44:51.3145117Z Running 318 items in this shard: test/typing/test_python_operators.py::TestPythonOperators::test_binary_a100_op_%_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a101_op_%_b101, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a102_op_%_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a103_op_%_b103, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a104_op_*_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a105_op_*_b105, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a106_op_*_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a107_op_*_b107, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a108_op_**_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a109_op_**_b109, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a110_op_**_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a111_op_**_b111, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a112_op_+_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a113_op_+_b113, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a114_op_+_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a115_op_+_b115, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a116_op_-_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a117_op_-_b117, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a118_op_-_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a119_op_-_b119, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a120_op_/_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a121_op_/_b121, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a122_op_/_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a123_op_/_b123, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a124_op_//_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a125_op_//_b125, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a126_op_//_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a127_op_//_b127, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a128_op_&_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a129_op_&_b129, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a130_op_&_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a131_op_&_b131, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a132_op_<<_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a133_op_<<_b133, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a134_op_<<_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a135_op_<<_b135, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a136_op_>>_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a137_op_>>_b137, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a138_op_>>_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a139_op_>>_b139, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a140_op_^_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a141_op_^_b141, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a142_op_^_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a143_op_^_b143, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a144_op_|_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a145_op_|_b145, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a146_op_|_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a147_op_|_b147, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a148_op_@_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a149_op_@_b149, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a150_op_@_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a151_op_@_b151, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a228_op_!=_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a229_op_!=_b229, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a230_op_!=_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a231_op_!=_b231, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a232_op_<_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a233_op_<_b233, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a234_op_<_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a235_op_<_b235, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a236_op_<=_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a237_op_<=_b237, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a238_op_<=_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a239_op_<=_b239, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a240_op_==_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a241_op_==_b241, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a242_op_==_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a243_op_==_b243, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a244_op_>_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a245_op_>_b245, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a246_op_>_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a247_op_>_b247, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a248_op_>=_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a249_op_>=_b249, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a250_op_>=_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a251_op_>=_b251, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a252_op_%_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a253_op_%_b253, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a254_op_%_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a255_op_%_b255, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a256_op_*_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a257_op_*_b257, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a258_op_*_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a259_op_*_b259, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a260_op_**_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a261_op_**_b261, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a262_op_**_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a263_op_**_b263, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a264_op_+_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a265_op_+_b265, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a266_op_+_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a267_op_+_b267, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a268_op_-_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a269_op_-_b269, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a270_op_-_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a271_op_-_b271, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a272_op_/_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a273_op_/_b273, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a274_op_/_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a275_op_/_b275, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a276_op_//_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a277_op_//_b277, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a278_op_//_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a279_op_//_b279, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a280_op_&_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a281_op_&_b281, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a282_op_&_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a283_op_&_b283, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a284_op_<<_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a285_op_<<_b285, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a286_op_<<_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a287_op_<<_b287, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a288_op_>>_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a289_op_>>_b289, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a290_op_>>_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a291_op_>>_b291, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a292_op_^_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a293_op_^_b293, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a294_op_^_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a295_op_^_b295, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a296_op_|_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a297_op_|_b297, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a298_op_|_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a299_op_|_b299, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a300_op_@_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a301_op_@_b301, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a302_op_@_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a303_op_@_b303, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a76_op_!=_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a77_op_!=_b77, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a78_op_!=_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a79_op_!=_b79, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a80_op_<_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a81_op_<_b81, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a82_op_<_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a83_op_<_b83, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a84_op_<=_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a85_op_<=_b85, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a86_op_<=_b_3, 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test/typing/test_python_operators.py::TestPythonOperators::test_binary_a_3_op_@_b227, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a_3_op_@_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a_3_op_@_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a_3_op_^_b217, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a_3_op_^_b219, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a_3_op_^_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a_3_op_^_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a_3_op_|_b221, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a_3_op_|_b223, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a_3_op_|_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a_3_op_|_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_operators_are_correct_and_complete, test/typing/test_python_operators.py::TestPythonOperators::test_type_tests_are_complete, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_+_a1, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_+_a3, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_+_a_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_+_a_3, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_-_a5, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_-_a7, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_-_a_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_-_a_3, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_~_a11, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_~_a9, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_~_a_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_unary_op_~_a_3 2025-07-17T08:44:51.3257248Z 2025-07-17T08:44:54.5669063Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:44:54.6935107Z import pkg_resources 2025-07-17T08:44:54.6935920Z Running torch_np/test_nep50_examples 1/1 ... [2025-07-17 08:44:54.693105] 2025-07-17T08:44:54.6936731Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:44:54.6938762Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_nep50_examples.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:44:54.693526] 2025-07-17T08:45:00.0665329Z 2025-07-17T08:45:00.0666927Z torch_np/test_nep50_examples 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_nep50_examples_1.1_66935c7fb370f033_.log 2025-07-17T08:45:00.1417218Z Running 1573 items in this shard: test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_3j + array(3, complex64), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_True + uint8(2), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array(1_0, float32) + 1e-14 == 1_0, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([0_1], float32) == float64(0_1), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([100], uint8) + 200, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1], uint8) + 1, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1], uint8) + 200, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1], uint8) + 300, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1], uint8) + array(1, int64), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1], uint8) + int64(1), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1_0], float32) + 1e-14 == 1_0, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1_], float32) + 3, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1_], float32) + array(1_, float64), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1_], float32) + float64(1_), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1_], float32) + int64(3), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_bool_(True) + 1, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_float32(1) + 1j, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_float32(1) + 3e100, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_float32(5) + 5j, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_int16(2) + 2, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_int16(4) + 4j, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_int32(1) + 5j, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_uint8(1) + 2, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_uint8(1) + 300, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_uint8(100) + 200, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar27_array27, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar28_array28, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar29_array29, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar30_array30, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar31_array31, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar32_array32, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar33_array33, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar34_array34, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar35_array35, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array10, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array11, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array12, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array13, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array14, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array15, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array16, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array17, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array9, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array18, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array19, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array20, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array21, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array22, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array23, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array24, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array25, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array26, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array0, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array1, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array2, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array3, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array4, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array5, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array6, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array7, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array8, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar27_array27, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar28_array28, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar29_array29, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar30_array30, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar31_array31, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar32_array32, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar33_array33, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar34_array34, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar35_array35, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array10, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array11, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array12, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array13, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array14, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array15, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array16, 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test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar33_array33, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar34_array34, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar35_array35, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array10, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array11, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array12, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array13, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array14, 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test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_True_array8, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar27_array27, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar28_array28, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar29_array29, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar30_array30, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar31_array31, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar32_array32, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar33_array33, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar34_array34, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar35_array35, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array10, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array11, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array12, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array13, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array14, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array15, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array16, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array17, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array9, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array18, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array19, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array20, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array21, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array22, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array23, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array24, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array25, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array26, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array0, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array1, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array2, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array3, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array4, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array5, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array6, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array7, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array8, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar27_array27_dtype27, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar28_array28_dtype28, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar29_array29_dtype29, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar30_array30_dtype30, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar31_array31_dtype31, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar32_array32_dtype32, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar33_array33_dtype33, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar34_array34_dtype34, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar35_array35_dtype35, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array10_dtype10, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array11_dtype11, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array12_dtype12, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array13_dtype13, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array14_dtype14, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array15_dtype15, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array16_dtype16, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array17_dtype17, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array9_dtype9, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array18_dtype18, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array19_dtype19, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array20_dtype20, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array21_dtype21, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array22_dtype22, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array23_dtype23, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array24_dtype24, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array25_dtype25, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array26_dtype26, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array0_dtype0, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array1_dtype1, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array2_dtype2, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array3_dtype3, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array4_dtype4, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array5_dtype5, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array6_dtype6, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array7_dtype7, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array8_dtype8 2025-07-17T08:45:00.2138384Z 2025-07-17T08:45:03.2282665Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:45:03.2285720Z import pkg_resources 2025-07-17T08:45:03.3528931Z Running test_ops_jit 1/1 ... [2025-07-17 08:45:03.352466] 2025-07-17T08:45:03.3529684Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:45:03.3532010Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_jit.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:45:03.352845] 2025-07-17T08:45:12.3811763Z 2025-07-17T08:45:12.3812603Z test_ops_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_jit_1.1_8590dabac4bb322a_.log 2025-07-17T08:45:12.4233328Z Running 1136 items in this shard: test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_abs_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_acos_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_acosh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_asin_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_asinh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_atan2_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_atan_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_atanh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_cat_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_clamp_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_digamma_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_div_floor_rounding_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_div_no_rounding_mode_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_div_trunc_rounding_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_erf_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_erfc_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_erfinv_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_exp2_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_expm1_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_ge_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_gt_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_i0_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_igamma_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_igammac_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_le_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_lgamma_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_linalg_det_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_linalg_householder_product_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_linalg_inv_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_linalg_matrix_power_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_log1p_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_log_softmax_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_log_softmax_with_dtype_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_logit_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_logsumexp_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_lt_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_mH_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_matmul_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_matrix_exp_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_max_binary_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_min_binary_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_movedim_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_mul_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_ne_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_neg_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_conv1d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_conv2d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_conv3d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_conv_transpose1d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_conv_transpose2d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_conv_transpose3d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_group_norm_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_layer_norm_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_rms_norm_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_outer_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_round_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_round_decimals_0_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_round_decimals_3_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_round_decimals_neg_3_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_sigmoid_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_sinc_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_softmax_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_softmax_with_dtype_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_sub_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_tanh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_transpose_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_trunc_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_vstack_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_xlogy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_H_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_H_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_T_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_T_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit___getitem___cpu_complex64, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_atleast_2d_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_atleast_2d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_atleast_3d_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_atleast_3d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_baddbmm_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_baddbmm_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_bernoulli_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_bfloat16_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_bfloat16_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_block_diag_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_block_diag_cpu_float32, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_byte_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cartesian_prod_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cartesian_prod_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cat_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cat_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cauchy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cdist_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cdouble_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cdouble_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_ceil_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cfloat_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cfloat_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_chalf_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_chalf_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_char_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_char_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cholesky_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cholesky_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cholesky_inverse_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cholesky_inverse_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cholesky_solve_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cholesky_solve_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_chunk_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_chunk_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_clamp_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_clamp_max_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_clamp_min_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_clone_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_clone_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_column_stack_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_column_stack_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_combinations_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_combinations_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_complex_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_conj_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_conj_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_conj_physical_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_conj_physical_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_constant_pad_nd_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_constant_pad_nd_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_contiguous_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_contiguous_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_copysign_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_corrcoef_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_corrcoef_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cos_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cos_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cosh_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cosh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_count_nonzero_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_count_nonzero_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cov_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cov_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cross_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cross_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cummax_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cummin_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cumprod_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cumprod_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cumsum_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cumsum_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cumulative_trapezoid_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_cumulative_trapezoid_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_deg2rad_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diag_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diag_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diag_embed_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diag_embed_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diagflat_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diagflat_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diagonal_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diagonal_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diagonal_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diagonal_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diagonal_scatter_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diagonal_scatter_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_diff_cpu_complex64, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_double_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_dsplit_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_dsplit_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_dstack_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_dstack_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_einsum_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_einsum_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_empty_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_empty_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_empty_like_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_empty_like_cpu_float32, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_jiterator_unary_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_kron_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_kron_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_kthvalue_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_ldexp_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_ldexp_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_le_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_lerp_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_lerp_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_lgamma_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_cholesky_cpu_complex64, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_diagonal_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_eig_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_eig_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_eigh_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_eigh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_eigvals_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_eigvals_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_eigvalsh_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_eigvalsh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_householder_product_cpu_complex64, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_ldl_solve_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_lstsq_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_lstsq_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_lstsq_grad_oriented_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_lu_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_lu_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_lu_factor_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_lu_factor_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_lu_factor_ex_cpu_complex64, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_neg_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_neg_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_new_empty_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_new_empty_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_new_empty_strided_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_new_empty_strided_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_new_full_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_new_full_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_new_ones_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_new_ones_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_new_zeros_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_new_zeros_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nextafter_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_alpha_dropout_cpu_float32, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_softplus_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_softshrink_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_softsign_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_softsign_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_tanhshrink_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_tanhshrink_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_threshold_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_triplet_margin_loss_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_triplet_margin_loss_cpu_float32, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_pca_lowrank_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_permute_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_permute_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_permute_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_permute_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_pinverse_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_pinverse_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_polar_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_polygamma_polygamma_n_0_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_polygamma_polygamma_n_1_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_polygamma_polygamma_n_2_cpu_float32, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_spherical_bessel_j0_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_xlog1py_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_zeta_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_list_args_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_list_args_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_with_sizes_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_with_sizes_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_with_sizes_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_with_sizes_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sqrt_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sqrt_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_square_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_square_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_squeeze_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_squeeze_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_squeeze_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_squeeze_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_squeeze_multiple_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_squeeze_multiple_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_stack_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_stack_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_mean_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_mean_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_mean_unbiased_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_mean_unbiased_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_unbiased_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_unbiased_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_stft_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_stft_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sub_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sub_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sum_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sum_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sum_to_size_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sum_to_size_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_svd_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_svd_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_svd_lowrank_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_svd_lowrank_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_t_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_t_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_t_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_t_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_take_along_dim_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_take_along_dim_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_take_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_take_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tan_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tan_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tanh_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tanh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tensor_split_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tensor_split_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tensordot_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tensordot_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tile_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tile_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_to_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_to_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_to_sparse_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_to_sparse_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_topk_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_trace_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_trace_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_transpose_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_transpose_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_transpose_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_transpose_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_trapezoid_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_trapezoid_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_trapz_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_trapz_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_triangular_solve_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_triangular_solve_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tril_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tril_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_triu_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_triu_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_true_divide_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_true_divide_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_trunc_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unbind_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unbind_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unbind_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unbind_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unflatten_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unflatten_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unfold_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unfold_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unfold_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unfold_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_uniform_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_uniform_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unique_consecutive_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unique_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsafe_chunk_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsafe_chunk_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsafe_split_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsafe_split_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsqueeze_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsqueeze_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsqueeze_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsqueeze_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_mean_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_mean_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_mean_unbiased_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_mean_unbiased_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_unbiased_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_unbiased_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_vdot_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_vdot_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_view_as_complex_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_view_as_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_view_as_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_view_as_real_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_view_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_view_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_view_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_view_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_vsplit_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_vsplit_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_vstack_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_vstack_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_where_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_where_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_xlogy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_zero__cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_zero__cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_zeros_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_zeros_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_zeros_like_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_zeros_like_cpu_float32 2025-07-17T08:45:12.4640155Z 2025-07-17T08:45:15.6614049Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:45:15.6615757Z import pkg_resources 2025-07-17T08:45:15.7845883Z Running dynamo/test_skip_guard_eval_unsafe 1/1 ... [2025-07-17 08:45:15.784195] 2025-07-17T08:45:15.7846451Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:45:15.7849029Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_skip_guard_eval_unsafe.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:45:15.784588] 2025-07-17T08:45:19.0976770Z 2025-07-17T08:45:19.0977962Z dynamo/test_skip_guard_eval_unsafe 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_skip_guard_eval_unsafe_1.1_e496a47fb5aed282_.log 2025-07-17T08:45:19.0978789Z 2025-07-17T08:45:22.3177288Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:45:22.3180626Z import pkg_resources 2025-07-17T08:45:22.4445009Z Running functorch/test_ac_logging 1/1 ... [2025-07-17 08:45:22.444094] 2025-07-17T08:45:22.4445936Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:45:22.4448422Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ac_logging.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:45:22.444478] 2025-07-17T08:45:26.9152067Z 2025-07-17T08:45:26.9153773Z functorch/test_ac_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ac_logging_1.1_db637cdea97510f7_.log 2025-07-17T08:45:26.9156600Z Running 4 items in this shard: test/functorch/test_ac_logging.py::TestAcLogging::test_create_activation_checkpointing_logging_structure_payload, test/functorch/test_ac_logging.py::TestAcLogging::test_create_joint_graph_edges, test/functorch/test_ac_logging.py::TestAcLogging::test_create_joint_graph_node_information, test/functorch/test_ac_logging.py::TestAcLogging::test_create_structured_trace_for_min_cut_info 2025-07-17T08:45:26.9158445Z 2025-07-17T08:45:30.1092072Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:45:30.1095037Z import pkg_resources 2025-07-17T08:45:30.2365158Z Running test_custom_ops 1/1 ... [2025-07-17 08:45:30.236109] 2025-07-17T08:45:30.2366050Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:45:30.2368851Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_custom_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:45:30.236563] 2025-07-17T08:45:34.9841320Z 2025-07-17T08:45:34.9842721Z test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_package_1.1_a64d3d51f2ffbd72_.log 2025-07-17T08:45:34.9880794Z Running 137 items in this shard: test/test_package.py::TestAnalyze::test_trace_dependencies, test/test_package.py::TestDependencyAPI::test_allow_empty_with_error, test/test_package.py::TestDependencyAPI::test_broken_dependency, test/test_package.py::TestDependencyAPI::test_deny, test/test_package.py::TestDependencyAPI::test_deny_glob, test/test_package.py::TestDependencyAPI::test_extern, test/test_package.py::TestDependencyAPI::test_extern_glob, test/test_package.py::TestDependencyAPI::test_extern_glob_allow_empty, test/test_package.py::TestDependencyAPI::test_externing_c_extension, test/test_package.py::TestDependencyAPI::test_implicit_intern, test/test_package.py::TestDependencyAPI::test_intern_error, test/test_package.py::TestDependencyAPI::test_invalid_import, test/test_package.py::TestDependencyAPI::test_mock, test/test_package.py::TestDependencyAPI::test_mock_glob, test/test_package.py::TestDependencyAPI::test_mock_glob_allow_empty, test/test_package.py::TestDependencyAPI::test_pickle_mocked, test/test_package.py::TestDependencyAPI::test_pickle_mocked_all, test/test_package.py::TestDependencyAPI::test_repackage_mocked_module, test/test_package.py::TestDependencyHooks::test_extern_and_mock_hook, test/test_package.py::TestDependencyHooks::test_multiple_extern_hooks, test/test_package.py::TestDependencyHooks::test_multiple_mock_hooks, test/test_package.py::TestDependencyHooks::test_remove_hooks, test/test_package.py::TestDependencyHooks::test_single_hook, test/test_package.py::TestDiGraph::test_all_paths, test/test_package.py::TestDiGraph::test_contains, test/test_package.py::TestDiGraph::test_contains_non_hashable, test/test_package.py::TestDiGraph::test_edges, test/test_package.py::TestDiGraph::test_forward_closure, test/test_package.py::TestDiGraph::test_iter, test/test_package.py::TestDiGraph::test_node_attr_update, test/test_package.py::TestDiGraph::test_node_attrs, test/test_package.py::TestDiGraph::test_predecessor_not_in_graph, test/test_package.py::TestDiGraph::test_predecessors, test/test_package.py::TestDiGraph::test_successor_not_in_graph, test/test_package.py::TestDiGraph::test_successors, test/test_package.py::DirectoryReaderTest::test_importer_access, test/test_package.py::DirectoryReaderTest::test_loading_has_record, test/test_package.py::DirectoryReaderTest::test_loading_module, test/test_package.py::DirectoryReaderTest::test_loading_pickle, test/test_package.py::DirectoryReaderTest::test_package_resource_access, test/test_package.py::DirectoryReaderTest::test_resource_access_by_path, test/test_package.py::DirectoryReaderTest::test_resource_reader, test/test_package.py::DirectoryReaderTest::test_scriptobject_failure_message, test/test_package.py::TestGlobGroup::test_exclude, test/test_package.py::TestGlobGroup::test_exclude_from_all, test/test_package.py::TestGlobGroup::test_invalid_raw, test/test_package.py::TestGlobGroup::test_list_include_exclude, test/test_package.py::TestGlobGroup::test_one_star, test/test_package.py::TestGlobGroup::test_one_star_middle, test/test_package.py::TestGlobGroup::test_one_star_multiple_in_component, test/test_package.py::TestGlobGroup::test_one_star_partial, test/test_package.py::TestGlobGroup::test_one_star_partial_extension, test/test_package.py::TestGlobGroup::test_raw_two_star, test/test_package.py::TestGlobGroup::test_two_star, test/test_package.py::TestGlobGroup::test_two_star_end, test/test_package.py::TestGlobGroup::test_two_star_middle, test/test_package.py::TestGlobGroup::test_two_star_multiple, test/test_package.py::TestImporter::test_ordered_importer_basic, test/test_package.py::TestImporter::test_ordered_importer_whichmodule, test/test_package.py::TestImporter::test_package_importer_whichmodule_no_dunder_module, test/test_package.py::TestImporter::test_single_ordered_importer, test/test_package.py::TestImporter::test_sys_importer, test/test_package.py::TestImporter::test_sys_importer_roundtrip, test/test_package.py::TestLoadBCPackages::test_load_bc_packages_fx_module, test/test_package.py::TestLoadBCPackages::test_load_bc_packages_nn_module, test/test_package.py::TestLoadBCPackages::test_load_bc_packages_torchscript_module, test/test_package.py::TestMangling::test_demangle_base, test/test_package.py::TestMangling::test_demangler_multiple_manglers, test/test_package.py::TestMangling::test_is_mangled, test/test_package.py::TestMangling::test_mangle_empty_errors, test/test_package.py::TestMangling::test_mangle_prefix, test/test_package.py::TestMangling::test_mangler_is_consistent, test/test_package.py::TestMangling::test_package_mangler, test/test_package.py::TestMangling::test_roundtrip_mangling, test/test_package.py::TestMangling::test_unique_manglers, test/test_package.py::TestMangling::test_unique_module_names, test/test_package.py::TestMisc::test_dunder_package_present, test/test_package.py::TestMisc::test_dunder_package_works_from_package, test/test_package.py::TestMisc::test_exporter_content_lists, test/test_package.py::TestMisc::test_file_structure, test/test_package.py::TestMisc::test_file_structure_has_file, test/test_package.py::TestMisc::test_inspect_class, test/test_package.py::TestMisc::test_is_from_package, test/test_package.py::TestMisc::test_load_python_version_from_package, test/test_package.py::TestMisc::test_loaders_that_remap_files_work_ok, test/test_package.py::TestMisc::test_python_version, test/test_package.py::TestMisc::test_std_lib_sys_hackery_checks, test/test_package.py::ModelTest::test_model_save, test/test_package.py::ModelTest::test_resnet, test/test_package.py::ModelTest::test_script_resnet, test/test_package.py::TestPackageFX::test_package_fx_custom_tracer, test/test_package.py::TestPackageFX::test_package_fx_package, test/test_package.py::TestPackageFX::test_package_fx_simple, test/test_package.py::TestPackageFX::test_package_fx_with_imports, test/test_package.py::TestPackageFX::test_package_fx_wrap, test/test_package.py::TestPackageFX::test_package_gm_preserve_stack_trace, test/test_package.py::TestPackageFX::test_package_then_fx, test/test_package.py::TestPackageScript::test_different_package_interface, test/test_package.py::TestPackageScript::test_different_package_script_class, test/test_package.py::TestPackageScript::test_load_shared_scriptmodules, test/test_package.py::TestPackageScript::test_load_shared_tensors, test/test_package.py::TestPackageScript::test_load_shared_tensors_repackaged, test/test_package.py::TestPackageScript::test_mixing_packaged_and_inline_modules, test/test_package.py::TestPackageScript::test_mixing_packaged_and_inline_modules_shared_code, test/test_package.py::TestPackageScript::test_package_interface, test/test_package.py::TestPackageScript::test_package_script_class, test/test_package.py::TestPackageScript::test_package_script_class_referencing_self, test/test_package.py::TestPackageScript::test_save_eager_mods_sharing_scriptmodule, test/test_package.py::TestPackageScript::test_save_independent_scriptmodules, test/test_package.py::TestPackageScript::test_save_repeat_scriptmodules, test/test_package.py::TestPackageScript::test_save_scriptmodule, test/test_package.py::TestPackageScript::test_save_scriptmodule_file, test/test_package.py::TestPackageScript::test_save_scriptmodule_only_necessary_code, test/test_package.py::TestPackageScript::test_save_scriptmodule_with_submods, test/test_package.py::TestPackageScript::test_save_scriptmodules_in_container, test/test_package.py::TestPackageScript::test_save_scriptmodules_submod_redefinition, test/test_package.py::TestPackageScript::test_save_shared_tensors, test/test_package.py::TestPackageScript::test_saving_and_scripting_packaged_mod, test/test_package.py::TestPackageScript::test_scriptmodules_repeat_save, test/test_package.py::TestPackageScript::test_tensor_sharing_pickle, test/test_package.py::TestRepackage::test_repackage_import_indirectly_via_parent_module, test/test_package.py::TestResources::test_importer_access, test/test_package.py::TestResources::test_package_resource_access, test/test_package.py::TestResources::test_resource_access_by_path, test/test_package.py::TestResources::test_resource_reader, test/test_package.py::TestSaveLoad::test_bad_dunder_imports, test/test_package.py::TestSaveLoad::test_dunder_imports, test/test_package.py::TestSaveLoad::test_exporting_mismatched_code, test/test_package.py::TestSaveLoad::test_pickle, test/test_package.py::TestSaveLoad::test_pickle_long_name_with_protocol_4, test/test_package.py::TestSaveLoad::test_save_imported_module, test/test_package.py::TestSaveLoad::test_save_imported_module_using_package_importer, test/test_package.py::TestSaveLoad::test_save_load_fp8, test/test_package.py::TestSaveLoad::test_save_module, test/test_package.py::TestSaveLoad::test_save_module_binary, test/test_package.py::TestSaveLoad::test_saving_source, test/test_package.py::TestSaveLoad::test_saving_string 2025-07-17T08:45:34.9917785Z 2025-07-17T08:45:38.2687745Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:45:38.2689577Z import pkg_resources 2025-07-17T08:45:38.3930469Z Running dynamo/test_interop 1/1 ... [2025-07-17 08:45:38.392615] 2025-07-17T08:45:38.3931310Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:45:38.3933747Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_interop.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:45:38.393023] 2025-07-17T08:45:41.6736137Z 2025-07-17T08:45:41.6737477Z dynamo/test_interop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_interop_1.1_47625c1144a45437_.log 2025-07-17T08:45:41.6738727Z 2025-07-17T08:45:44.9667531Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:45:44.9670712Z import pkg_resources 2025-07-17T08:45:45.0970966Z Running dynamo/test_resume 1/1 ... [2025-07-17 08:45:45.096630] 2025-07-17T08:45:45.0971756Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:45:45.0974436Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_resume.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:45:45.097103] 2025-07-17T08:45:48.2121559Z 2025-07-17T08:45:48.2123015Z dynamo/test_resume 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_resume_1.1_6373e1550fb9bc3d_.log 2025-07-17T08:45:48.2124257Z 2025-07-17T08:45:51.3652401Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:45:51.3653971Z import pkg_resources 2025-07-17T08:45:51.4898560Z Running dynamo/test_sdpa 1/1 ... [2025-07-17 08:45:51.489455] 2025-07-17T08:45:51.4899370Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:45:51.4902028Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sdpa.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:45:51.489858] 2025-07-17T08:45:54.8569408Z 2025-07-17T08:45:54.8570931Z dynamo/test_sdpa 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sdpa_1.1_64bce085762a87f0_.log 2025-07-17T08:45:54.8572099Z 2025-07-17T08:45:57.9965081Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:45:57.9968013Z import pkg_resources 2025-07-17T08:45:58.1212072Z Running dynamo/test_utils 1/1 ... [2025-07-17 08:45:58.120715] 2025-07-17T08:45:58.1212878Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:45:58.1214690Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:45:58.121081] 2025-07-17T08:46:01.3419825Z 2025-07-17T08:46:01.3420751Z dynamo/test_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_utils_1.1_c627e8424552a88a_.log 2025-07-17T08:46:01.3421404Z 2025-07-17T08:46:04.5554632Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:46:04.5556380Z import pkg_resources 2025-07-17T08:46:04.6808039Z Running profiler/test_kineto 1/1 ... [2025-07-17 08:46:04.680373] 2025-07-17T08:46:04.6808666Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:46:04.6810792Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_kineto.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:46:04.680770] 2025-07-17T08:46:09.3019924Z 2025-07-17T08:46:09.3021405Z profiler/test_kineto 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_kineto_1.1_23defec43cd0656e_.log 2025-07-17T08:46:09.3023418Z Running 1 items in this shard: test/profiler/test_kineto.py::SimpleKinetoInitializationTest::test_kineto_profiler_with_environment_variable 2025-07-17T08:46:09.3024526Z 2025-07-17T08:46:12.5414583Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:46:12.5417637Z import pkg_resources 2025-07-17T08:46:12.6669475Z Running test_fx_experimental 1/1 ... [2025-07-17 08:46:12.666531] 2025-07-17T08:46:12.6670466Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:46:12.6672869Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_experimental.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:46:12.666910] 2025-07-17T08:46:24.7335283Z 2025-07-17T08:46:24.7336584Z test_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_1.1_c42e06e0d46e64de_.log 2025-07-17T08:46:25.9991294Z Running 34299 items in this shard: test/test_ops.py::TestSelfKwarg::test_self_kwargs, test/test_ops.py::TestCommonCPU::test_compare_cpu_H_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_T_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu___getitem___cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu___radd___cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu___rand___cpu_int64, test/test_ops.py::TestCommonCPU::test_compare_cpu___rdiv___cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu___rmatmul___cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu___rmod___cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu___rmul___cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu___ror___cpu_int64, test/test_ops.py::TestCommonCPU::test_compare_cpu___rpow___cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu___rsub___cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu___rxor___cpu_int64, test/test_ops.py::TestCommonCPU::test_compare_cpu__batch_norm_with_update_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__chunk_cat_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__native_batch_norm_legit_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_T_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_bfloat16_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_bool_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_byte_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_cdouble_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_cfloat_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_chalf_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_char_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_complex_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_double_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_float_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_half_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_int_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_long_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_polar_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_short_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_addcdiv_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_addcmul_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_addr_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_alias_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_arange_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_as_strided_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_as_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_as_strided_partial_views_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_as_strided_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_atan2_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_atleast_1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_atleast_2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_atleast_3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_bitwise_left_shift_cpu_int64, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_bitwise_right_shift_cpu_int64, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_block_diag_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_bucketize_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_cauchy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_chunk_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_column_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_constant_pad_nd_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_contiguous_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_copysign_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_cumprod_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_cumsum_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_diag_embed_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_diagonal_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_diagonal_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_diagonal_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_div_floor_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_div_trunc_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_dsplit_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_dstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_empty_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_empty_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_empty_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_expand_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_expand_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_expand_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_exponential_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_eye_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_fft_fftshift_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_fft_ifftshift_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_flip_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_fliplr_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_flipud_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_fmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_fmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_geometric_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_hsplit_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_hstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_hypot_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_igamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_igammac_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_index_add_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_index_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_index_fill_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_index_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_istft_cpu_complex64, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_lerp_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_linalg_diagonal_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_linalg_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_linalg_svd_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_linalg_svdvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_linalg_vector_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_linspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_log_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_logaddexp2_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_logaddexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_logspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_logsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_masked_fill_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_movedim_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_mul_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_narrow_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_narrow_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_new_empty_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_new_empty_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_new_full_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_new_ones_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_new_zeros_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nextafter_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_alpha_dropout_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_dropout_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_glu_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_pixel_shuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_relu6_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_softmin_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_normal__in_place_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_normal_number_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_ones_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_permute_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_randn_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_renorm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_repeat_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_reshape_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_reshape_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_rot90_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_rsub_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_select_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_special_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_special_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_special_xlog1py_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_special_zeta_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_split_with_sizes_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_std_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_stft_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_sum_to_size_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_t_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_take_along_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_to_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_trace_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_transpose_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_tril_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_triu_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_true_divide_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_unflatten_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_unfold_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_unfold_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_unsqueeze_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_unsqueeze_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_var_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_vdot_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_view_as_complex_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_view_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_view_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_compare_cpu_empty_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_empty_permuted_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_empty_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_expand_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_expand_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_expand_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_exponential_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_eye_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_fft_fftshift_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_fft_ifftshift_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_flip_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_fliplr_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_flipud_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_compare_cpu_hypot_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_igamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_igammac_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_index_add_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_index_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_index_fill_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_index_put_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_index_reduce_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_index_reduce_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_index_reduce_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_index_reduce_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_index_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_inner_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_int_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_isin_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_istft_cpu_complex64, test/test_ops.py::TestCommonCPU::test_compare_cpu_kron_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_kthvalue_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_ldexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_lerp_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_cholesky_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_cholesky_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_cond_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_det_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_diagonal_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_eig_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_eigh_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_eigvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_householder_product_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_inv_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_inv_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_ldl_factor_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_ldl_factor_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_ldl_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_lstsq_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_lu_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_lu_factor_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_lu_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_matrix_power_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_matrix_rank_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_matrix_rank_hermitian_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_multi_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_pinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_pinv_hermitian_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_compare_cpu_mode_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_movedim_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_msort_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_mul_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_multinomial_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_mv_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nanmedian_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nanquantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_narrow_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_narrow_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_native_batch_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_native_dropout_backward_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_new_empty_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_new_empty_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_new_full_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_new_ones_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_new_zeros_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nextafter_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_alpha_dropout_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_batch_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_binary_cross_entropy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_conv1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_conv2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_conv3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_cosine_embedding_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_cosine_similarity_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_cross_entropy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_ctc_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_dropout2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_dropout3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_dropout_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_embedding_bag_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_embedding_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_fractional_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_gaussian_nll_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_glu_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_hardswish_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_instance_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_interpolate_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_interpolate_linear_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_interpolate_trilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_kl_div_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_linear_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_max_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_max_unpool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_max_unpool1d_grad_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_max_unpool2d_grad_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_max_unpool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_max_unpool3d_grad_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_multi_head_attention_forward_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_multi_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_multilabel_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_normalize_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_pad_circular_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_compare_cpu_special_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_special_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_special_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_special_hermite_polynomial_h_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_special_laguerre_polynomial_l_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_special_legendre_polynomial_p_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_special_shifted_chebyshev_polynomial_u_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_compare_cpu_stft_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_sum_to_size_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_svd_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_svd_lowrank_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_t_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_take_along_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_take_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_tensordot_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_to_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_to_sparse_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_topk_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_torch__scaled_mm_cpu_float8_e4m3fn, 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test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_addmv_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_addr_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_alias_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_all_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_aminmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_angle_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_any_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_arange_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_argmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_argmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_as_strided_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_asin_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_asinh_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_atan2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_atan_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_atanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_baddbmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_bernoulli_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_bmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_bucketize_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cat_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_ceil_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cholesky_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cholesky_inverse_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cholesky_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_clamp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_clamp_max_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_clamp_min_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_column_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_complex_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_conj_physical_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_copysign_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cos_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cosh_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cross_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cummax_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cummin_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cumprod_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cumsum_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_deg2rad_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_diag_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_diagonal_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_diff_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_digamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_div_floor_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_div_trunc_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_dstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_empty_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_eq_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_equal_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_erf_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_erfc_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_erfinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_exp2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_exp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_expand_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_expm1_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_eye_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_fft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_fft_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_fftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_hfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_hfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_hfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_ifft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_ifft_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_ifftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_ihfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_ihfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_ihfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_irfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_irfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_irfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_rfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_rfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_rfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_float_power_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_floor_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_floor_divide_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fmod_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_frac_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_frexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_full_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_gather_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_ge_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_geqrf_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_gt_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_heaviside_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_histc_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_histogram_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_histogramdd_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_hstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_hypot_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_i0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_igamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_igammac_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_index_add_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_index_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_index_reduce_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_index_reduce_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_index_reduce_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_index_reduce_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_index_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_inner_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_isin_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_isneginf_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_isposinf_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_kron_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_kthvalue_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_ldexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_le_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_lerp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_lgamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_cholesky_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_cholesky_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_cond_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_cross_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_det_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_eig_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_eigh_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_eigvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_householder_product_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_inv_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_inv_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_ldl_factor_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_ldl_factor_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_ldl_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_lstsq_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_lu_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_lu_factor_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_lu_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_matrix_power_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_matrix_rank_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_matrix_rank_hermitian_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_multi_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_pinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_pinv_hermitian_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_qr_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_slogdet_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_solve_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_svd_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_svdvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_tensorinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_tensorsolve_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_vecdot_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_vector_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_log10_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_log1p_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_log2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_log_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_log_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logaddexp2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logaddexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logcumsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logical_and_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logical_not_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logical_or_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logical_xor_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logit_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_lt_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_lu_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_lu_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_lu_unpack_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_masked_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_matmul_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_max_binary_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_max_reduction_no_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_maximum_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_min_binary_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_min_reduction_no_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_minimum_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_mm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_mode_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_msort_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_mul_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_multinomial_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_mv_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nan_to_num_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nanmean_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nanquantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nansum_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_narrow_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_native_batch_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_ne_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_neg_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nextafter_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_gelu_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_linear_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_normalize_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_softplus_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nonzero_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_norm_fro_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_norm_inf_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_norm_nuc_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_normal_number_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_ones_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_ormqr_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_outer_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_permute_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_polar_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_polygamma_polygamma_n_2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_pow_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_qr_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_quantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_rad2deg_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_randn_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_reciprocal_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_remainder_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_renorm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_round_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_round_decimals_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_round_decimals_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_round_decimals_neg_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_rsqrt_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_scatter_add_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_scatter_reduce_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_searchsorted_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sgn_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sigmoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sign_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_signbit_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sin_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sinc_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sinh_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_slice_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sort_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_airy_ai_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_bessel_j0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_bessel_j1_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_bessel_y0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_bessel_y1_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_entr_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_erfcx_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_hermite_polynomial_h_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_i0e_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_i1_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_i1e_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_laguerre_polynomial_l_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_legendre_polynomial_p_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_log_ndtr_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_modified_bessel_i0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_modified_bessel_i1_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_modified_bessel_k0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_modified_bessel_k1_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_ndtr_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_ndtri_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_scaled_modified_bessel_k0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_scaled_modified_bessel_k1_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_spherical_bessel_j0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_xlog1py_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_zeta_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_split_with_sizes_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sqrt_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_square_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_squeeze_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_std_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sub_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_svd_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_t_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_take_along_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_take_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_tan_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_tanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_tensordot_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_topk_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_transpose_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_triangular_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_tril_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_triu_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_true_divide_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_trunc_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_unbind_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_unfold_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_unsqueeze_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_var_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_vdot_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_view_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_vstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_where_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_xlogy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_zeros_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_H_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_H_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_T_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_T_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___getitem___cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices___getitem___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___radd___cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices___radd___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___rand___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___rdiv___cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices___rdiv___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___rmatmul___cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices___rmatmul___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___rmod___cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices___rmul___cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices___rmul___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___ror___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___rpow___cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices___rpow___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___rsub___cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices___rsub___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___rxor___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices__batch_norm_with_update_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices__chunk_cat_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices__chunk_cat_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices__native_batch_norm_legit_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices__segment_reduce_lengths_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices__segment_reduce_offsets_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices__softmax_backward_data_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices__unsafe_masked_index_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices__unsafe_masked_index_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices__unsafe_masked_index_put_accumulate_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices__unsafe_masked_index_put_accumulate_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices__upsample_bilinear2d_aa_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_abs_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_abs_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_acos_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_acos_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_acosh_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_acosh_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_add_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_add_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_addbmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_addbmm_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_addcdiv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_addcmul_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_addcmul_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_addmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_addmm_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_addmm_decomposed_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_addmm_decomposed_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_addmv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_addmv_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_addr_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_addr_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_alias_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_alias_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_all_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_all_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_allclose_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_amax_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_amin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_aminmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_aminmax_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_angle_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_angle_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_any_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_any_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_arange_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_arange_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_argmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_argmax_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_argmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_argmin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_argsort_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_argsort_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_argwhere_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_argwhere_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_partial_views_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_partial_views_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_asin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_asin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_asinh_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_asinh_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_atan2_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_atan2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_atan_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_atan_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_atanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_atanh_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_atleast_1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_atleast_1d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_atleast_2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_atleast_2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_atleast_3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_atleast_3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_baddbmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_baddbmm_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bernoulli_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_bfloat16_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_bfloat16_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bincount_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_and_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_left_shift_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_not_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_or_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_right_shift_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_xor_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_block_diag_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_block_diag_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_bmm_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bool_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_bool_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_broadcast_shapes_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_broadcast_tensors_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_broadcast_tensors_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_broadcast_to_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_broadcast_to_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bucketize_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_bucketize_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_byte_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_byte_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cartesian_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cartesian_prod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cat_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cat_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cauchy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cdist_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cdouble_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cdouble_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_ceil_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ceil_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cfloat_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cfloat_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_chalf_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_chalf_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_char_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_char_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cholesky_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cholesky_inverse_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cholesky_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_chunk_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_chunk_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_clamp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_clamp_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_clamp_max_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_clamp_max_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_clamp_min_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_clamp_min_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_clone_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_clone_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_column_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_column_stack_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_combinations_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_combinations_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_complex_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_conj_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_conj_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_conj_physical_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_conj_physical_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_constant_pad_nd_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_constant_pad_nd_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_contiguous_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_contiguous_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_copysign_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_copysign_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_corrcoef_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_corrcoef_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cos_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cos_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cosh_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cosh_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_count_nonzero_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_count_nonzero_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cov_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cov_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cross_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cross_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cummax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cummax_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cummin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cummin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cumprod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cumprod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cumsum_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cumsum_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cumulative_trapezoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cumulative_trapezoid_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_deg2rad_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_deg2rad_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_diag_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_diag_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_diag_embed_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_diag_embed_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagflat_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagflat_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagonal_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagonal_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagonal_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagonal_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagonal_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagonal_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_diff_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_diff_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_digamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_digamma_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_dist_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_div_floor_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_div_floor_rounding_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_div_no_rounding_mode_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_div_trunc_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_div_trunc_rounding_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_dot_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_double_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_double_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_dsplit_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_dsplit_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_dstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_dstack_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_einsum_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_einsum_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_like_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_permuted_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_permuted_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_strided_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_eq_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_eq_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_equal_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_equal_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_erf_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_erf_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_erfc_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_erfc_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_erfinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_erfinv_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_exp2_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_exp2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_exp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_exp_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_expand_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_expand_as_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_expand_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_expand_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_expand_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_expand_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_expm1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_expm1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_exponential_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_eye_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_eye_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fft2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fft_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fft_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fftn_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fftshift_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fftshift_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_hfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_hfft2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_hfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_hfft_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_hfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_hfftn_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifft2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifft_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifft_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifftn_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifftshift_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifftshift_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ihfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ihfft2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ihfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ihfft_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ihfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ihfftn_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_irfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_irfft2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_irfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_irfft_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_irfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_irfftn_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_rfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_rfft2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_rfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_rfft_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_rfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_rfftn_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fill_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fill_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_flatten_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_flatten_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_flip_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_flip_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fliplr_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fliplr_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_flipud_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_flipud_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_float_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_float_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_float_power_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_float_power_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_floor_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_floor_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_floor_divide_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_floor_divide_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fmax_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fmin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fmod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fmod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_frac_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_frexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_full_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_full_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_full_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_full_like_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_gather_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_gather_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_gcd_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_ge_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ge_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_geometric_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_geometric_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_geqrf_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_gradient_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_gradient_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_grid_sampler_2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_gt_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_gt_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_half_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_half_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_heaviside_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_heaviside_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_histc_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_histogram_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_histogramdd_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_hsplit_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_hsplit_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_hstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_hstack_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_hypot_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_i0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_i0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_igamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_igammac_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_add_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_add_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_fill_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_fill_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_put_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_put_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_reduce_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_reduce_amax_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_reduce_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_reduce_amin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_reduce_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_reduce_mean_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_reduce_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_reduce_prod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_select_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_inner_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_inner_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_int_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_int_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_isclose_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_isclose_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_isfinite_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_isfinite_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_isin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_isin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_isinf_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_isinf_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_isnan_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_isnan_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_isneginf_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_isneginf_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_isposinf_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_isposinf_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_isreal_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_isreal_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_item_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_item_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_2inputs_2outputs_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_2inputs_2outputs_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_4inputs_with_extra_args_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_4inputs_with_extra_args_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_binary_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_binary_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_binary_return_by_ref_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_binary_return_by_ref_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_unary_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_unary_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_kron_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_kron_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_kthvalue_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_kthvalue_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_lcm_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_ldexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ldexp_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_le_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_le_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_lerp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_lgamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_lgamma_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_cholesky_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_cholesky_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_cond_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_cross_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_cross_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_det_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_diagonal_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_diagonal_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_eig_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_eigh_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_eigvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_householder_product_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_inv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_inv_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_ldl_factor_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_ldl_factor_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_ldl_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_lstsq_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_lu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_lu_factor_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_lu_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_matrix_power_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_matrix_rank_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_matrix_rank_hermitian_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_multi_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_multi_dot_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_pinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_pinv_hermitian_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_pinv_singular_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_qr_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_slogdet_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_solve_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_svd_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_svdvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_tensorinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_tensorsolve_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_vander_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_vander_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_vecdot_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_vector_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linspace_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linspace_tensor_overload_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_log10_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_log10_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_log1p_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_log1p_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_log2_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_log2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_log_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_log_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_log_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_log_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_log_softmax_with_dtype_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_logaddexp2_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logaddexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logcumsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logdet_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logical_and_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logical_and_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_logical_not_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logical_not_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_logical_or_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logical_or_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_logical_xor_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logical_xor_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_logit_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logit_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_logspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logspace_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logspace_tensor_overload_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_logsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logsumexp_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_long_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_long_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_lt_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_lt_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_lu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_lu_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_lu_unpack_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mH_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mH_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_mT_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mT_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_amax_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_amin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_argmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_argmax_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_argmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_argmin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_cumprod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_cumprod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_cumsum_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_cumsum_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_fill_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_fill_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_log_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_logaddexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_logsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_logsumexp_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_median_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_normalize_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_prod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_select_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_softmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_std_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_std_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_sum_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_var_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_var_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_matmul_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_matmul_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_matrix_exp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_max_binary_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_max_binary_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_max_pool2d_with_indices_backward_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_max_reduction_no_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_max_reduction_no_dim_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_max_reduction_with_dim_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_maximum_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_maximum_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_median_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_median_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_meshgrid_list_of_tensors_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_meshgrid_variadic_tensors_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_meshgrid_variadic_tensors_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_min_binary_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_min_binary_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_min_reduction_no_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_min_reduction_no_dim_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_min_reduction_with_dim_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_minimum_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_minimum_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_mm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mm_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_mode_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mode_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_movedim_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_movedim_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_msort_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_msort_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_mul_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mul_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_multinomial_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mv_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mvlgamma_mvlgamma_p_5_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nan_to_num_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nan_to_num_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nanmean_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nanmedian_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nanmedian_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nanquantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nansum_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nansum_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_narrow_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_narrow_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_narrow_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_narrow_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_native_batch_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_native_dropout_backward_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_native_dropout_backward_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_native_layer_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ne_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ne_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_neg_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_neg_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_empty_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_empty_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_empty_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_empty_strided_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_full_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_full_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_ones_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_ones_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_zeros_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_zeros_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nextafter_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_alpha_dropout_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_avg_pool1d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_avg_pool2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_avg_pool3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_batch_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_bilinear_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_binary_cross_entropy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_celu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_channel_shuffle_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv1d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv_transpose1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv_transpose1d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv_transpose2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv_transpose2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv_transpose3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv_transpose3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_cosine_embedding_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_cosine_embedding_loss_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_cosine_similarity_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_cross_entropy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_ctc_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_dropout2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_dropout3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_dropout_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_elu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_embedding_bag_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_embedding_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_feature_alpha_dropout_without_train_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_fractional_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_gaussian_nll_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_gelu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_glu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_hardsigmoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_hardswish_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_hardtanh_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_instance_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_interpolate_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_interpolate_linear_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_interpolate_trilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_kl_div_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_l1_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_layer_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_linear_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_linear_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_local_response_norm_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_margin_ranking_loss_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_pool2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_pool3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_unpool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_unpool1d_grad_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_unpool2d_grad_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_unpool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_unpool3d_grad_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_mish_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_mse_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_multi_head_attention_forward_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_multi_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_multilabel_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_normalize_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_one_hot_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_circular_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_circular_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_constant_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_constant_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_reflect_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_replicate_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_replicate_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_replicate_negative_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pairwise_distance_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pairwise_distance_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pdist_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pixel_shuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pixel_shuffle_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pixel_unshuffle_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_poisson_nll_loss_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_prelu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_relu6_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_relu6_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_relu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_relu_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_rms_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_rrelu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_selu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_silu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_smooth_l1_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_soft_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_softmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_softmin_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_softmin_with_dtype_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_softplus_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_softsign_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_softsign_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_tanhshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_tanhshrink_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_threshold_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_threshold_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_triplet_margin_loss_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_triplet_margin_with_distance_loss_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_unfold_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nonzero_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nonzero_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nonzero_static_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nonzero_static_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_norm_fro_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_norm_inf_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_norm_nuc_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_normal_in_place_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_normal_number_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ones_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ones_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_ones_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ones_like_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_ormqr_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_outer_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_outer_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_pca_lowrank_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_permute_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_permute_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_permute_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_permute_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_pinverse_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_polar_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_2_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_3_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_4_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_positive_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_positive_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_pow_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_pow_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_prod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_put_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_put_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_qr_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_quantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_rad2deg_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_rad2deg_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_rand_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_randint_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_randint_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_randint_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_randint_like_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_randn_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_randn_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ravel_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ravel_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_real_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_real_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_reciprocal_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_reciprocal_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_remainder_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_remainder_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_renorm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_repeat_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_repeat_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_repeat_interleave_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_repeat_interleave_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_reshape_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_reshape_as_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_reshape_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_reshape_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_resize__cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_resize__cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_resize_as__cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_resize_as__cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_resolve_conj_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_resolve_conj_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_resolve_neg_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_resolve_neg_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_roll_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_roll_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_rot90_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_rot90_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_round_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_round_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_round_decimals_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_round_decimals_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_round_decimals_neg_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_rsqrt_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_rsqrt_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_rsub_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_rsub_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_scalar_tensor_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_scalar_tensor_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_add_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_add_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_amax_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_amin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_mean_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_prod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_sum_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_searchsorted_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_searchsorted_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_select_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_select_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_select_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sgn_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sgn_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_short_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_short_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sigmoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sigmoid_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sign_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sign_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_bartlett_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_blackman_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_cosine_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_exponential_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_gaussian_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_general_cosine_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_general_hamming_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_hamming_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_hann_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_kaiser_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_nuttall_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signbit_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signbit_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sinc_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sinc_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sinh_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sinh_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_slice_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_slice_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_slice_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_slice_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_softmax_with_dtype_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sort_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sort_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sparse_mm_reduce_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_airy_ai_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_airy_ai_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_bessel_j0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_bessel_j0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_bessel_j1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_bessel_j1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_bessel_y0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_bessel_y0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_bessel_y1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_bessel_y1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_t_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_u_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_v_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_w_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_entr_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_entr_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_erfcx_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_erfcx_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_hermite_polynomial_h_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_hermite_polynomial_h_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_hermite_polynomial_he_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_i0e_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_i0e_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_i1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_i1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_i1e_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_i1e_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_laguerre_polynomial_l_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_laguerre_polynomial_l_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_legendre_polynomial_p_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_legendre_polynomial_p_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_log_ndtr_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_log_ndtr_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_i0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_i0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_i1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_i1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_k0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_k0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_k1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_k1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_ndtr_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_ndtr_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_ndtri_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_ndtri_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_polygamma_special_polygamma_n_0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_scaled_modified_bessel_k0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_scaled_modified_bessel_k0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_scaled_modified_bessel_k1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_scaled_modified_bessel_k1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_shifted_chebyshev_polynomial_t_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_shifted_chebyshev_polynomial_u_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_shifted_chebyshev_polynomial_v_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_shifted_chebyshev_polynomial_w_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_spherical_bessel_j0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_spherical_bessel_j0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_xlog1py_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_xlog1py_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_zeta_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_zeta_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_split_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_split_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_split_list_args_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_split_list_args_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_split_with_sizes_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_split_with_sizes_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_split_with_sizes_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_split_with_sizes_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sqrt_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sqrt_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_square_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_square_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_squeeze_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_squeeze_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_squeeze_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_squeeze_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_squeeze_multiple_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_squeeze_multiple_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_stack_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_std_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_std_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_std_mean_unbiased_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_std_unbiased_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_stft_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sub_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sub_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sum_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sum_to_size_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sum_to_size_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_svd_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_svd_lowrank_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_t_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_t_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_t_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_take_along_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_take_along_dim_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_take_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_take_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_tan_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_tan_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_tanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_tanh_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_tensor_split_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_tensor_split_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_tensordot_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_tensordot_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_tile_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_tile_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_to_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_to_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_to_sparse_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_to_sparse_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_topk_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_topk_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_torch_ops_aten__safe_softmax_default_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_trace_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_trace_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_transpose_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_transpose_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_transpose_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_transpose_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_trapezoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_trapezoid_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_trapz_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_trapz_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_triangular_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_tril_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_tril_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_tril_indices_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_triu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_triu_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_triu_indices_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_true_divide_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_true_divide_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_trunc_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_trunc_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_unbind_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_unbind_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_unbind_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_unbind_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_unflatten_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_unflatten_cpu_int64, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_angle_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_angle_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_any_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_any_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_any_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_arange_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_arange_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_argmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_argmax_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_argmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_argmin_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_argsort_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_argsort_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_argwhere_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_argwhere_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_argwhere_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_partial_views_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_partial_views_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_partial_views_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_scatter_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_asin_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_asin_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_asin_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_asinh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_asinh_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_asinh_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atan2_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atan2_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atan_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atan_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atan_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atanh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atanh_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atleast_1d_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atleast_1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atleast_1d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atleast_2d_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atleast_2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atleast_2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atleast_3d_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atleast_3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atleast_3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_baddbmm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_baddbmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_baddbmm_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bernoulli_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bfloat16_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bfloat16_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bfloat16_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bincount_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bitwise_and_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bitwise_left_shift_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bitwise_not_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bitwise_or_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bitwise_right_shift_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bitwise_xor_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_block_diag_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_block_diag_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_block_diag_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bmm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bmm_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bool_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bool_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bool_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_broadcast_shapes_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_broadcast_tensors_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_broadcast_tensors_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_broadcast_tensors_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_broadcast_to_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_broadcast_to_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_broadcast_to_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bucketize_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bucketize_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_byte_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_byte_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_byte_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cartesian_prod_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cartesian_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cartesian_prod_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cat_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cat_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cat_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cauchy_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cdist_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cdouble_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cdouble_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cdouble_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ceil_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ceil_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cfloat_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cfloat_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cfloat_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_chalf_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_chalf_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_chalf_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_char_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_char_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_char_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cholesky_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cholesky_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cholesky_inverse_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cholesky_inverse_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cholesky_solve_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cholesky_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_chunk_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_chunk_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_chunk_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_clamp_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_clamp_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_clamp_max_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_clamp_max_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_clamp_min_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_clamp_min_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_clone_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_clone_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_clone_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_column_stack_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_column_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_column_stack_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_combinations_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_combinations_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_combinations_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_complex_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_conj_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_conj_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_conj_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_conj_physical_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_conj_physical_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_conj_physical_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_constant_pad_nd_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_constant_pad_nd_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_constant_pad_nd_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_contiguous_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_contiguous_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_contiguous_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_copysign_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_copysign_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_corrcoef_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_corrcoef_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_corrcoef_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cos_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cos_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cos_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cosh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cosh_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cosh_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_count_nonzero_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_count_nonzero_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_count_nonzero_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cov_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cov_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cov_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cross_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cross_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cross_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cummax_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cummax_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cummin_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cummin_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cumprod_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cumprod_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cumprod_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cumsum_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cumsum_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cumsum_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cumulative_trapezoid_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cumulative_trapezoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cumulative_trapezoid_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_deg2rad_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_deg2rad_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diag_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diag_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diag_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diag_embed_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diag_embed_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diag_embed_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagflat_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagflat_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagflat_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagonal_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagonal_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagonal_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagonal_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagonal_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagonal_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagonal_scatter_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagonal_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diagonal_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diff_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diff_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_diff_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_digamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_digamma_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_dist_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_dist_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_div_floor_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_div_floor_rounding_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_div_no_rounding_mode_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_div_no_rounding_mode_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_div_trunc_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_div_trunc_rounding_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_dot_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_dot_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_double_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_double_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_double_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_dsplit_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_dsplit_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_dsplit_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_dstack_cpu_complex64, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_empty_permuted_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_empty_permuted_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_empty_strided_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_empty_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_empty_strided_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_eq_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_eq_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_eq_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_equal_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_equal_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_equal_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_erf_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_fmax_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_fmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_fmin_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_fmod_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_fmod_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_frac_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_frexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_full_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_full_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_full_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_full_like_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_full_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_full_like_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_gather_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_gather_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_gather_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_gcd_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ge_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ge_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_geometric_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_geometric_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_geqrf_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_geqrf_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_gradient_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_gradient_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_gradient_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_grid_sampler_2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_gt_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_gt_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_half_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_half_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_half_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_heaviside_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_heaviside_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_histc_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_histogram_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_index_select_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_inner_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_inner_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_inner_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_int_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_int_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_int_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isclose_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isclose_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isclose_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isfinite_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isfinite_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isfinite_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isin_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isin_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isinf_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isinf_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isinf_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isnan_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isnan_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isnan_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isneginf_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isneginf_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_isposinf_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_linalg_vector_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_linspace_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_linspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_linspace_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_linspace_tensor_overload_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_linspace_tensor_overload_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log10_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log10_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log10_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log1p_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log1p_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log1p_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log2_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log2_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log2_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log_softmax_with_dtype_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_log_softmax_with_dtype_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logical_not_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logical_not_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logical_not_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logical_or_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logical_or_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logical_or_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logical_xor_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logical_xor_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logical_xor_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logit_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logit_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logspace_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logspace_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logspace_tensor_overload_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logspace_tensor_overload_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logsumexp_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_logsumexp_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_long_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_long_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_long_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_lt_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_lt_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_lu_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_lu_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_lu_solve_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_lu_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_lu_unpack_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_lu_unpack_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_mH_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_mH_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_mH_cpu_int64, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_cumprod_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_cumprod_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_cumsum_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_cumsum_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_cumsum_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_fill_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_fill_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_fill_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_log_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_logaddexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_logsumexp_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_logsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_logsumexp_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_mean_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_median_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_normalize_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_normalize_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_prod_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_prod_cpu_int64, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_sum_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_sum_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_var_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_var_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_masked_var_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_matmul_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_matmul_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_matmul_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_matrix_exp_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_matrix_exp_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_max_binary_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_alpha_dropout_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_avg_pool1d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_avg_pool2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_avg_pool3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_batch_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_bilinear_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_binary_cross_entropy_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_celu_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_channel_shuffle_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_channel_shuffle_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv1d_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv1d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv2d_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv3d_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv_transpose1d_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv_transpose1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv_transpose1d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv_transpose2d_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv_transpose2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv_transpose2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv_transpose3d_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv_transpose3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_conv_transpose3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_cosine_embedding_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_cosine_embedding_loss_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_cosine_similarity_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_cross_entropy_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_ctc_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_dropout2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_dropout3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_dropout_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_elu_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_embedding_bag_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_embedding_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_feature_alpha_dropout_without_train_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_feature_alpha_dropout_without_train_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_fractional_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_gaussian_nll_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_gelu_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_glu_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_hardsigmoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_hardswish_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_hardtanh_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_instance_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_interpolate_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_interpolate_linear_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_interpolate_trilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_kl_div_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_l1_loss_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_l1_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_layer_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_linear_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_linear_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_linear_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_local_response_norm_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_margin_ranking_loss_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_pool2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_pool3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_unpool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_unpool1d_grad_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_unpool2d_grad_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_unpool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_unpool3d_grad_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_mish_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_mse_loss_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_circular_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_circular_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_constant_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_constant_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_constant_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_reflect_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_reflect_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_replicate_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_replicate_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_soft_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_softmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_softmin_with_dtype_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_softmin_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_softmin_with_dtype_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_softplus_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_softsign_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_softsign_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_softsign_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_tanhshrink_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_tanhshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_tanhshrink_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_threshold_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_threshold_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_triplet_margin_loss_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_triplet_margin_loss_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_triplet_margin_with_distance_loss_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_triplet_margin_with_distance_loss_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_unfold_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_unfold_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nonzero_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nonzero_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nonzero_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nonzero_static_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nonzero_static_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nonzero_static_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_norm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_norm_fro_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_norm_fro_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_norm_inf_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_norm_inf_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_norm_nuc_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_norm_nuc_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_normal_in_place_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_normal_in_place_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_normal_number_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ones_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ones_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ones_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ones_like_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ones_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ones_like_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ormqr_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ormqr_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_outer_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_outer_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_polygamma_polygamma_n_0_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_polygamma_polygamma_n_1_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_polygamma_polygamma_n_2_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_polygamma_polygamma_n_2_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_polygamma_polygamma_n_3_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_polygamma_polygamma_n_4_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_positive_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_positive_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_positive_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_pow_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_pow_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_pow_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_prod_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_prod_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_put_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_put_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_put_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_qr_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_qr_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_quantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rad2deg_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rad2deg_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rand_like_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rand_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_randint_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_randint_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_randint_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_randint_like_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_randn_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_randn_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_randn_like_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_randn_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ravel_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ravel_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ravel_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_real_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_real_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_real_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_reciprocal_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_reciprocal_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_reciprocal_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_remainder_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_remainder_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_renorm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_renorm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_repeat_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_repeat_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_repeat_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_repeat_interleave_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_repeat_interleave_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_repeat_interleave_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_reshape_as_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_reshape_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_reshape_as_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_reshape_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_reshape_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_reshape_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resize__cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resize__cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resize__cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resize_as__cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resize_as__cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resize_as__cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resolve_conj_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resolve_conj_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resolve_conj_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resolve_neg_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resolve_neg_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resolve_neg_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_roll_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_roll_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_roll_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rot90_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rot90_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rot90_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_round_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_round_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_round_decimals_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_round_decimals_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_round_decimals_neg_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rsqrt_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rsqrt_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rsqrt_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rsub_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rsub_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rsub_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scalar_tensor_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scalar_tensor_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scalar_tensor_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_add_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_add_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_add_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_reduce_amax_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_reduce_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_reduce_amin_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_reduce_mean_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_reduce_prod_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_scatter_reduce_sum_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_searchsorted_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_searchsorted_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_select_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_select_cpu_int64, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sign_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_signal_windows_bartlett_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_signal_windows_blackman_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_signal_windows_cosine_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_signal_windows_exponential_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_signal_windows_gaussian_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_signal_windows_general_cosine_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_signal_windows_general_hamming_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_signal_windows_hamming_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_signal_windows_hann_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_spherical_bessel_j0_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_xlog1py_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_xlog1py_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_zeta_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_zeta_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_list_args_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_list_args_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_list_args_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_with_sizes_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_with_sizes_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_with_sizes_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_with_sizes_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_with_sizes_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_split_with_sizes_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sqrt_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sqrt_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sqrt_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_square_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_square_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_square_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_squeeze_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_squeeze_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_squeeze_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_squeeze_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_squeeze_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_squeeze_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_squeeze_multiple_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_squeeze_multiple_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_squeeze_multiple_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_stack_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_stack_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_std_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_std_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_std_mean_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_std_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_std_mean_unbiased_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_std_mean_unbiased_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_std_unbiased_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_std_unbiased_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_stft_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_stft_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sub_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sub_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sub_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sum_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sum_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sum_to_size_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sum_to_size_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sum_to_size_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_svd_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_svd_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_svd_lowrank_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_svd_lowrank_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_t_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_t_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_t_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_t_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_t_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_take_along_dim_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_take_along_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_take_along_dim_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_take_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_take_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_take_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tan_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tan_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tan_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tanh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tanh_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tensor_split_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tensor_split_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tensor_split_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tensordot_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tensordot_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tensordot_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tile_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tile_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tile_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_to_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_to_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_to_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_to_sparse_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_to_sparse_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_to_sparse_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_topk_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_topk_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_torch_ops_aten__safe_softmax_default_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_trace_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_trace_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_trace_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_transpose_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_transpose_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_transpose_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_transpose_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_transpose_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_transpose_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_trapezoid_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_trapezoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_trapezoid_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_trapz_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_trapz_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_trapz_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_triangular_solve_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_triangular_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tril_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tril_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tril_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tril_indices_cpu_int64, 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test/test_ops.py::TestCommonCPU::test_out_ones_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_ones_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_ormqr_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_outer_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_pca_lowrank_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_permute_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_permute_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_pinverse_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_polar_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_polygamma_polygamma_n_2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_positive_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_pow_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_put_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_qr_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_quantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_rad2deg_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_rand_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_randint_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_randint_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_randn_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_randn_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_ravel_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_real_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_reciprocal_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_remainder_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_renorm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_repeat_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_repeat_interleave_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error__batch_norm_with_update_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error__native_batch_norm_legit_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_abs_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_abs_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_acos_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_acos_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_acosh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_acosh_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_add_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_add_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addbmm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addbmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addcdiv_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addcdiv_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addcmul_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addcmul_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addmm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addmm_decomposed_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addmm_decomposed_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addmv_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addmv_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addr_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_addr_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_alias_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_alias_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_angle_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_angle_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_arange_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_as_strided_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_as_strided_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_asin_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_asin_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_asinh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_asinh_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_atan2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_atan_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_atan_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_atanh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_atanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_baddbmm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_baddbmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_bernoulli_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_bmm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_bmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cat_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cat_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_ceil_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cholesky_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cholesky_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cholesky_inverse_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cholesky_inverse_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cholesky_solve_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cholesky_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_clamp_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_clamp_max_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_clamp_min_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_column_stack_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_column_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_complex_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_conj_physical_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_conj_physical_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_copysign_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cos_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cos_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cosh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cosh_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cross_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cross_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cummax_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cummin_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cumprod_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cumprod_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cumsum_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_cumsum_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_deg2rad_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_diag_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_diag_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_diagonal_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_diagonal_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_diff_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_diff_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_digamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_div_floor_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_div_no_rounding_mode_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_div_trunc_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_dot_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_dstack_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_dstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_erf_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_erfc_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_erfinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_exp2_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_exp2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_exp_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_exp_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_expand_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_expand_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_expm1_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_expm1_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_fft2_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_fft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_fft_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_fft_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_fftn_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_fftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_hfft2_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_hfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_hfft_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_hfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_hfftn_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_hfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_ifft2_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_ifft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_ifft_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_ifft_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_ifftn_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_ifftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_ihfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_ihfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_ihfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_irfft2_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_irfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_irfft_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_irfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_irfftn_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_irfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_rfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_rfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fft_rfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_float_power_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_float_power_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_floor_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_fmod_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_frac_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_frexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_full_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_full_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_gather_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_gather_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_hstack_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_hstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_hypot_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_i0_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_index_add_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_index_add_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_index_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_index_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_index_reduce_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_index_reduce_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_index_reduce_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_index_reduce_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_index_select_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_index_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_inner_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_inner_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_kron_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_kron_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_kthvalue_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_ldexp_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_ldexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_lerp_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_lerp_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_lgamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_cholesky_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_cholesky_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_cholesky_ex_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_cholesky_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_cond_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_cond_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_cross_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_cross_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_det_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_det_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_eig_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_eig_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_eigh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_eigh_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_eigvals_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_eigvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_eigvalsh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_householder_product_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_householder_product_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_inv_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_inv_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_inv_ex_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_inv_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_lstsq_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_lstsq_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_lu_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_lu_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_lu_factor_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_lu_factor_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_lu_factor_ex_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_lu_solve_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_lu_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_matrix_norm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_matrix_power_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_matrix_power_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_multi_dot_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_multi_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_norm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_norm_subgradients_at_zero_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_pinv_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_pinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_pinv_hermitian_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_pinv_hermitian_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_qr_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_qr_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_slogdet_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_slogdet_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_solve_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_solve_ex_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_solve_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_solve_triangular_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_svd_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_svd_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_svdvals_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_svdvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_tensorinv_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_tensorinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_tensorsolve_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_tensorsolve_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_vecdot_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_vecdot_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_vector_norm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linalg_vector_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linspace_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linspace_tensor_overload_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_log10_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_log10_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_log1p_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_log1p_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_log2_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_log2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_log_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_log_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_log_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_log_softmax_with_dtype_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logaddexp2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logaddexp_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logaddexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logcumsumexp_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logcumsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logit_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logspace_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logspace_tensor_overload_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logsumexp_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_logsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_lu_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_lu_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_lu_solve_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_lu_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_lu_unpack_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_lu_unpack_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_masked_select_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_masked_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_matmul_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_matmul_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_max_binary_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_max_reduction_no_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_maximum_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mean_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_min_binary_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_min_reduction_no_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_minimum_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mode_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_msort_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mul_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mul_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mv_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mv_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nan_to_num_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nanmean_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nanquantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nansum_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_native_batch_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_neg_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_neg_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nn_functional_gelu_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nn_functional_linear_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nn_functional_linear_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nn_functional_normalize_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nn_functional_normalize_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nn_functional_softplus_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_norm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_norm_fro_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_norm_fro_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_norm_inf_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_norm_inf_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_norm_nuc_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_norm_nuc_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_normal_number_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_ones_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_ones_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_ormqr_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_ormqr_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_outer_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_outer_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_permute_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_permute_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_polar_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_polygamma_polygamma_n_2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_pow_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_pow_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_qr_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_qr_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_quantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_rad2deg_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_reciprocal_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_reciprocal_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_remainder_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_renorm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_renorm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_round_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_round_decimals_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_round_decimals_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_round_decimals_neg_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_rsqrt_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_rsqrt_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_scatter_add_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_scatter_add_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_scatter_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_scatter_reduce_amin_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sgn_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sgn_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sigmoid_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sigmoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sign_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sin_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sin_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sinc_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sinc_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sinh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sinh_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_slice_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_softmax_with_dtype_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sort_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sparse_sampled_addmm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_special_entr_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_special_erfcx_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_special_i0e_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_special_i1_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_special_i1e_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_special_log_ndtr_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_special_ndtr_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_special_ndtri_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_special_xlog1py_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_split_with_sizes_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_split_with_sizes_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sqrt_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_sqrt_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_square_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_square_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_squeeze_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_squeeze_copy_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_take_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_take_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_tan_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_tan_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_tanh_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_tanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_tensordot_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_tensordot_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_topk_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_transpose_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_transpose_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_triangular_solve_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_triangular_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_tril_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_tril_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_triu_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_triu_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_true_divide_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_true_divide_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_trunc_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_unbind_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_unbind_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_unfold_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_unfold_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_unsqueeze_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_unsqueeze_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_var_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_var_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_vdot_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_vdot_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_view_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_view_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_requires_grad_error_vstack_cpu_complex64, 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test/test_ops.py::TestCommonCPU::test_out_stft_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_sub_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_sum_to_size_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_svd_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_svd_lowrank_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_t_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_take_along_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_take_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_tan_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_tanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_tensor_split_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_tensordot_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_tile_cpu_float32, test/test_ops.py::TestCommonCPU::test_out_to_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_out_warning_signal_windows_gaussian_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_signal_windows_general_cosine_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_signal_windows_general_hamming_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_signal_windows_hamming_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_signal_windows_hann_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_signal_windows_kaiser_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_signal_windows_nuttall_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_signbit_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_sin_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_sinc_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_sinh_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_slice_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_slice_scatter_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_softmax_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_softmax_with_dtype_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_sort_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_sparse_mm_reduce_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_sparse_sampled_addmm_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_airy_ai_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_bessel_j0_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_bessel_j1_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_bessel_y0_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_bessel_y1_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_chebyshev_polynomial_t_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_chebyshev_polynomial_u_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_chebyshev_polynomial_v_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_chebyshev_polynomial_w_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_entr_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_erfcx_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_hermite_polynomial_h_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_hermite_polynomial_he_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_i0e_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_i1_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_i1e_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_laguerre_polynomial_l_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_legendre_polynomial_p_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_log_ndtr_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_modified_bessel_i0_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_modified_bessel_i1_cpu, test/test_ops.py::TestCommonCPU::test_out_warning_special_modified_bessel_k0_cpu, 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test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_erfinv_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp2_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp2_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp2_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp2_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp2_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp2_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_exp_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_expm1_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_expm1_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_expm1_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_expm1_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_expm1_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_expm1_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_float_power_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_float_power_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_float_power_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_float_power_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_float_power_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_float_power_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_i0_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_i0_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_i0_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_i0_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_i0_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_i0_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_ldexp_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_ldexp_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_ldexp_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_ldexp_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_ldexp_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_ldexp_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_lgamma_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_lgamma_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_lgamma_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_lgamma_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_lgamma_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_lgamma_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log10_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log10_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log10_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log10_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log10_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log10_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log1p_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log1p_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log1p_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log1p_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log1p_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log1p_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log2_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log2_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log2_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log2_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log2_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log2_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_log_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_logit_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_logit_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_logit_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_logit_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_logit_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_logit_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_masked_std_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_masked_std_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_masked_std_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_masked_std_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_masked_std_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_masked_var_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_masked_var_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_masked_var_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_masked_var_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_masked_var_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_1_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_1_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_1_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_3_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_3_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_3_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_5_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_5_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_mvlgamma_mvlgamma_p_5_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_0_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_0_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_0_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_0_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_0_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_0_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_1_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_1_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_1_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_1_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_1_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_1_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_2_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_2_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_2_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_2_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_2_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_2_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_3_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_3_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_3_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_3_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_3_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_3_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_4_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_4_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_4_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_4_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_4_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_polygamma_polygamma_n_4_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rad2deg_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rad2deg_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rad2deg_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rad2deg_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rad2deg_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rad2deg_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_reciprocal_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_reciprocal_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_reciprocal_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_reciprocal_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_reciprocal_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_reciprocal_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rsqrt_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rsqrt_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rsqrt_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rsqrt_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rsqrt_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_rsqrt_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sigmoid_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sigmoid_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sigmoid_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sigmoid_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sigmoid_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sigmoid_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sin_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sin_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sin_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sin_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sin_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sin_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinc_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinc_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinc_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinc_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinc_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinc_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinh_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinh_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinh_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinh_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinh_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_sinh_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_t_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_t_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_t_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_t_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_t_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_t_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_u_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_u_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_u_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_u_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_u_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_u_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_v_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_v_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_v_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_v_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_v_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_v_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_w_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_w_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_w_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_w_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_w_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_chebyshev_polynomial_w_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_hermite_polynomial_h_cpu_bool, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_hermite_polynomial_h_cpu_int16, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_hermite_polynomial_h_cpu_int32, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_hermite_polynomial_h_cpu_int64, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_hermite_polynomial_h_cpu_int8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_hermite_polynomial_h_cpu_uint8, test/test_ops.py::TestCommonCPU::test_promotes_int_to_float_special_hermite_polynomial_he_cpu_bool, 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test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_asinh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_atan_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_atanh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_atleast_1d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_atleast_2d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_atleast_3d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_block_diag_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_broadcast_tensors_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_broadcast_to_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_cat_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_chunk_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_clone_cpu_complex64, 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test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_narrow_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_narrow_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_ne_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_neg_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_new_empty_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_new_empty_strided_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_new_full_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_new_ones_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_new_zeros_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_channel_shuffle_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_l1_loss_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_log_softmax_with_dtype_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_pairwise_distance_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_pixel_shuffle_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_pixel_unshuffle_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_softmax_with_dtype_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_softmin_with_dtype_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_tanhshrink_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_triplet_margin_loss_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_norm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_normal__in_place_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_ones_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_permute_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_permute_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_positive_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_pow_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_prod_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_randn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_ravel_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_real_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_reciprocal_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_renorm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_repeat_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_reshape_as_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_reshape_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_roll_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_rot90_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_rsqrt_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_rsub_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_sgn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_sigmoid_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_sin_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_sinc_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_sinh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_softmax_with_dtype_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_special_log_softmax_with_dtype_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_special_softmax_with_dtype_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_split_with_sizes_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_sqrt_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_square_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_squeeze_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_squeeze_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_squeeze_multiple_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_stack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_std_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_std_mean_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_stft_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_sub_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_sum_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_sum_to_size_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_t_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_t_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_take_along_dim_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_tan_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_tanh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_tensor_split_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_to_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_trace_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_transpose_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_transpose_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_tril_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_triu_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_true_divide_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_unbind_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_unbind_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_unflatten_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_unfold_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_unfold_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_unsqueeze_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_unsqueeze_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_var_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_var_mean_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_vdot_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_view_as_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_view_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_view_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_vsplit_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_vstack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_where_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_zeros_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__unsafe_masked_index_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__unsafe_masked_index_put_accumulate_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_abs_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_acos_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_acosh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_add_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_addbmm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_addcdiv_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_addcmul_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_addmm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_addmm_decomposed_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_addmv_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_addr_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_alias_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_all_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_allclose_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_angle_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_any_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_argwhere_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_as_strided_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_as_strided_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_as_strided_partial_views_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_as_strided_scatter_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_asin_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_asinh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_atan_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_atanh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_atleast_1d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_atleast_2d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_atleast_3d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_baddbmm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_bfloat16_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_block_diag_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_bmm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_bool_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_broadcast_tensors_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_broadcast_to_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_byte_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cartesian_prod_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cat_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cdouble_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cfloat_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_chalf_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_char_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cholesky_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cholesky_inverse_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cholesky_solve_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_chunk_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_clone_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_column_stack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_combinations_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_conj_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_conj_physical_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_constant_pad_nd_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_contiguous_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_corrcoef_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cos_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cosh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_count_nonzero_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cov_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cross_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cumprod_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cumsum_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cumulative_trapezoid_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_diag_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_diag_embed_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_diagflat_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_diagonal_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_diagonal_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_diagonal_scatter_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_diff_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_dist_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_div_no_rounding_mode_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_dot_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_double_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_dsplit_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_dstack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_einsum_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_empty_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_empty_like_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_empty_permuted_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_empty_strided_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_eq_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_equal_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_exp2_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_exp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_expand_as_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_expand_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_expand_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_expm1_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_eye_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_fft2_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_fft_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_fftn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_fftshift_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_hfft2_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_hfft_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_hfftn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_ifft2_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_ifft_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_ifftn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_ifftshift_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_irfft2_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_irfft_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_irfftn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fill_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_flatten_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_flip_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fliplr_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_flipud_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_float_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_float_power_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_full_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_full_like_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_gather_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_geqrf_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_gradient_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_half_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_hsplit_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_hstack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_imag_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_index_add_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_index_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_index_fill_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_index_put_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_index_select_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_inner_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_int_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_isclose_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_isfinite_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_isinf_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_isnan_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_isreal_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_istft_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_item_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_jiterator_2inputs_2outputs_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_jiterator_4inputs_with_extra_args_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_jiterator_binary_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_jiterator_binary_return_by_ref_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_jiterator_unary_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_kron_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_ldexp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_lerp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_cholesky_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_cholesky_ex_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_cond_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_cross_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_det_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_diagonal_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_eig_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_eigh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_eigvals_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_eigvalsh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_householder_product_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_inv_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_inv_ex_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_ldl_factor_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_ldl_factor_ex_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_ldl_solve_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_lstsq_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_lstsq_grad_oriented_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_lu_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_lu_factor_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_lu_factor_ex_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_lu_solve_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_matrix_norm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_matrix_power_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_matrix_rank_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_matrix_rank_hermitian_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_multi_dot_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_norm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_norm_subgradients_at_zero_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_pinv_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_pinv_hermitian_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_pinv_singular_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_qr_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_slogdet_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_solve_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_solve_ex_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_solve_triangular_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_svd_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_svdvals_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_tensorinv_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_tensorsolve_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_vander_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_vecdot_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_vector_norm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linspace_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linspace_tensor_overload_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_log10_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_log1p_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_log2_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_log_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_log_softmax_with_dtype_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logaddexp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logcumsumexp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logdet_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logical_and_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logical_not_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logical_or_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logical_xor_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logspace_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logspace_tensor_overload_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logsumexp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_long_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_lu_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_lu_solve_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_lu_unpack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_mH_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_mT_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_cumprod_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_cumsum_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_fill_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_logsumexp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_mean_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_normalize_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_prod_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_scatter_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_select_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_std_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_sum_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_var_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_matmul_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_matrix_exp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_mean_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_meshgrid_list_of_tensors_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_meshgrid_variadic_tensors_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_mm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_movedim_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_mul_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_mv_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_narrow_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_narrow_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_ne_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_neg_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_new_empty_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_new_empty_strided_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_new_full_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_new_ones_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_new_zeros_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_channel_shuffle_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_conv1d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_conv2d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_conv3d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_conv_transpose1d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_conv_transpose2d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_conv_transpose3d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_feature_alpha_dropout_without_train_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_l1_loss_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_linear_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_normalize_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pad_circular_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pad_constant_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pad_reflect_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pad_replicate_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pad_replicate_negative_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pairwise_distance_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pixel_shuffle_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pixel_unshuffle_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_rms_norm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_silu_complex_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_softmin_with_dtype_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_softsign_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_tanhshrink_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_triplet_margin_loss_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_triplet_margin_with_distance_loss_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_unfold_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nonzero_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nonzero_static_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_norm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_norm_fro_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_norm_inf_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_norm_nuc_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_normal_in_place_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_ones_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_ones_like_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_ormqr_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_outer_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_pca_lowrank_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_permute_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_permute_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_pinverse_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_positive_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_pow_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_prod_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_put_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_qr_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_rand_like_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_randn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_randn_like_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_ravel_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_real_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_reciprocal_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_renorm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_repeat_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_repeat_interleave_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_reshape_as_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_reshape_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_resize__cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_resize_as__cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_resolve_conj_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_resolve_neg_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_roll_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_rot90_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_rsqrt_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_rsub_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_scalar_tensor_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_scatter_add_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_scatter_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_select_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sgn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_short_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sigmoid_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sin_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sinc_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sinh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_slice_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_softmax_with_dtype_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sparse_sampled_addmm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_split_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_split_list_args_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_split_with_sizes_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_split_with_sizes_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sqrt_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_square_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_squeeze_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_squeeze_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_squeeze_multiple_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_stack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_std_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_std_mean_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_std_mean_unbiased_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_std_unbiased_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_stft_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sub_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sum_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sum_to_size_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_svd_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_svd_lowrank_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_t_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_t_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_take_along_dim_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_take_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_tan_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_tanh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_tensor_split_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_tensordot_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_tile_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_to_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_to_sparse_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_trace_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_transpose_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_transpose_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_trapezoid_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_trapz_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_triangular_solve_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_tril_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_triu_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_true_divide_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unbind_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unbind_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unflatten_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unfold_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unfold_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_uniform_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unsafe_chunk_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unsafe_split_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unsqueeze_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unsqueeze_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_var_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_var_mean_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_var_mean_unbiased_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_var_unbiased_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_vdot_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_view_as_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_view_as_real_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_view_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_view_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_vsplit_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_vstack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_where_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_zero__cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_zeros_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_zeros_like_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_H_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_T_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view___getitem___cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view___radd___cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view___rdiv___cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view___rmatmul___cpu_complex128, 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test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs__conversions_char_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs__conversions_double_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs__conversions_float_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs__conversions_half_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs__conversions_int_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs__conversions_long_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs__conversions_short_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_abs_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_acos_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_acosh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_add_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_addcdiv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_addcmul_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_addr_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_alias_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_all_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_allclose_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_any_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_as_strided_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_as_strided_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_as_strided_partial_views_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_as_strided_scatter_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_asin_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_asinh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_atan_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_atanh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_atleast_1d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_atleast_2d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_atleast_3d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_block_diag_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_broadcast_tensors_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_broadcast_to_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_cat_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_chunk_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_clone_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_column_stack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_conj_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_conj_physical_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_constant_pad_nd_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_contiguous_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_cos_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_cosh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_count_nonzero_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_cumprod_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_cumsum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_diag_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_diag_embed_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_diagonal_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_diagonal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_diagonal_scatter_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_div_no_rounding_mode_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_dot_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_dsplit_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_dstack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_empty_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_empty_like_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_empty_strided_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_eq_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_equal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_exp2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_exp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_expand_as_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_expand_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_expand_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_expm1_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_eye_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_fft2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_fft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_fftn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_fftshift_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_hfft2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_hfft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_hfftn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_ifft2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_ifft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_ifftn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_ifftshift_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_irfft2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_irfft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_irfftn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fill_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_flatten_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_flip_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fliplr_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_flipud_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_float_power_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_hsplit_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_hstack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_imag_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_index_add_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_index_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_index_fill_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_index_select_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_isclose_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_isfinite_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_isinf_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_isnan_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_isreal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_istft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_item_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_lerp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_linalg_cross_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_linalg_diagonal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_linalg_matrix_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_linalg_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_linalg_svd_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_linalg_svdvals_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_linalg_vecdot_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_linalg_vector_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_linspace_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_linspace_tensor_overload_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_log10_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_log1p_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_log2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_log_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_log_softmax_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logaddexp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logical_and_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logical_not_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logical_or_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logical_xor_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logspace_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logspace_tensor_overload_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logsumexp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_masked_fill_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_mean_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_meshgrid_list_of_tensors_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_meshgrid_variadic_tensors_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_movedim_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_mul_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_narrow_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_narrow_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_ne_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_neg_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_new_empty_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_new_empty_strided_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_new_full_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_new_ones_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_new_zeros_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_nn_functional_channel_shuffle_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_nn_functional_l1_loss_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_nn_functional_log_softmax_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_nn_functional_pairwise_distance_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_nn_functional_pixel_shuffle_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_nn_functional_pixel_unshuffle_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_nn_functional_softmax_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_nn_functional_softmin_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_nn_functional_tanhshrink_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_nn_functional_triplet_margin_loss_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_normal__in_place_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_ones_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_permute_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_permute_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_positive_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_pow_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_prod_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_randn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_ravel_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_real_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_reciprocal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_renorm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_repeat_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_reshape_as_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_reshape_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_roll_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_rot90_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_rsqrt_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_rsub_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sgn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sigmoid_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sin_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sinc_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sinh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_softmax_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_special_log_softmax_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_special_softmax_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_split_with_sizes_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sqrt_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_square_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_squeeze_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_squeeze_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_squeeze_multiple_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_stack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_std_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_std_mean_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_stft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sub_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sum_to_size_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_t_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_t_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_take_along_dim_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_tan_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_tanh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_tensor_split_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_to_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_trace_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_transpose_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_transpose_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_tril_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_triu_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_true_divide_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_unbind_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_unbind_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_unflatten_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_unfold_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_unfold_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_unsqueeze_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_unsqueeze_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_var_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_var_mean_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_vdot_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_view_as_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_view_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_view_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_vsplit_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_vstack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_where_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_zeros_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__unsafe_masked_index_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_abs_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_acos_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_acosh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_add_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_addbmm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_addcdiv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_addcmul_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_addmm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_addmm_decomposed_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_addmv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_addr_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_alias_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_all_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_allclose_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_angle_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_any_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_argwhere_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_as_strided_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_as_strided_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_as_strided_partial_views_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_as_strided_scatter_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_asin_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_asinh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_atan_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_atanh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_atleast_1d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_atleast_2d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_atleast_3d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_baddbmm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_bfloat16_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_block_diag_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_bmm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_bool_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_broadcast_tensors_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_broadcast_to_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_byte_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cartesian_prod_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cat_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cdouble_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cfloat_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_chalf_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_char_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cholesky_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cholesky_inverse_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cholesky_solve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_chunk_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_clone_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_column_stack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_combinations_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_conj_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_conj_physical_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_constant_pad_nd_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_contiguous_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_corrcoef_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cos_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cosh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_count_nonzero_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cov_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cross_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cumprod_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cumsum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cumulative_trapezoid_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_diag_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_diag_embed_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_diagflat_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_diagonal_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_diagonal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_diagonal_scatter_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_diff_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_dist_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_div_no_rounding_mode_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_dot_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_double_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_dsplit_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_dstack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_einsum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_empty_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_empty_like_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_empty_permuted_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_empty_strided_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_eq_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_equal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_exp2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_exp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_expand_as_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_expand_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_expand_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_expm1_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_eye_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_fft2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_fft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_fftn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_fftshift_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_hfft2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_hfft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_hfftn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_ifft2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_ifft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_ifftn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_ifftshift_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_irfft2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_irfft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_irfftn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fill_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_flatten_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_flip_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fliplr_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_flipud_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_float_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_float_power_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_full_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_full_like_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_gather_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_geqrf_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_gradient_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_half_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_hsplit_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_hstack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_imag_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_index_add_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_index_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_index_fill_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_index_put_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_index_select_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_inner_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_int_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_isclose_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_isfinite_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_isinf_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_isnan_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_isreal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_istft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_item_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_jiterator_2inputs_2outputs_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_jiterator_4inputs_with_extra_args_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_jiterator_binary_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_jiterator_binary_return_by_ref_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_jiterator_unary_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_kron_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_ldexp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_lerp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_cholesky_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_cholesky_ex_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_cond_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_cross_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_det_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_diagonal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_eig_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_eigh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_eigvals_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_eigvalsh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_householder_product_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_inv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_inv_ex_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_ldl_factor_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_ldl_factor_ex_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_ldl_solve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_lstsq_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_lstsq_grad_oriented_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_lu_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_lu_factor_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_lu_factor_ex_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_lu_solve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_matrix_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_matrix_power_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_matrix_rank_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_matrix_rank_hermitian_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_multi_dot_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_norm_subgradients_at_zero_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_pinv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_pinv_hermitian_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_pinv_singular_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_qr_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_slogdet_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_solve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_solve_ex_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_solve_triangular_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_svd_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_svdvals_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_tensorinv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_tensorsolve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_vander_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_vecdot_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_vector_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linspace_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linspace_tensor_overload_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_log10_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_log1p_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_log2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_log_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_log_softmax_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logaddexp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logcumsumexp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logdet_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logical_and_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logical_not_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logical_or_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logical_xor_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logspace_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logspace_tensor_overload_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logsumexp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_long_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_lu_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_lu_solve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_lu_unpack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_mH_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_mT_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_cumprod_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_cumsum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_fill_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_logsumexp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_mean_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_normalize_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_prod_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_scatter_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_select_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_std_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_sum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_var_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_matmul_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_matrix_exp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_mean_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_meshgrid_list_of_tensors_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_meshgrid_variadic_tensors_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_mm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_movedim_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_mul_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_mv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_narrow_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_narrow_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_ne_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_neg_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_new_empty_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_new_empty_strided_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_new_full_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_new_ones_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_new_zeros_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_channel_shuffle_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_conv1d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_conv2d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_conv3d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_conv_transpose1d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_conv_transpose2d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_conv_transpose3d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_feature_alpha_dropout_without_train_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_l1_loss_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_linear_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_normalize_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_pad_circular_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_pad_constant_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_pad_reflect_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_pad_replicate_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_pad_replicate_negative_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_pairwise_distance_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_pixel_shuffle_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_pixel_unshuffle_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_rms_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_silu_complex_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_softmin_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_softsign_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_tanhshrink_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_triplet_margin_loss_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_triplet_margin_with_distance_loss_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_unfold_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nonzero_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nonzero_static_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_norm_fro_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_norm_inf_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_norm_nuc_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_normal_in_place_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_ones_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_ones_like_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_ormqr_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_outer_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_pca_lowrank_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_permute_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_permute_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_pinverse_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_positive_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_pow_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_prod_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_put_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_qr_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_rand_like_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_randn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_randn_like_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_ravel_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_real_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_reciprocal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_renorm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_repeat_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_repeat_interleave_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_reshape_as_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_reshape_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_resize__cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_resize_as__cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_resolve_conj_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_resolve_neg_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_roll_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_rot90_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_rsqrt_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_rsub_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_scalar_tensor_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_scatter_add_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_scatter_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_select_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sgn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_short_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sigmoid_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sin_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sinc_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sinh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_slice_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_softmax_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sparse_sampled_addmm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_split_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_split_list_args_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_split_with_sizes_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_split_with_sizes_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sqrt_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_square_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_squeeze_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_squeeze_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_squeeze_multiple_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_stack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_std_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_std_mean_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_std_mean_unbiased_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_std_unbiased_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_stft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sub_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sum_to_size_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_svd_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_svd_lowrank_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_t_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_t_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_take_along_dim_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_take_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_tan_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_tanh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_tensor_split_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_tensordot_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_tile_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_to_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_to_sparse_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_trace_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_transpose_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_transpose_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_trapezoid_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_trapz_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_triangular_solve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_tril_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_triu_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_true_divide_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unbind_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unbind_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unflatten_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unfold_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unfold_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_uniform_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unsafe_chunk_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unsafe_split_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unsqueeze_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unsqueeze_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_var_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_var_mean_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_var_mean_unbiased_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_var_unbiased_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_vdot_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_view_as_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_view_as_real_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_view_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_view_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_vsplit_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_vstack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_where_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_zero__cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_zeros_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_zeros_like_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_view_H_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_T_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view___getitem___cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view___radd___cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view___rdiv___cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view___rmatmul___cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view___rmod___cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view___rmul___cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view___rpow___cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view___rsub___cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__batch_norm_with_update_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__chunk_cat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__native_batch_norm_legit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_T_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_bfloat16_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_bool_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_byte_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_cdouble_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_cfloat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_chalf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_char_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_complex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_double_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_float_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_half_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_int_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_long_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_polar_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_short_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_abs_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_acos_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_acosh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_add_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_addcdiv_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_addcmul_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_addr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_alias_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_all_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_allclose_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_amax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_amin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_any_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_arange_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_as_strided_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_as_strided_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_as_strided_partial_views_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_as_strided_scatter_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_asin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_asinh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_atan2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_atan_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_atanh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_atleast_1d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_atleast_2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_atleast_3d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_block_diag_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_broadcast_tensors_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_broadcast_to_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_bucketize_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_cat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_cauchy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_ceil_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_chunk_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_clamp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_clamp_max_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_clamp_min_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_clone_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_column_stack_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_conj_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_conj_physical_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_constant_pad_nd_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_contiguous_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_copysign_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_cos_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_cosh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_count_nonzero_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_cumprod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_cumsum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_deg2rad_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_diag_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_diag_embed_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_diagonal_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_diagonal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_diagonal_scatter_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_digamma_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_div_floor_rounding_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_div_no_rounding_mode_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_div_trunc_rounding_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_dot_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_dsplit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_dstack_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_empty_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_empty_like_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_empty_strided_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_eq_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_equal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_erf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_erfc_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_erfinv_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_exp2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_exp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_expand_as_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_expand_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_expand_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_expm1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_exponential_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_eye_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_fft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_fft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_fftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_fftshift_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_hfft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_hfft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_hfftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_ifft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_ifft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_ifftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_ifftshift_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_ihfft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_ihfft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_ihfftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_irfft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_irfft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_irfftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_rfft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_rfft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_rfftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fill_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_flatten_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_flip_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fliplr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_flipud_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_float_power_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_floor_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_floor_divide_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fmax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fmin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fmod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_frac_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_frexp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_ge_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_geometric_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_gt_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_heaviside_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_hsplit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_hstack_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_hypot_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_i0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_igamma_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_igammac_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_index_add_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_index_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_index_fill_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_index_select_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_isclose_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_isfinite_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_isinf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_isnan_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_isneginf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_isposinf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_isreal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_item_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_le_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_lerp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_lgamma_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_cross_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_diagonal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_matrix_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_svd_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_svdvals_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_vecdot_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_vector_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linspace_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linspace_tensor_overload_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_log10_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_log1p_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_log2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_log_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_log_normal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_log_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_logaddexp2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_logaddexp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_logical_and_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_logical_not_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_logical_or_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_logical_xor_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_logspace_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_logspace_tensor_overload_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_logsumexp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_lt_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_masked_fill_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_maximum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_meshgrid_list_of_tensors_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_meshgrid_variadic_tensors_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_minimum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_movedim_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_mul_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nan_to_num_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_narrow_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_narrow_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_native_layer_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_ne_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_neg_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_new_empty_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_new_empty_strided_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_new_full_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_new_ones_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_new_zeros_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nextafter_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_alpha_dropout_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_celu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_channel_shuffle_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_dropout_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_elu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_gelu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_glu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_group_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_hardshrink_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_hardtanh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_hinge_embedding_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_huber_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_l1_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_layer_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_leaky_relu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_log_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_margin_ranking_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_mish_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_mse_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_nll_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_pairwise_distance_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_pdist_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_pixel_shuffle_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_pixel_unshuffle_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_poisson_nll_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_prelu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_relu6_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_relu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_selu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_smooth_l1_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_softmin_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_softplus_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_softshrink_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_tanhshrink_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_threshold_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_triplet_margin_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_normal__in_place_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_normal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_normal_number_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_ones_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_permute_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_permute_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_positive_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_pow_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_prod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_rad2deg_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_randn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_ravel_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_real_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_reciprocal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_remainder_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_renorm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_repeat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_reshape_as_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_reshape_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_roll_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_rot90_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_round_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_rsqrt_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_rsub_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_select_scatter_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sgn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sigmoid_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sign_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_signbit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sinc_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sinh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_bessel_j0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_bessel_j1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_entr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_erfcx_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_i0e_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_i1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_i1e_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_log_ndtr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_log_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_logit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_multigammaln_mvlgamma_p_1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_multigammaln_mvlgamma_p_3_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_multigammaln_mvlgamma_p_5_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_ndtr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_ndtri_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_spherical_bessel_j0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_xlog1py_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_zeta_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_split_with_sizes_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sqrt_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_square_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_squeeze_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_squeeze_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_squeeze_multiple_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_stack_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_std_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_std_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_stft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sub_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sum_to_size_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_t_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_t_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_take_along_dim_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_tan_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_tanh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_tensor_split_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_to_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_trace_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_transpose_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_transpose_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_tril_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_triu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_true_divide_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_trunc_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_unbind_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_unbind_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_unflatten_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_unfold_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_unfold_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_unsqueeze_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_unsqueeze_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_var_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_var_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_vdot_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_view_as_complex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_view_as_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_view_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_view_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_vsplit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_vstack_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_where_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_xlogy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_zeros_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__segment_reduce_lengths_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__segment_reduce_offsets_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__softmax_backward_data_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__unsafe_masked_index_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__unsafe_masked_index_put_accumulate_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__upsample_bilinear2d_aa_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_abs_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_acos_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_acosh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_add_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_addbmm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_addcdiv_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_addcmul_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_addmm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_addmm_decomposed_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_addmv_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_addr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_alias_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_all_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_allclose_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_amax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_amin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_aminmax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_angle_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_any_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_arange_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_argmax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_argmin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_argsort_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_argwhere_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_as_strided_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_as_strided_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_as_strided_partial_views_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_as_strided_scatter_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_asin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_asinh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_atan2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_atan_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_atanh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_atleast_1d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_atleast_2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_atleast_3d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_baddbmm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_bernoulli_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_bfloat16_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_block_diag_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_bmm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_bool_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_broadcast_tensors_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_broadcast_to_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_bucketize_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_byte_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cartesian_prod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cauchy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cdist_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cdouble_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_ceil_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cfloat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_chalf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_char_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cholesky_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cholesky_inverse_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cholesky_solve_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_chunk_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_clamp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_clamp_max_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_clamp_min_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_clone_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_column_stack_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_combinations_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_complex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_conj_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_conj_physical_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_constant_pad_nd_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_contiguous_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_copysign_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_corrcoef_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cos_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cosh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_count_nonzero_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cov_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cross_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cummax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cummin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cumprod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cumsum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cumulative_trapezoid_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_deg2rad_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_diag_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_diag_embed_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_diagflat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_diagonal_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_diagonal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_diagonal_scatter_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_diff_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_digamma_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_dist_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_div_floor_rounding_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_div_no_rounding_mode_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_div_trunc_rounding_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_dot_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_double_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_dsplit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_dstack_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_einsum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_empty_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_empty_like_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_empty_permuted_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_empty_strided_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_eq_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_equal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_erf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_erfc_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_erfinv_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_exp2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_exp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_expand_as_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_expand_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_expand_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_expm1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_exponential_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_eye_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_fft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_fft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_fftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_fftshift_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_hfft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_hfft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_hfftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_ifft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_ifft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_ifftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_ifftshift_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_ihfft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_ihfft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_ihfftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_irfft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_irfft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_irfftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_rfft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_rfft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_rfftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fill_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_flatten_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_flip_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fliplr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_flipud_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_float_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_float_power_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_floor_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_floor_divide_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fmax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fmin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fmod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_frac_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_frexp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_full_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_full_like_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_gather_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_ge_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_geometric_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_geqrf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_gradient_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_grid_sampler_2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_gt_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_half_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_heaviside_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_histc_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_histogram_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_histogramdd_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_hsplit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_hstack_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_hypot_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_i0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_igamma_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_igammac_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_index_add_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_index_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_index_fill_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_index_put_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_index_reduce_amax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_index_reduce_amin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_index_reduce_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_index_reduce_prod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_index_select_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_inner_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_int_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_isclose_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_isfinite_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_isin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_isinf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_isnan_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_isneginf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_isposinf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_isreal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_item_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_jiterator_2inputs_2outputs_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_jiterator_4inputs_with_extra_args_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_jiterator_binary_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_jiterator_binary_return_by_ref_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_jiterator_unary_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_kron_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_kthvalue_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_ldexp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_le_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_lerp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_lgamma_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_cholesky_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_cholesky_ex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_cond_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_cross_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_det_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_diagonal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_eig_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_eigh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_eigvals_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_eigvalsh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_householder_product_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_inv_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_inv_ex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_ldl_factor_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_ldl_factor_ex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_ldl_solve_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_lstsq_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_lstsq_grad_oriented_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_lu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_lu_factor_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_lu_factor_ex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_lu_solve_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_matrix_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_matrix_power_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_matrix_rank_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_matrix_rank_hermitian_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_multi_dot_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_norm_subgradients_at_zero_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_pinv_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_pinv_hermitian_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_pinv_singular_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_qr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_slogdet_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_solve_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_solve_ex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_solve_triangular_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_svd_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_svdvals_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_tensorinv_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_tensorsolve_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_vander_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_vecdot_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_vector_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linspace_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linspace_tensor_overload_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_log10_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_log1p_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_log2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_log_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_log_normal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_log_softmax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_log_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logaddexp2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logaddexp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logcumsumexp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logdet_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logical_and_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logical_not_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logical_or_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logical_xor_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logspace_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logspace_tensor_overload_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_logsumexp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_long_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_lt_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_lu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_lu_solve_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_lu_unpack_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mH_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mT_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_amax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_amin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_argmax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_argmin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_cumprod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_cumsum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_fill_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_log_softmax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_logaddexp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_logsumexp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_median_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_normalize_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_prod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_scatter_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_select_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_softmax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_softmin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_std_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_sum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_var_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_matmul_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_matrix_exp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_max_binary_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_max_pool2d_with_indices_backward_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_max_reduction_no_dim_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_max_reduction_with_dim_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_maximum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_median_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_meshgrid_list_of_tensors_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_meshgrid_variadic_tensors_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_min_binary_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_min_reduction_no_dim_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_min_reduction_with_dim_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_minimum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mode_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_movedim_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_msort_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mul_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_multinomial_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mv_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nan_to_num_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nanmean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nanmedian_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nanquantile_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nansum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_narrow_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_narrow_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_native_batch_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_native_dropout_backward_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_native_layer_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_ne_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_neg_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_new_empty_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_new_empty_strided_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_new_full_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_new_ones_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_new_zeros_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nextafter_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_adaptive_avg_pool1d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_adaptive_avg_pool2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_adaptive_avg_pool3d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_adaptive_max_pool1d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_adaptive_max_pool2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_adaptive_max_pool3d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_alpha_dropout_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_avg_pool1d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_avg_pool2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_avg_pool3d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_batch_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_bilinear_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_binary_cross_entropy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_binary_cross_entropy_with_logits_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_celu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_channel_shuffle_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_conv1d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_conv2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_conv3d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_conv_transpose1d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_conv_transpose2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_conv_transpose3d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_cosine_embedding_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_cosine_similarity_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_cross_entropy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_ctc_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_dropout2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_dropout3d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_dropout_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_elu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_embedding_bag_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_embedding_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_feature_alpha_dropout_with_train_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_feature_alpha_dropout_without_train_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_fractional_max_pool2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_fractional_max_pool3d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_gaussian_nll_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_gelu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_glu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_grid_sample_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_group_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_hardshrink_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_hardsigmoid_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_hardswish_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_hardtanh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_hinge_embedding_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_huber_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_instance_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_interpolate_area_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_interpolate_bicubic_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_interpolate_bilinear_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_interpolate_linear_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_interpolate_nearest-exact_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_interpolate_nearest_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_interpolate_trilinear_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_kl_div_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_l1_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_layer_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_leaky_relu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_linear_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_local_response_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_logsigmoid_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_margin_ranking_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_max_pool1d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_max_pool2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_max_pool3d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_max_unpool1d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_max_unpool1d_grad_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_max_unpool2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_max_unpool2d_grad_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_max_unpool3d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_max_unpool3d_grad_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_mish_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_mse_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_multi_head_attention_forward_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_multi_margin_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_multilabel_margin_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_multilabel_soft_margin_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_nll_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_normalize_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_pad_circular_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_pad_constant_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_pad_reflect_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_pad_replicate_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_pad_replicate_negative_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_pairwise_distance_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_pdist_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_pixel_shuffle_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_pixel_unshuffle_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_poisson_nll_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_prelu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_relu6_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_relu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_rms_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_rrelu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_scaled_dot_product_attention_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_selu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_silu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_smooth_l1_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_soft_margin_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_softmin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_softmin_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_softplus_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_softshrink_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_softsign_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_tanhshrink_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_threshold_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_triplet_margin_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_triplet_margin_with_distance_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_unfold_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_upsample_bilinear_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_upsample_nearest_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nonzero_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nonzero_static_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_norm_fro_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_norm_inf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_norm_nuc_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_normal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_normal_in_place_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_normal_number_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_ones_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_ones_like_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_ormqr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_outer_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_pca_lowrank_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_permute_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_permute_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_pinverse_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_polar_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_polygamma_polygamma_n_0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_polygamma_polygamma_n_1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_polygamma_polygamma_n_2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_polygamma_polygamma_n_3_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_polygamma_polygamma_n_4_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_positive_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_pow_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_prod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_put_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_qr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_quantile_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_rad2deg_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_rand_like_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_randint_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_randint_like_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_randn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_randn_like_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_ravel_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_real_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_reciprocal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_remainder_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_renorm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_repeat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_repeat_interleave_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_reshape_as_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_reshape_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_resize__cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_resize_as__cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_resolve_conj_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_resolve_neg_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_roll_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_rot90_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_round_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_round_decimals_0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_round_decimals_3_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_round_decimals_neg_3_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_rsqrt_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_rsub_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_scalar_tensor_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_scatter_add_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_scatter_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_scatter_reduce_amax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_scatter_reduce_amin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_scatter_reduce_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_scatter_reduce_prod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_scatter_reduce_sum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_searchsorted_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_select_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_select_scatter_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sgn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_short_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sigmoid_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sign_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_bartlett_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_blackman_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_cosine_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_exponential_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_gaussian_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_general_cosine_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_general_hamming_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_hamming_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_hann_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_kaiser_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_nuttall_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signbit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sinc_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sinh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_slice_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_slice_scatter_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_softmax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sort_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sparse_mm_reduce_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sparse_sampled_addmm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_airy_ai_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_bessel_j0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_bessel_j1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_bessel_y0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_bessel_y1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_chebyshev_polynomial_t_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_chebyshev_polynomial_u_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_chebyshev_polynomial_v_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_chebyshev_polynomial_w_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_entr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_erfcx_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_hermite_polynomial_h_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_hermite_polynomial_he_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_i0e_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_i1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_i1e_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_laguerre_polynomial_l_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_legendre_polynomial_p_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_log_ndtr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_modified_bessel_i0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_modified_bessel_i1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_modified_bessel_k0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_modified_bessel_k1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_ndtr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_ndtri_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_polygamma_special_polygamma_n_0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_scaled_modified_bessel_k0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_scaled_modified_bessel_k1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_shifted_chebyshev_polynomial_t_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_shifted_chebyshev_polynomial_u_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_shifted_chebyshev_polynomial_v_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_shifted_chebyshev_polynomial_w_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_spherical_bessel_j0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_xlog1py_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_zeta_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_split_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_split_list_args_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_split_with_sizes_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_split_with_sizes_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sqrt_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_square_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_squeeze_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_squeeze_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_squeeze_multiple_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_stack_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_std_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_std_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_std_mean_unbiased_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_std_unbiased_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_stft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sub_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sum_to_size_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_svd_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_svd_lowrank_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_t_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_t_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_take_along_dim_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_take_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_tan_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_tanh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_tensor_split_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_tensordot_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_tile_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_to_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_to_sparse_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_topk_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_torch_ops_aten__safe_softmax_default_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_trace_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_transpose_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_transpose_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_trapezoid_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_trapz_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_triangular_solve_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_tril_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_triu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_true_divide_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_trunc_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unbind_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unbind_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unflatten_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unfold_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unfold_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_uniform_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unique_consecutive_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unique_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unsafe_chunk_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unsafe_split_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unsqueeze_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unsqueeze_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_var_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_var_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_var_mean_unbiased_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_var_unbiased_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_vdot_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_view_as_complex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_view_as_cpu_float64, 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test/test_ops.py::TestFakeTensorCPU::test_fake_autocast___rmatmul___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast___rmod___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast___rmul___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast___ror___cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast___rpow___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast___rsub___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast___rxor___cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__batch_norm_with_update_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__chunk_cat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__native_batch_norm_legit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__segment_reduce_lengths_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__segment_reduce_offsets_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__softmax_backward_data_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__unsafe_masked_index_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__unsafe_masked_index_put_accumulate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__upsample_bilinear2d_aa_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_abs_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_acos_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_acosh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_addbmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_addcdiv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_addcmul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_addmm_decomposed_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_addmv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_addr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_alias_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_all_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_allclose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_aminmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_angle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_any_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_arange_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_argmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_argmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_argsort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_argwhere_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_as_strided_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_as_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_as_strided_partial_views_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_as_strided_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_asin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_asinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_atan2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_atan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_atanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_atleast_1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_atleast_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_atleast_3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_baddbmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bernoulli_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bfloat16_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bincount_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bitwise_and_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bitwise_left_shift_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bitwise_not_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bitwise_or_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bitwise_right_shift_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bitwise_xor_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_block_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bool_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_broadcast_shapes_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_broadcast_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_broadcast_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bucketize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_byte_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cartesian_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cauchy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cdouble_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_ceil_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cfloat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_chalf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_char_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cholesky_inverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cholesky_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_clamp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_clamp_max_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_clamp_min_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_clone_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_column_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_combinations_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_conj_physical_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_constant_pad_nd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_contiguous_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_copysign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_corrcoef_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cos_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cosh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_count_nonzero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cov_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cummax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cummin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cumulative_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_deg2rad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_diag_embed_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_diagflat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_diagonal_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_diagonal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_diagonal_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_diff_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_digamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_dist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_div_floor_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_div_trunc_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_double_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_dsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_dstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_einsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_empty_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_empty_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_empty_permuted_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_empty_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_eq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_equal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_erf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_erfc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_erfinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_exp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_exp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_expand_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_expand_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_expand_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_expm1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_exponential_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_eye_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_fft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_fft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_fftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_fftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_hfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_hfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_hfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_ifft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_ifft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_ifftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_ifftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_ihfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_ihfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_ihfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_irfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_irfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_irfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_rfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_rfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_rfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_flatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_flip_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fliplr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_flipud_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_float_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_float_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_floor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_floor_divide_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fmod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_frac_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_frexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_full_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_full_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_gather_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_gcd_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_ge_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_geometric_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_geqrf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_gradient_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_grid_sampler_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_gt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_half_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_heaviside_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_histc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_histogram_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_histogramdd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_hsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_hstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_hypot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_i0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_igamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_igammac_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_imag_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_index_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_index_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_index_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_index_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_index_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_index_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_index_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_index_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_index_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_inner_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_int_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isclose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isfinite_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isinf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isnan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isneginf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isposinf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isreal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_istft_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_item_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_jiterator_2inputs_2outputs_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_jiterator_4inputs_with_extra_args_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_jiterator_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_jiterator_binary_return_by_ref_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_jiterator_unary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_kron_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_kthvalue_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_lcm_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_ldexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_le_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_lerp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_lgamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_cholesky_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_cond_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_det_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_diagonal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_eig_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_eigh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_eigvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_householder_product_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_inv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_inv_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_ldl_factor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_ldl_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_ldl_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_lstsq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_lu_factor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_lu_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_matrix_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_matrix_rank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_matrix_rank_hermitian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_multi_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_pinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_pinv_hermitian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_pinv_singular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_slogdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_solve_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_svdvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_tensorinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_tensorsolve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_vander_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_vecdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_vector_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_log10_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_log1p_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_log2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_log_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_log_normal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logaddexp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logcumsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logical_and_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logical_not_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logical_or_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logical_xor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_long_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_lt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_lu_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_lu_unpack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mH_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mT_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_argmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_argmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_median_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_std_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_matmul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_matrix_exp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_max_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_max_pool2d_with_indices_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_max_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_maximum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_median_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_meshgrid_variadic_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_min_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_min_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_minimum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_movedim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_msort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_multinomial_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nan_to_num_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nanmean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nanmedian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nanquantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nansum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_narrow_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_narrow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_native_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_native_dropout_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_native_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_ne_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_new_empty_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_new_empty_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_new_full_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_new_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_new_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nextafter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_alpha_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_binary_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_celu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_conv1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_conv2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_conv3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_conv_transpose1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_conv_transpose2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_conv_transpose3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_cosine_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_cosine_similarity_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_ctc_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_dropout2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_dropout3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_elu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_embedding_bag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_embedding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_fractional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_gaussian_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_gelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_glu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_hardsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_hardswish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_instance_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_interpolate_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_interpolate_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_interpolate_trilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_kl_div_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_unpool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_unpool1d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_unpool2d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_unpool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_unpool3d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_mish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_mse_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_multi_head_attention_forward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_multi_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_multilabel_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_one_hot_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pad_circular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pad_constant_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pad_replicate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pairwise_distance_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pixel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_prelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_relu6_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_rms_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_rrelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_selu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_silu_complex_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_silu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_smooth_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_softmin_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_softplus_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_softsign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_tanhshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_threshold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nonzero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nonzero_static_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_norm_fro_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_norm_inf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_norm_nuc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_normal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_normal_in_place_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_normal_number_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_ones_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_ormqr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_outer_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_pca_lowrank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_permute_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_permute_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_pinverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_polar_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_polygamma_polygamma_n_2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_positive_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_pow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_quantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_rad2deg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_rand_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_randint_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_randint_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_randn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_randn_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_ravel_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_real_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_reciprocal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_remainder_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_renorm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_repeat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_repeat_interleave_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_reshape_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_reshape_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_resize__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_resize_as__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_resolve_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_resolve_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_roll_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_rot90_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_round_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_round_decimals_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_round_decimals_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_round_decimals_neg_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_rsqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_rsub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_scalar_tensor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_scatter_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_scatter_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_searchsorted_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_select_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sgn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_short_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_bartlett_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_blackman_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_cosine_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_exponential_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_gaussian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_general_cosine_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_general_hamming_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_hamming_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_hann_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_kaiser_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_nuttall_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signbit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sinc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_slice_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_slice_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sparse_mm_reduce_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_airy_ai_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_bessel_j0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_bessel_j1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_bessel_y0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_bessel_y1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_entr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_erfcx_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_hermite_polynomial_h_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_i0e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_i1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_i1e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_laguerre_polynomial_l_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_legendre_polynomial_p_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_log_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_modified_bessel_i0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_modified_bessel_i1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_modified_bessel_k0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_modified_bessel_k1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_ndtri_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_scaled_modified_bessel_k0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_scaled_modified_bessel_k1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_spherical_bessel_j0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_xlog1py_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_zeta_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_split_list_args_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_split_with_sizes_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_split_with_sizes_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_square_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_squeeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_squeeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_squeeze_multiple_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_std_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_std_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_std_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_std_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_stft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sum_to_size_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_svd_lowrank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_t_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_take_along_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_take_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_tan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_tanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_tensor_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_tensordot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_tile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_to_sparse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_topk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_torch__scaled_mm_cpu_float8_e4m3fn, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_trace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_transpose_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_transpose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_trapz_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_triangular_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_tril_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_tril_indices_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_triu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_triu_indices_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_true_divide_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_trunc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unbind_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unbind_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unflatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unfold_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_uniform_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unique_consecutive_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unique_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unravel_index_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unsafe_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unsafe_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unsqueeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unsqueeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_var_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_var_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_var_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_vdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_view_as_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_view_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_view_as_real_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_view_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_view_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_vsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_vstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_where_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_xlogy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_zero__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_zeros_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_baddbmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_bernoulli_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_bfloat16_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_bincount_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_bitwise_and_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_bitwise_left_shift_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_bitwise_not_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_bitwise_or_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_bitwise_right_shift_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_bitwise_xor_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_block_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_bmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_bool_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_broadcast_shapes_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_broadcast_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_broadcast_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_bucketize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_byte_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cartesian_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cauchy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cdouble_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_ceil_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cfloat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_chalf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_char_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cholesky_inverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cholesky_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_clamp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_clamp_max_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_clamp_min_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_clone_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_column_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_combinations_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_conj_physical_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_constant_pad_nd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_contiguous_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_copysign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_corrcoef_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cos_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cosh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_count_nonzero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cov_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_H_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_T_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp___getitem___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp___radd___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp___rdiv___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp___rmatmul___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp___rmod___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp___rmul___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp___rpow___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp___rsub___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp__batch_norm_with_update_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp__native_batch_norm_legit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp__segment_reduce_lengths_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp__segment_reduce_offsets_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp__softmax_backward_data_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp__unsafe_masked_index_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp__unsafe_masked_index_put_accumulate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp__upsample_bilinear2d_aa_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_abs_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_acos_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_acosh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_addbmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_addcdiv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_addcmul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_addmm_decomposed_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_addmv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_addr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_alias_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_angle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_as_strided_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_as_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_as_strided_partial_views_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_as_strided_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_asin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_asinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_atan2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_atan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_atanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_atleast_1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_atleast_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_atleast_3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_baddbmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_bernoulli_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_bfloat16_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_block_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_bmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_broadcast_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_broadcast_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cartesian_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cdouble_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_ceil_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cfloat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_chalf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cholesky_inverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cholesky_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_clamp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_clamp_max_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_clamp_min_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_clone_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_column_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_combinations_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_conj_physical_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_constant_pad_nd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_contiguous_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_copysign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_corrcoef_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cos_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cosh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cov_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cummax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cummin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cumulative_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_deg2rad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_diag_embed_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_diagflat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_diagonal_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_diagonal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_diagonal_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_diff_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_digamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_dist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_div_floor_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_div_trunc_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_double_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_dsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_dstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_einsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_erf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_erfc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_erfinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_exp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_exp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_expand_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_expand_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_expand_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_expm1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_fft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_fft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_fftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_fftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_hfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_hfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_hfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_ifft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_ifft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_ifftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_ifftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_ihfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_ihfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_ihfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_irfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_irfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_irfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_rfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_rfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_rfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_flatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_flip_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fliplr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_flipud_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_float_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_float_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_floor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fmod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_frac_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_frexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_gather_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_gradient_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_grid_sampler_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_half_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_hsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_hstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_hypot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_i0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_inner_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_kron_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_kthvalue_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_ldexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_lerp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_lgamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_cholesky_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_cond_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_det_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_diagonal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_eig_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_eigh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_eigvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_householder_product_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_inv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_inv_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_lstsq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_lu_factor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_lu_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_matrix_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_multi_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_pinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_pinv_hermitian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_pinv_singular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_slogdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_solve_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_svdvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_tensorinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_tensorsolve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_vander_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_vecdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_vector_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_log10_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_log1p_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_log2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_log_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_logaddexp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_logcumsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_logdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_logit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_lu_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_lu_unpack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mH_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mT_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_median_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_std_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_matmul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_matrix_exp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_max_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_max_pool2d_with_indices_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_max_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_maximum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_median_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_meshgrid_variadic_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_min_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_min_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_minimum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_movedim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_msort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nan_to_num_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nanmean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nanmedian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nanquantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nansum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_narrow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_native_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_native_dropout_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_native_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_alpha_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_binary_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_celu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_conv1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_conv2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_conv3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_conv_transpose1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_conv_transpose2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_conv_transpose3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_cosine_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_cosine_similarity_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_ctc_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_dropout2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_dropout3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_elu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_embedding_bag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_embedding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_fractional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_gaussian_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_gelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_glu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_hardsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_hardswish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_instance_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_interpolate_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_interpolate_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_interpolate_trilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_kl_div_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_max_unpool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_max_unpool1d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_max_unpool2d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_max_unpool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_max_unpool3d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_mish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_mse_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_multi_head_attention_forward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_multi_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_multilabel_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pad_circular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pad_constant_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pad_replicate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pairwise_distance_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pixel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_prelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_relu6_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_rms_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_rrelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_selu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_silu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_smooth_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_softmin_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_softplus_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_softsign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_tanhshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_threshold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_norm_fro_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_norm_inf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_norm_nuc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_normal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_normal_number_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_ormqr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_outer_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_pca_lowrank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_permute_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_permute_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_pinverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_polar_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_polygamma_polygamma_n_2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_positive_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_pow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_quantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_rad2deg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_ravel_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_real_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_reciprocal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_remainder_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_renorm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_repeat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_repeat_interleave_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_reshape_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_reshape_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_resolve_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_resolve_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_roll_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_rot90_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_round_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_round_decimals_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_round_decimals_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_round_decimals_neg_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_rsqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_rsub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_select_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sgn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sinc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_slice_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_slice_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sparse_mm_reduce_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_entr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_erfcx_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_i0e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_i1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_i1e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_log_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_ndtri_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_xlog1py_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_split_list_args_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_split_with_sizes_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_split_with_sizes_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_square_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_squeeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_squeeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_squeeze_multiple_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_std_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_std_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_std_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_std_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_stft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sum_to_size_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_svd_lowrank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_t_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_take_along_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_take_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_tan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_tanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_tensor_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_tensordot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_tile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_to_sparse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_topk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_trace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_transpose_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_transpose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_trapz_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_triangular_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_tril_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_triu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_true_divide_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_trunc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unbind_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unbind_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unflatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unfold_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unsafe_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unsafe_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unsqueeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unsqueeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_var_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_var_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_var_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_vdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_view_as_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_view_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_view_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_view_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_vsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_vstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_where_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_xlogy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_zero__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_H_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_T_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp___getitem___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp___radd___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp___rdiv___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp___rmatmul___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp___rmod___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp___rmul___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp___rpow___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp___rsub___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp__batch_norm_with_update_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp__native_batch_norm_legit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp__segment_reduce_lengths_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp__segment_reduce_offsets_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp__softmax_backward_data_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp__unsafe_masked_index_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp__unsafe_masked_index_put_accumulate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp__upsample_bilinear2d_aa_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_abs_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_acos_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_acosh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_addbmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_addcdiv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_addcmul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_addmm_decomposed_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_addmv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_addr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_alias_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_angle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_as_strided_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_as_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_as_strided_partial_views_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_as_strided_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_asin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_asinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_atan2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_atan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_atanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_atleast_1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_atleast_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_atleast_3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_baddbmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_bernoulli_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_bfloat16_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_block_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_bmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_broadcast_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_broadcast_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cartesian_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cdouble_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_ceil_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cfloat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_chalf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cholesky_inverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cholesky_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_clamp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_clamp_max_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_clamp_min_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_clone_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_column_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_combinations_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_conj_physical_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_constant_pad_nd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_contiguous_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_copysign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_corrcoef_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cos_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cosh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cov_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cummax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cummin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cumulative_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_deg2rad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_diag_embed_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_diagflat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_diagonal_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_diagonal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_diagonal_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_diff_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_digamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_dist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_div_floor_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_div_trunc_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_double_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_dsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_dstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_einsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_erf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_erfc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_erfinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_exp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_exp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_expand_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_expand_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_expand_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_expm1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_fft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_fft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_fftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_fftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_hfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_hfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_hfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ifft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ifft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ifftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ifftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ihfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ihfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ihfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_irfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_irfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_irfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_rfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_rfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_rfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_flatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_flip_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fliplr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_flipud_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_float_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_float_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_floor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fmod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_frac_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_frexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_gather_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_gradient_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_grid_sampler_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_half_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_hsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_hstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_hypot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_i0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_inner_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_kron_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_kthvalue_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_ldexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_lerp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_lgamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_cholesky_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_cond_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_det_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_diagonal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_eig_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_eigh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_eigvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_householder_product_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_inv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_inv_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_lstsq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_lu_factor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_lu_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_matrix_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_multi_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_pinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_pinv_hermitian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_pinv_singular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_slogdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_solve_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_svdvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_tensorinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_tensorsolve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_vander_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_vecdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_vector_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_log10_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_log1p_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_log2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_log_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_logaddexp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_logcumsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_logdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_logit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_lu_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_lu_unpack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mH_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mT_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_median_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_std_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_matmul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_matrix_exp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_max_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_max_pool2d_with_indices_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_max_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_maximum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_median_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_meshgrid_variadic_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_min_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_min_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_minimum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_movedim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_msort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nan_to_num_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nanmean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nanmedian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nanquantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nansum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_narrow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_native_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_native_dropout_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_native_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_alpha_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_binary_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_celu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_conv1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_conv2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_conv3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_conv_transpose1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_conv_transpose2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_conv_transpose3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_cosine_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_cosine_similarity_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_ctc_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_dropout2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_dropout3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_elu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_embedding_bag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_embedding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_fractional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_gaussian_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_gelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_glu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_hardsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_hardswish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_instance_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_interpolate_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_interpolate_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_interpolate_trilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_kl_div_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_unpool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_unpool1d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_unpool2d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_unpool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_unpool3d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_mish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_mse_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_multi_head_attention_forward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_multi_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_multilabel_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pad_circular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pad_constant_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pad_replicate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pairwise_distance_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pixel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_prelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_relu6_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_rms_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_rrelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_selu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_silu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_smooth_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_softmin_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_softplus_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_softsign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_tanhshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_threshold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_norm_fro_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_norm_inf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_norm_nuc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_normal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_normal_number_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_ormqr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_outer_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_pca_lowrank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_permute_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_permute_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_pinverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_polar_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_polygamma_polygamma_n_2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_positive_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_pow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_quantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_rad2deg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_ravel_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_real_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_reciprocal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_remainder_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_renorm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_repeat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_repeat_interleave_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_reshape_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_reshape_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_resolve_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_resolve_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_roll_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_rot90_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_round_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_round_decimals_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_round_decimals_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_round_decimals_neg_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_rsqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_rsub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_scatter_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_scatter_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_select_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sgn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sinc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_slice_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_slice_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sparse_mm_reduce_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_entr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_erfcx_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_i0e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_i1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_i1e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_log_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_ndtri_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_xlog1py_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_split_list_args_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_split_with_sizes_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_split_with_sizes_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_square_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_squeeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_squeeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_squeeze_multiple_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_std_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_std_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_std_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_std_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_stft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sum_to_size_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_svd_lowrank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_t_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_take_along_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_take_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_tan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_tanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_tensor_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_tensordot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_tile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_to_sparse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_topk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_trace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_transpose_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_transpose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_trapz_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_triangular_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_tril_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_triu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_true_divide_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_trunc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unbind_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unbind_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unflatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unfold_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unsafe_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unsafe_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unsqueeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unsqueeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_var_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_var_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_var_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_vdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_view_as_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_view_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_view_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_view_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_vsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_vstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_where_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_xlogy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_zero__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cummax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cummin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cumulative_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_deg2rad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_diag_embed_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_diagflat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_diagonal_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_diagonal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_diagonal_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_diff_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_digamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_dist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_div_floor_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_div_trunc_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_double_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_dsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_dstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_einsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_empty_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_empty_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_empty_permuted_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_empty_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_eq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_equal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_erf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_erfc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_erfinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_exp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_exp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_expand_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_expand_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_expand_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_expm1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_exponential_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_eye_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_fft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_fft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_fftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_fftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_hfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_hfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_hfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ifft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ifft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ifftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ifftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ihfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ihfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ihfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_irfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_irfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_irfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_rfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_rfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_rfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_flatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_flip_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fliplr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_flipud_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_float_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_float_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_floor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_floor_divide_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fmod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_frac_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_frexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_full_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_full_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_gather_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_gcd_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_ge_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_geometric_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_geqrf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_gradient_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_grid_sampler_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_gt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_half_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_heaviside_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_histc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_histogram_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_histogramdd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_hsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_hstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_hypot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_i0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_igamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_igammac_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_imag_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_fake_index_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_inner_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_int_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_isclose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_isfinite_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_isin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_isinf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_isnan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_isneginf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_isposinf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_isreal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_istft_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_fake_item_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_jiterator_2inputs_2outputs_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_jiterator_4inputs_with_extra_args_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_jiterator_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_jiterator_binary_return_by_ref_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_jiterator_unary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_kron_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_kthvalue_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_lcm_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_ldexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_le_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_lerp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_lgamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_cholesky_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_cond_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_det_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_diagonal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_eig_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_eigh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_eigvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_householder_product_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_inv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_inv_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_ldl_factor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_ldl_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_ldl_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_lstsq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_lu_factor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_lu_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_matrix_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_matrix_rank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_matrix_rank_hermitian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_multi_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_pinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_pinv_hermitian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_pinv_singular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_slogdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_solve_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_svdvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_tensorinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_tensorsolve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_vander_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_vecdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_vector_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_log10_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_log1p_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_log2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_log_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_log_normal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logaddexp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logcumsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logical_and_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logical_not_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logical_or_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logical_xor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_long_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_lt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_lu_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_lu_unpack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mH_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mT_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_argmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_argmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_median_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_std_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_matmul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_matrix_exp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_max_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_max_pool2d_with_indices_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_max_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_maximum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_median_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_meshgrid_variadic_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_min_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_min_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_minimum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_movedim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_msort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_multinomial_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nan_to_num_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nanmean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nanmedian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nanquantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nansum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_narrow_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_narrow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_native_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_native_dropout_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_native_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_ne_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_new_empty_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_new_empty_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_new_full_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_new_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_new_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nextafter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_alpha_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_binary_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_celu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_conv1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_conv2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_conv3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_conv_transpose1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_conv_transpose2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_conv_transpose3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_cosine_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_cosine_similarity_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_ctc_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_dropout2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_dropout3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_elu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_embedding_bag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_embedding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_fractional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_gaussian_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_gelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_glu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_hardsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_hardswish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_instance_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_interpolate_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_interpolate_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_interpolate_trilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_kl_div_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_max_unpool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_max_unpool1d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_max_unpool2d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_max_unpool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_max_unpool3d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_mish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_mse_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_multi_head_attention_forward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_multi_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_multilabel_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_one_hot_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pad_circular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pad_constant_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pad_replicate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pairwise_distance_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pixel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_prelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_relu6_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_rms_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_rrelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_selu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_silu_complex_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_silu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_smooth_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_softmin_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_softplus_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_softsign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_tanhshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_threshold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nonzero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nonzero_static_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_norm_fro_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_norm_inf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_norm_nuc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_normal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_normal_in_place_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_normal_number_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_ones_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_ormqr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_outer_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_pca_lowrank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_permute_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_permute_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_pinverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_polar_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_polygamma_polygamma_n_2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_positive_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_pow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_quantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_rad2deg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_rand_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_randint_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_randint_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_randn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_randn_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_ravel_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_real_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_reciprocal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_remainder_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_renorm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_repeat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_repeat_interleave_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_reshape_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_reshape_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_resize__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_resize_as__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_resolve_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_resolve_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_roll_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_rot90_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_round_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_round_decimals_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_round_decimals_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_round_decimals_neg_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_rsqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_rsub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_scalar_tensor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_scatter_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_scatter_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_searchsorted_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_select_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sgn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_short_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_bartlett_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_blackman_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_cosine_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_exponential_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_gaussian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_general_cosine_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_general_hamming_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_hamming_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_hann_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_kaiser_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_nuttall_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signbit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sinc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_slice_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_slice_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sparse_mm_reduce_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_airy_ai_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_bessel_j0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_bessel_j1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_bessel_y0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_bessel_y1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_entr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_erfcx_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_hermite_polynomial_h_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_i0e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_i1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_i1e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_laguerre_polynomial_l_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_legendre_polynomial_p_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_log_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_modified_bessel_i0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_modified_bessel_i1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_modified_bessel_k0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_modified_bessel_k1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_ndtri_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_scaled_modified_bessel_k0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_scaled_modified_bessel_k1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_spherical_bessel_j0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_xlog1py_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_zeta_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_split_list_args_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_split_with_sizes_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_split_with_sizes_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_square_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_squeeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_squeeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_squeeze_multiple_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_std_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_std_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_std_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_std_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_stft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sum_to_size_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_svd_lowrank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_t_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_take_along_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_take_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_tan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_tanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_tensor_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_tensordot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_tile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_to_sparse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_topk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_torch__scaled_mm_cpu_float8_e4m3fn, test/test_ops.py::TestFakeTensorCPU::test_fake_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_trace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_transpose_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_transpose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_trapz_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_triangular_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_tril_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_tril_indices_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_triu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_triu_indices_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_true_divide_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_trunc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unbind_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unbind_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unflatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unfold_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_uniform_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unique_consecutive_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unique_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unravel_index_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_unsafe_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unsafe_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unsqueeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unsqueeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_var_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_var_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_var_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_vdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_view_as_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_view_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_view_as_real_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_fake_view_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_view_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_vsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_vstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_where_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_xlogy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_zero__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_zeros_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_H_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_T_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___getitem___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___radd___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rand___cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rdiv___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rmatmul___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rmod___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rmul___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___ror___cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rpow___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rsub___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rxor___cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__batch_norm_with_update_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__chunk_cat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__native_batch_norm_legit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__segment_reduce_lengths_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__segment_reduce_offsets_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__softmax_backward_data_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__unsafe_masked_index_cpu_float32, 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test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_addr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_alias_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_all_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_allclose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_aminmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_angle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_any_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_arange_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_argmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_argmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_argsort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_argwhere_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_as_strided_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_as_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_as_strided_partial_views_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_as_strided_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_asin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_asinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_atan2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_atan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_atanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_atleast_1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_atleast_2d_cpu_float32, 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test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_bmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_bool_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_broadcast_shapes_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_broadcast_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_broadcast_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_bucketize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_byte_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cartesian_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cauchy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cdouble_cpu_float32, 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test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_column_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_combinations_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_conj_physical_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_constant_pad_nd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_contiguous_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_copysign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_corrcoef_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cos_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cosh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_count_nonzero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cov_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cummax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cummin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cumulative_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_deg2rad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_diag_embed_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_diagflat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_diagonal_copy_cpu_float32, 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test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_einsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_empty_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_empty_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_empty_permuted_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_empty_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_eq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_equal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_erf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_erfc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_erfinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_exp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_exp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_expand_as_cpu_float32, 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test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_ifft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_ifft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_ifftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_ifftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_ihfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_ihfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_ihfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_irfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_irfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_irfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_rfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_rfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_rfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_flatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_flip_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fliplr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_flipud_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_float_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_float_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_floor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_floor_divide_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fmod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_frac_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_frexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_full_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_full_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_gather_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_gcd_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_ge_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_geometric_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_geqrf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_gradient_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_grid_sampler_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_gt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_half_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_heaviside_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_histc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_histogram_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_histogramdd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_hsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_hstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_hypot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_i0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_igamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_igammac_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_imag_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_inner_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_int_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isclose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isfinite_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isinf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isnan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isneginf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isposinf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isreal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_istft_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_item_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_jiterator_2inputs_2outputs_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_jiterator_4inputs_with_extra_args_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_jiterator_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_jiterator_binary_return_by_ref_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_jiterator_unary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_kron_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_kthvalue_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_lcm_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_ldexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_le_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_lerp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_lgamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_cholesky_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_cond_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_det_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_diagonal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_eig_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_eigh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_eigvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_householder_product_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_inv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_inv_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_ldl_factor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_ldl_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_ldl_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_lstsq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_lu_factor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_lu_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_matrix_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_matrix_rank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_matrix_rank_hermitian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_multi_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_pinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_pinv_hermitian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_pinv_singular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_slogdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_solve_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_svdvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_tensorinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_tensorsolve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_vander_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_vecdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_vector_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_log10_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_log1p_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_log2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_log_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_log_normal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logaddexp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logcumsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logical_and_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logical_not_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logical_or_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logical_xor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_long_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_lt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_lu_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_lu_unpack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mH_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mT_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_argmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_argmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_median_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_std_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_matmul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_matrix_exp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_max_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_max_pool2d_with_indices_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_max_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_maximum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_median_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_meshgrid_variadic_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_min_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_min_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_minimum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_movedim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_msort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_multinomial_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nan_to_num_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nanmean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nanmedian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nanquantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nansum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_narrow_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_narrow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_native_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_native_dropout_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_native_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_ne_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_new_empty_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_new_empty_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_new_full_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_new_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_new_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nextafter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_alpha_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_binary_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_celu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_conv1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_conv2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_conv3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_conv_transpose1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_conv_transpose2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_conv_transpose3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_cosine_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_cosine_similarity_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_ctc_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_dropout2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_dropout3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_elu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_embedding_bag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_embedding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_fractional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_gaussian_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_gelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_glu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_hardsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_hardswish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_instance_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_interpolate_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_interpolate_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_interpolate_trilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_kl_div_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_max_unpool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_max_unpool1d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_max_unpool2d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_max_unpool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_max_unpool3d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_mish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_mse_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_multi_head_attention_forward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_multi_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_multilabel_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_one_hot_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pad_circular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pad_constant_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pad_replicate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pairwise_distance_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pixel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_prelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_relu6_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_rms_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_rrelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_selu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_silu_complex_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_silu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_smooth_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_softmin_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_softplus_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_softsign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_tanhshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_threshold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nonzero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nonzero_static_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_norm_fro_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_norm_inf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_norm_nuc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_normal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_normal_in_place_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_normal_number_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_ones_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_ormqr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_outer_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_pca_lowrank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_permute_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_permute_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_pinverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_polar_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_polygamma_polygamma_n_2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_positive_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_pow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_quantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_rad2deg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_rand_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_randint_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_randint_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_randn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_randn_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_ravel_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_real_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_reciprocal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_remainder_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_renorm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_repeat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_repeat_interleave_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_reshape_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_reshape_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_resize__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_resize_as__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_resolve_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_resolve_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_roll_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_rot90_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_round_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_round_decimals_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_round_decimals_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_round_decimals_neg_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_rsqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_rsub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_scalar_tensor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_scatter_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_scatter_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_searchsorted_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_select_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sgn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_short_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_bartlett_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_blackman_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_cosine_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_exponential_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_gaussian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_general_cosine_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_general_hamming_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_hamming_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_hann_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_kaiser_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_nuttall_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signbit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sinc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_slice_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_slice_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sparse_mm_reduce_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_airy_ai_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_bessel_j0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_bessel_j1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_bessel_y0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_bessel_y1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_entr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_erfcx_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_hermite_polynomial_h_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_i0e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_i1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_i1e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_laguerre_polynomial_l_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_legendre_polynomial_p_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_log_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_modified_bessel_i0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_modified_bessel_i1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_modified_bessel_k0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_modified_bessel_k1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_ndtri_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_scaled_modified_bessel_k0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_scaled_modified_bessel_k1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_spherical_bessel_j0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_xlog1py_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_zeta_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_split_list_args_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_split_with_sizes_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_split_with_sizes_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_square_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_squeeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_squeeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_squeeze_multiple_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_std_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_std_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_std_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_std_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_stft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sum_to_size_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_svd_lowrank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_t_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_take_along_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_take_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tensor_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tensordot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_to_sparse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_topk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_torch__scaled_mm_cpu_float8_e4m3fn, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_trace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_transpose_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_transpose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_trapz_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_triangular_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tril_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tril_indices_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_triu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_triu_indices_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_true_divide_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_trunc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unbind_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unbind_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unflatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unfold_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_uniform_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unique_consecutive_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unique_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unravel_index_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unsafe_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unsafe_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unsqueeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unsqueeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_var_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_var_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_var_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_vdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_view_as_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_view_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_view_as_real_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_view_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_view_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_vsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_vstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_where_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_xlogy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_zero__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_zeros_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_bool, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_complex32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_bool, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_complex32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_bool, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_complex32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_bool, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_complex32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_bool, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_complex32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_uint8, test/test_ops.py::TestTagsCPU::test_tags_H_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_T_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___getitem___cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___radd___cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___rand___cpu_int64, test/test_ops.py::TestTagsCPU::test_tags___rdiv___cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___rmatmul___cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___rmod___cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___rmul___cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___ror___cpu_int64, test/test_ops.py::TestTagsCPU::test_tags___rpow___cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___rsub___cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___rxor___cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__batch_norm_with_update_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__chunk_cat_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__native_batch_norm_legit_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_T_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_bfloat16_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_bool_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_byte_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_cdouble_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_cfloat_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_chalf_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_char_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_complex_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_double_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_float_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_half_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_int_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_long_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_polar_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_short_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_abs_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_acos_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_acosh_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_add_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_addcdiv_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_addcmul_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_addr_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_alias_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_all_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_allclose_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_amax_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_amin_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_any_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_arange_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_as_strided_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_as_strided_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_as_strided_partial_views_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_as_strided_scatter_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_asin_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_asinh_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_atan2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_atan_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_atanh_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_atleast_1d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_atleast_2d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_atleast_3d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_bitwise_and_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__refs_bitwise_left_shift_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__refs_bitwise_not_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__refs_bitwise_or_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__refs_bitwise_right_shift_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__refs_bitwise_xor_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__refs_block_diag_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_broadcast_shapes_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_broadcast_tensors_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_broadcast_to_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_bucketize_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_cat_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_cauchy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_ceil_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_chunk_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_clamp_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_clamp_max_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_clamp_min_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_clone_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_column_stack_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_conj_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_conj_physical_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_constant_pad_nd_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_contiguous_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_copysign_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_cos_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_cosh_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_count_nonzero_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_cumprod_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_cumsum_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_deg2rad_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_diag_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_diag_embed_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_diagonal_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_diagonal_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_diagonal_scatter_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_digamma_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_div_floor_rounding_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_div_trunc_rounding_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_dot_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_dsplit_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_dstack_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_empty_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_empty_like_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_empty_strided_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_eq_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_equal_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_erf_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_erfc_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_erfinv_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_exp2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_exp_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_expand_as_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_expand_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_expand_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_expm1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_exponential_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_eye_cpu_float32, 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test/test_ops.py::TestTagsCPU::test_tags_sinc_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sinh_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_slice_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_slice_scatter_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_softmax_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_softmax_with_dtype_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sort_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sparse_mm_reduce_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_airy_ai_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_bessel_j0_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_bessel_j1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_bessel_y0_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_bessel_y1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_entr_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_erfcx_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_hermite_polynomial_h_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_i0e_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_i1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_i1e_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_laguerre_polynomial_l_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_legendre_polynomial_p_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_log_ndtr_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_modified_bessel_i0_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_modified_bessel_i1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_modified_bessel_k0_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_modified_bessel_k1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_ndtr_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_ndtri_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_scaled_modified_bessel_k0_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_scaled_modified_bessel_k1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_spherical_bessel_j0_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_xlog1py_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_zeta_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_split_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_split_list_args_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_split_with_sizes_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_split_with_sizes_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sqrt_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_square_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_squeeze_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_squeeze_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_squeeze_multiple_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_stack_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_std_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_std_mean_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_std_mean_unbiased_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_std_unbiased_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_stft_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sub_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sum_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sum_to_size_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_svd_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_svd_lowrank_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_t_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_t_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_take_along_dim_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_take_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_tan_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_tanh_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_tensor_split_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_tensordot_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_tile_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_to_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_to_sparse_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_topk_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_torch__scaled_mm_cpu_float8_e4m3fn, test/test_ops.py::TestTagsCPU::test_tags_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_trace_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_transpose_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_transpose_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_trapezoid_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_trapz_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_triangular_solve_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_tril_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_tril_indices_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags_triu_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_triu_indices_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags_true_divide_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_trunc_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unbind_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unbind_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unflatten_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unfold_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unfold_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_uniform_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unique_consecutive_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unique_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unravel_index_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags_unsafe_chunk_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unsafe_split_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unsqueeze_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unsqueeze_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_var_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_var_mean_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_var_mean_unbiased_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_var_unbiased_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_vdot_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_view_as_complex_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_view_as_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_view_as_real_cpu_complex64, test/test_ops.py::TestTagsCPU::test_tags_view_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_view_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_vsplit_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_vstack_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_where_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_xlogy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_zero__cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_zeros_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_zeros_like_cpu_float32 2025-07-17T08:46:27.2769149Z 2025-07-17T08:46:28.3859796Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:46:28.3862486Z import pkg_resources 2025-07-17T08:46:28.5110596Z Running dynamo/test_pre_dispatch 1/1 ... [2025-07-17 08:46:28.510653] 2025-07-17T08:46:28.5111415Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:46:28.5113978Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_pre_dispatch.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:46:28.511076] 2025-07-17T08:46:31.7207494Z 2025-07-17T08:46:31.7208961Z dynamo/test_pre_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_pre_dispatch_1.1_ad3c2af709c9ca70_.log 2025-07-17T08:46:31.7209759Z 2025-07-17T08:46:35.1419696Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:46:35.1422427Z import pkg_resources 2025-07-17T08:46:35.2696462Z Running cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 ... [2025-07-17 08:46:35.269168] 2025-07-17T08:46:35.2697263Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:46:35.2699015Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'cpp_extensions/python_agnostic_extension/test/test_python_agnostic.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:46:35.269578] 2025-07-17T08:46:39.1110947Z 2025-07-17T08:46:39.1113108Z cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp_extensions.python_agnostic_extension.test.test_python_agnostic_1.1_6df5ec68f32a8dd2_.log 2025-07-17T08:46:39.1115327Z Running 0 items in this shard: 2025-07-17T08:46:39.1115657Z 2025-07-17T08:46:43.0684722Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:46:43.0687689Z import pkg_resources 2025-07-17T08:46:43.1961783Z Running dynamo/test_dynamic_shapes 1/1 ... [2025-07-17 08:46:43.195668] 2025-07-17T08:46:43.1962590Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:46:43.1964716Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_dynamic_shapes.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:46:43.196110] 2025-07-17T08:46:52.6125422Z 2025-07-17T08:46:52.6126644Z dynamo/test_dynamic_shapes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_dynamic_shapes_1.1_335bae441fa97281_.log 2025-07-17T08:46:52.6127652Z 2025-07-17T08:46:55.8797230Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:46:55.8801526Z import pkg_resources 2025-07-17T08:46:56.0066931Z Running dynamo/test_functions 1/1 ... [2025-07-17 08:46:56.006224] 2025-07-17T08:46:56.0068393Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:46:56.0071192Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_functions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:46:56.006691] 2025-07-17T08:47:03.0802130Z 2025-07-17T08:47:03.0803612Z dynamo/test_functions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_functions_1.1_32291fba72e653e3_.log 2025-07-17T08:47:03.0804652Z 2025-07-17T08:47:06.3085904Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:47:06.3088790Z import pkg_resources 2025-07-17T08:47:06.4358001Z Running dynamo/test_after_aot 1/1 ... [2025-07-17 08:47:06.435376] 2025-07-17T08:47:06.4358741Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:47:06.4361939Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_after_aot.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:47:06.435833] 2025-07-17T08:47:10.8094143Z 2025-07-17T08:47:10.8095898Z dynamo/test_after_aot 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_after_aot_1.1_5a3965fb5fe59b2e_.log 2025-07-17T08:47:10.8097844Z 2025-07-17T08:47:14.2171194Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:47:14.2172790Z import pkg_resources 2025-07-17T08:47:14.3431174Z Running test_optim 2/3 ... [2025-07-17 08:47:14.342614] 2025-07-17T08:47:14.3431939Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:47:14.3437514Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_optim.py', '-m', 'not serial', '--shard-id=2', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:47:14.343044] 2025-07-17T08:47:47.6146196Z 2025-07-17T08:47:47.6175263Z test_custom_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_custom_ops_1.1_3aae1a6ee4f1b8e9_.log 2025-07-17T08:47:47.6366945Z Running 276 items in this shard: test/test_custom_ops.py::TestCustomOp::test_abstract_impl_on_existing_op, test/test_custom_ops.py::TestCustomOp::test_abstract_impl_on_existing_op_with_CompositeExplicitAutograd, test/test_custom_ops.py::TestCustomOp::test_abstract_impl_on_existing_op_with_CompositeImplicitAutograd, test/test_custom_ops.py::TestCustomOp::test_abstract_impl_on_existing_op_with_meta, test/test_custom_ops.py::TestCustomOp::test_autogen_aten_ops_are_pt2_compliant, test/test_custom_ops.py::TestCustomOp::test_autograd_function_backed_op, test/test_custom_ops.py::TestCustomOp::test_autograd_notimplemented, test/test_custom_ops.py::TestCustomOp::test_autograd_notimplemented_gradmode, test/test_custom_ops.py::TestCustomOp::test_backward_dict_grad_for_nontensor, test/test_custom_ops.py::TestCustomOp::test_backward_dict_invalid_keys, test/test_custom_ops.py::TestCustomOp::test_backward_dict_requires_keys_for_input_optional_tensors, test/test_custom_ops.py::TestCustomOp::test_backward_dict_requires_keys_for_input_tensors, test/test_custom_ops.py::TestCustomOp::test_backward_grads_are_tensor_or_none, test/test_custom_ops.py::TestCustomOp::test_backward_impl_on_existing_op, test/test_custom_ops.py::TestCustomOp::test_backward_impl_on_existing_op_CompositeImplicitAutograd, test/test_custom_ops.py::TestCustomOp::test_backward_impl_on_existing_op_incorrect_schema_mutable, test/test_custom_ops.py::TestCustomOp::test_backward_impl_on_existing_op_incorrect_schema_no_output, test/test_custom_ops.py::TestCustomOp::test_backward_impl_on_existing_op_incorrect_schema_views, test/test_custom_ops.py::TestCustomOp::test_backward_impl_on_existing_op_with_key_key_Autograd, test/test_custom_ops.py::TestCustomOp::test_backward_impl_on_existing_op_with_key_key_AutogradCPU, test/test_custom_ops.py::TestCustomOp::test_backward_impl_on_existing_op_with_key_key_AutogradCUDA, test/test_custom_ops.py::TestCustomOp::test_backward_output_differentiability_non_tensor, test/test_custom_ops.py::TestCustomOp::test_backward_output_differentiability_numel, test/test_custom_ops.py::TestCustomOp::test_backward_output_differentiability_tensorlist, test/test_custom_ops.py::TestCustomOp::test_backward_output_differentiability_type, test/test_custom_ops.py::TestCustomOp::test_backward_partially_registered, test/test_custom_ops.py::TestCustomOp::test_backward_returns_dict, test/test_custom_ops.py::TestCustomOp::test_backward_tensorlist_input_requires_list_grads, test/test_custom_ops.py::TestCustomOp::test_backward_tensorlist_input_requires_list_grads_none_or_Tensor, test/test_custom_ops.py::TestCustomOp::test_backward_tensorlist_input_requires_list_grads_with_same_numel, test/test_custom_ops.py::TestCustomOp::test_basic_make_fx, test/test_custom_ops.py::TestCustomOp::test_builtin_aten_ops_are_pt2_compliant, test/test_custom_ops.py::TestCustomOp::test_builtin_torchscript_ops, test/test_custom_ops.py::TestCustomOp::test_data_dependent_basic, test/test_custom_ops.py::TestCustomOp::test_data_dependent_compile, test/test_custom_ops.py::TestCustomOp::test_data_dependent_fake_tracing, test/test_custom_ops.py::TestCustomOp::test_data_dependent_nms_dynamic_compile, test/test_custom_ops.py::TestCustomOp::test_define_and_impl, test/test_custom_ops.py::TestCustomOp::test_define_bad_schema, test/test_custom_ops.py::TestCustomOp::test_define_validation, test/test_custom_ops.py::TestCustomOp::test_define_with_tags_list, test/test_custom_ops.py::TestCustomOp::test_define_with_tags_single, test/test_custom_ops.py::TestCustomOp::test_define_with_tags_tuple, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_duplicate_impl, test/test_custom_ops.py::TestCustomOp::test_functionalize_error, test/test_custom_ops.py::TestCustomOp::test_impl_abstract_overload, test/test_custom_ops.py::TestCustomOp::test_impl_cpu, test/test_custom_ops.py::TestCustomOp::test_impl_device_cpu, test/test_custom_ops.py::TestCustomOp::test_impl_device_cuda, test/test_custom_ops.py::TestCustomOp::test_impl_device_function, test/test_custom_ops.py::TestCustomOp::test_impl_device_invalid, test/test_custom_ops.py::TestCustomOp::test_impl_function, test/test_custom_ops.py::TestCustomOp::test_impl_invalid_devices, test/test_custom_ops.py::TestCustomOp::test_impl_meta, test/test_custom_ops.py::TestCustomOp::test_impl_multiple, test/test_custom_ops.py::TestCustomOp::test_impl_on_existing_op, test/test_custom_ops.py::TestCustomOp::test_impl_on_existing_op_with_cpu_registration_key_CPU, test/test_custom_ops.py::TestCustomOp::test_impl_on_existing_op_with_cpu_registration_key_CUDA, test/test_custom_ops.py::TestCustomOp::test_impl_on_existing_op_with_cpu_registration_key_CompositeExplicitAutograd, test/test_custom_ops.py::TestCustomOp::test_impl_on_existing_op_with_cpu_registration_key_CompositeImplicitAutograd, test/test_custom_ops.py::TestCustomOp::test_impl_separate, test/test_custom_ops.py::TestCustomOp::test_incorrect_schema_types, test/test_custom_ops.py::TestCustomOp::test_infer_schema_no_return, test/test_custom_ops.py::TestCustomOp::test_infer_schema_supported, test/test_custom_ops.py::TestCustomOp::test_infer_schema_unsupported, test/test_custom_ops.py::TestCustomOp::test_invalid_qualname, test/test_custom_ops.py::TestCustomOp::test_invalid_schemas, test/test_custom_ops.py::TestCustomOp::test_is_functional_schema, test/test_custom_ops.py::TestCustomOp::test_is_tensorlist_like_type, test/test_custom_ops.py::TestCustomOp::test_legacy_define, test/test_custom_ops.py::TestCustomOp::test_legacy_impl, test/test_custom_ops.py::TestCustomOp::test_lifetime, test/test_custom_ops.py::TestCustomOp::test_meta_for_data_dependent_shape_operation, test/test_custom_ops.py::TestCustomOp::test_name_must_match, test/test_custom_ops.py::TestCustomOp::test_new_data_dependent_symint, test/test_custom_ops.py::TestCustomOp::test_not_implemented_error, test/test_custom_ops.py::TestCustomOp::test_override_cea, test/test_custom_ops.py::TestCustomOp::test_override_fake, test/test_custom_ops.py::TestCustomOp::test_override_impl, test/test_custom_ops.py::TestCustomOp::test_override_meta, test/test_custom_ops.py::TestCustomOp::test_private_ctor, test/test_custom_ops.py::TestCustomOp::test_reserved_ns, test/test_custom_ops.py::TestCustomOp::test_resolve_packet, test/test_custom_ops.py::TestCustomOp::test_save_for_backward_inputs_are_namedtuple, test/test_custom_ops.py::TestCustomOp::test_schema_matches_signature, test/test_custom_ops.py::TestCustomOp::test_sequences, test/test_custom_ops.py::TestCustomOp::test_supported_param_types, test/test_custom_ops.py::TestCustomOp::test_supported_return_types_multi_return, test/test_custom_ops.py::TestCustomOp::test_supported_return_types_single_return, test/test_custom_ops.py::TestCustomOp::test_supported_schemas, test/test_custom_ops.py::TestCustomOp::test_symints, test/test_custom_ops.py::TestCustomOp::test_unsupported_param_types, test/test_custom_ops.py::TestCustomOp::test_unsupported_schemas, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_dynamic__test_delayed_error, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_dynamic__test_delayed_error_no_requires_grad, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_dynamic__test_incorrect_schema, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_dynamic__test_inplace, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_dynamic__test_mm, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_dynamic__test_mm_errors, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_dynamic__test_mm_fake, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_dynamic__test_mm_meta, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_dynamic__test_no_abstract, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_dynamic__test_nonzero, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_static__test_delayed_error, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_static__test_delayed_error_no_requires_grad, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_static__test_incorrect_schema, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_static__test_inplace, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_static__test_mm, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_static__test_mm_errors, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_static__test_mm_fake, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_static__test_mm_meta, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_static__test_no_abstract, test/test_custom_ops.py::MiniOpTest::test_aot_dispatch_static__test_nonzero, test/test_custom_ops.py::MiniOpTest::test_autograd_registration__test_delayed_error, test/test_custom_ops.py::MiniOpTest::test_autograd_registration__test_delayed_error_no_requires_grad, test/test_custom_ops.py::MiniOpTest::test_autograd_registration__test_incorrect_schema, test/test_custom_ops.py::MiniOpTest::test_autograd_registration__test_inplace, test/test_custom_ops.py::MiniOpTest::test_autograd_registration__test_mm, test/test_custom_ops.py::MiniOpTest::test_autograd_registration__test_mm_errors, test/test_custom_ops.py::MiniOpTest::test_autograd_registration__test_mm_fake, test/test_custom_ops.py::MiniOpTest::test_autograd_registration__test_mm_meta, test/test_custom_ops.py::MiniOpTest::test_autograd_registration__test_no_abstract, test/test_custom_ops.py::MiniOpTest::test_autograd_registration__test_nonzero, test/test_custom_ops.py::MiniOpTest::test_delayed_error, test/test_custom_ops.py::MiniOpTest::test_delayed_error_no_requires_grad, test/test_custom_ops.py::MiniOpTest::test_dont_generate, test/test_custom_ops.py::MiniOpTest::test_faketensor__test_delayed_error, test/test_custom_ops.py::MiniOpTest::test_faketensor__test_delayed_error_no_requires_grad, test/test_custom_ops.py::MiniOpTest::test_faketensor__test_incorrect_schema, test/test_custom_ops.py::MiniOpTest::test_faketensor__test_inplace, test/test_custom_ops.py::MiniOpTest::test_faketensor__test_mm, test/test_custom_ops.py::MiniOpTest::test_faketensor__test_mm_errors, test/test_custom_ops.py::MiniOpTest::test_faketensor__test_mm_fake, test/test_custom_ops.py::MiniOpTest::test_faketensor__test_mm_meta, test/test_custom_ops.py::MiniOpTest::test_faketensor__test_no_abstract, test/test_custom_ops.py::MiniOpTest::test_faketensor__test_nonzero, test/test_custom_ops.py::MiniOpTest::test_incorrect_schema, test/test_custom_ops.py::MiniOpTest::test_inplace, test/test_custom_ops.py::MiniOpTest::test_mm, test/test_custom_ops.py::MiniOpTest::test_mm_errors, test/test_custom_ops.py::MiniOpTest::test_mm_fake, test/test_custom_ops.py::MiniOpTest::test_mm_meta, test/test_custom_ops.py::MiniOpTest::test_no_abstract, test/test_custom_ops.py::MiniOpTest::test_nonzero, test/test_custom_ops.py::MiniOpTest::test_pt2_compliant_tag_aten_mm, test/test_custom_ops.py::MiniOpTest::test_pt2_compliant_tag_aten_nonzero, test/test_custom_ops.py::MiniOpTest::test_pt2_compliant_tag_aten_sin_, test/test_custom_ops.py::MiniOpTest::test_pt2_compliant_tag_mini_op_test_delayed_error, test/test_custom_ops.py::MiniOpTest::test_pt2_compliant_tag_mini_op_test_incorrect_schema, test/test_custom_ops.py::MiniOpTest::test_pt2_compliant_tag_mini_op_test_no_abstract, test/test_custom_ops.py::MiniOpTest::test_schema__test_delayed_error, test/test_custom_ops.py::MiniOpTest::test_schema__test_delayed_error_no_requires_grad, test/test_custom_ops.py::MiniOpTest::test_schema__test_incorrect_schema, test/test_custom_ops.py::MiniOpTest::test_schema__test_inplace, test/test_custom_ops.py::MiniOpTest::test_schema__test_mm, test/test_custom_ops.py::MiniOpTest::test_schema__test_mm_errors, test/test_custom_ops.py::MiniOpTest::test_schema__test_mm_fake, test/test_custom_ops.py::MiniOpTest::test_schema__test_mm_meta, test/test_custom_ops.py::MiniOpTest::test_schema__test_no_abstract, test/test_custom_ops.py::MiniOpTest::test_schema__test_nonzero, test/test_custom_ops.py::TestCustomOpAPI::test_any_output_is_alias_to_input_or_output, test/test_custom_ops.py::TestCustomOpAPI::test_any_requires_grad, test/test_custom_ops.py::TestCustomOpAPI::test_basic, test/test_custom_ops.py::TestCustomOpAPI::test_compile, test/test_custom_ops.py::TestCustomOpAPI::test_default_values, test/test_custom_ops.py::TestCustomOpAPI::test_disallows_output_aliasing, test/test_custom_ops.py::TestCustomOpAPI::test_factory_function, test/test_custom_ops.py::TestCustomOpAPI::test_fake, test/test_custom_ops.py::TestCustomOpAPI::test_kwarg_only_tensors, test/test_custom_ops.py::TestCustomOpAPI::test_layout_constraint_tags, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_autocast, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_autocast_list_input, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_autocast_low_level, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_autocast_multiple_times, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_autocast_multiple_times_different_devices, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_autograd, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_autograd_low_level, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_fake, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_fake_source_idx_0, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_fake_source_idx_1, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_fake_source_idx_2, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_fake_source_idx_3, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_fake_source_idx_4, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_fake_source_idx_5, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_kernel, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_kernel_low_level, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_torch_dispatch, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_torch_dispatch_low_level, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_torch_dispatch_rule_mode, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_torch_dispatch_rule_subclass, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_vmap, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_vmap_library_decorator, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_vmap_op_decorator, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_vmap_register_multiple_times, test/test_custom_ops.py::TestCustomOpAPI::test_library_register_vmap_register_multiple_times_2, test/test_custom_ops.py::TestCustomOpAPI::test_library_schema_infer, test/test_custom_ops.py::TestCustomOpAPI::test_manual_schema, test/test_custom_ops.py::TestCustomOpAPI::test_manual_schema_error, test/test_custom_ops.py::TestCustomOpAPI::test_multi_types, test/test_custom_ops.py::TestCustomOpAPI::test_mutated, test/test_custom_ops.py::TestCustomOpAPI::test_mutated_error, test/test_custom_ops.py::TestCustomOpAPI::test_mutated_unknown, test/test_custom_ops.py::TestCustomOpAPI::test_no_grad_skips_autograd, test/test_custom_ops.py::TestCustomOpAPI::test_overloading, test/test_custom_ops.py::TestCustomOpAPI::test_register_autograd_defaults, test/test_custom_ops.py::TestCustomOpAPI::test_register_autograd_error_cases, test/test_custom_ops.py::TestCustomOpAPI::test_register_autograd_kwargonly_low_level, test/test_custom_ops.py::TestCustomOpAPI::test_register_vmap_defaults, test/test_custom_ops.py::TestCustomOpAPI::test_register_vmap_kwargonly_low_level, test/test_custom_ops.py::TestCustomOpAPI::test_replacement, test/test_custom_ops.py::TestCustomOpAPI::test_set_kernel_enabled, test/test_custom_ops.py::TestCustomOpAPI::test_split_device, test/test_custom_ops.py::TestCustomOpAPI::test_supports_tensorlist, test/test_custom_ops.py::MiniOpTestOther::test_aot_dispatch_dynamic__test_nonzero_again, test/test_custom_ops.py::MiniOpTestOther::test_aot_dispatch_static__test_nonzero_again, test/test_custom_ops.py::MiniOpTestOther::test_autograd_registration__test_nonzero_again, test/test_custom_ops.py::MiniOpTestOther::test_faketensor__test_nonzero_again, test/test_custom_ops.py::MiniOpTestOther::test_nonzero_again, test/test_custom_ops.py::MiniOpTestOther::test_pt2_compliant_tag_aten_mm, test/test_custom_ops.py::MiniOpTestOther::test_pt2_compliant_tag_aten_nonzero, test/test_custom_ops.py::MiniOpTestOther::test_pt2_compliant_tag_aten_sin_, test/test_custom_ops.py::MiniOpTestOther::test_pt2_compliant_tag_mini_op_test_delayed_error, test/test_custom_ops.py::MiniOpTestOther::test_pt2_compliant_tag_mini_op_test_incorrect_schema, test/test_custom_ops.py::MiniOpTestOther::test_pt2_compliant_tag_mini_op_test_no_abstract, test/test_custom_ops.py::MiniOpTestOther::test_schema__test_nonzero_again, test/test_custom_ops.py::TestGenerateOpcheckTests::test_MiniOpTest, test/test_custom_ops.py::TestGenerateOpcheckTests::test_dont_generate_decorator, test/test_custom_ops.py::TestGenerateOpcheckTests::test_failures_dict_validation, test/test_custom_ops.py::TestGenerateOpcheckTests::test_generate_repro_no_save_data, test/test_custom_ops.py::TestGenerateOpcheckTests::test_generate_repro_save_data, test/test_custom_ops.py::TestGenerateOpcheckTests::test_is_inside_opcheck_mode, test/test_custom_ops.py::TestGenerateOpcheckTests::test_opcheck, test/test_custom_ops.py::TestGenerateOpcheckTests::test_opcheck_bad_op, test/test_custom_ops.py::TestGenerateOpcheckTests::test_opcheck_customopdef, test/test_custom_ops.py::TestGenerateOpcheckTests::test_opcheck_does_not_require_extra_deps, test/test_custom_ops.py::TestTypeConversion::test_mixed_types, test/test_custom_ops.py::TestTypeConversion::test_optional, test/test_custom_ops.py::TestTypeConversion::test_simple_tuple, test/test_custom_ops.py::TestTypeConversion::test_supported_types, test/test_custom_ops.py::TestOpProfiles::test_duplicate_registration_custom_op, test/test_custom_ops.py::TestOpProfiles::test_duplicate_registration_impl, test/test_custom_ops.py::TestOpProfiles::test_fake_registration, test/test_custom_ops.py::TestOpProfiles::test_save_to_file, test/test_custom_ops.py::TestOpProfiles::test_version, test/test_custom_ops.py::TestOpProfiles::test_yaml, test/test_custom_ops.py::TestCustomOpTestingCPU::test_aot_autograd_check_degenerate_cases_check_gradients_False_dynamic_False_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_aot_autograd_check_degenerate_cases_check_gradients_False_dynamic_True_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_aot_autograd_check_degenerate_cases_check_gradients_auto_dynamic_False_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_aot_autograd_check_degenerate_cases_check_gradients_auto_dynamic_True_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_assert_raises_regex_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_autograd_registered_at_backend_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_autograd_registration_check_autograd_kernel_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_autograd_registration_check_compositeimplicitautograd_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_autograd_registration_check_incorrect_composite_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_autograd_registration_check_incorrect_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_global_state_mutation_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_incorrect_abstract_impl_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_incorrect_schema_mutation_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_incorrect_schema_view_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_missing_abstract_impl_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_missing_functionalization_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_fails_basic_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_opinfo_NumpyCatCustomOp_cpu_float32, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_opinfo_NumpyCubeCustomOp_cpu_float32, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_opinfo_NumpyMulCustomOp_cpu_float32, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_opinfo_NumpyMulScalarCustomOp_cpu_float32, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_opinfo_NumpyNMSCustomOp_cpu_float32, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_opinfo_NumpyNonzeroCustomOp_cpu_float32, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_opinfo_NumpySortCustomOp_cpu_float32, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_opinfo_NumpySplitCopyCustomOp_cpu_float32, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_opinfo_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_opinfo_NumpyTakeCustomOp_cpu_float32, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_opinfo_NumpyViewCopyCustomOp_cpu_float32, test/test_custom_ops.py::TestCustomOpTestingCPU::test_opcheck_unbacked_stride_cpu, test/test_custom_ops.py::TestCustomOpTestingCPU::test_single_element_tuple_output_cpu 2025-07-17T08:47:47.6664027Z 2025-07-17T08:47:51.5179207Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:47:51.5182430Z import pkg_resources 2025-07-17T08:47:51.6438679Z Running test_optim 3/3 ... [2025-07-17 08:47:51.643461] 2025-07-17T08:47:51.6439428Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:47:51.6442339Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_optim.py', '-m', 'not serial', '--shard-id=3', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:47:51.643895] 2025-07-17T08:52:28.2682590Z 2025-07-17T08:52:28.2683978Z test_fx_experimental 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_experimental_1.1_e3c83ca6ef777ca5_.log 2025-07-17T08:52:28.3066506Z Running 721 items in this shard: test/test_fx_experimental.py::TestFXExperimental::test_annotate_getitem_node, test/test_fx_experimental.py::TestFXExperimental::test_annotate_returns_with_schema, test/test_fx_experimental.py::TestFXExperimental::test_aot_based_partition, test/test_fx_experimental.py::TestFXExperimental::test_call_to_assert_no_msg, test/test_fx_experimental.py::TestFXExperimental::test_call_to_assert_with_empty_msg, test/test_fx_experimental.py::TestFXExperimental::test_call_to_assert_with_msg, test/test_fx_experimental.py::TestFXExperimental::test_call_to_assert_with_multiline_message, test/test_fx_experimental.py::TestFXExperimental::test_conv_bn_fusion, test/test_fx_experimental.py::TestFXExperimental::test_conv_bn_fusion_mixed_dtype, test/test_fx_experimental.py::TestFXExperimental::test_conv_bn_fusion_not_running_state, test/test_fx_experimental.py::TestFXExperimental::test_cost_aware_partition, test/test_fx_experimental.py::TestFXExperimental::test_fetch, test/test_fx_experimental.py::TestFXExperimental::test_find_single_partition, test/test_fx_experimental.py::TestFXExperimental::test_lack_of_devices, test/test_fx_experimental.py::TestFXExperimental::test_large_node_error, test/test_fx_experimental.py::TestFXExperimental::test_merge_matmuls, test/test_fx_experimental.py::TestFXExperimental::test_meta_tracer, test/test_fx_experimental.py::TestFXExperimental::test_normalize_args, test/test_fx_experimental.py::TestFXExperimental::test_normalize_args_perserve_type, test/test_fx_experimental.py::TestFXExperimental::test_normalize_args_preserve_meta, test/test_fx_experimental.py::TestFXExperimental::test_normalize_binary_operators, test/test_fx_experimental.py::TestFXExperimental::test_normalize_modules_exhaustive, test/test_fx_experimental.py::TestFXExperimental::test_optimize_for_inference_cpu, test/test_fx_experimental.py::TestFXExperimental::test_optimize_for_inference_cpu_torchvision, test/test_fx_experimental.py::TestFXExperimental::test_partition_device_mapping, test/test_fx_experimental.py::TestFXExperimental::test_partition_latency, test/test_fx_experimental.py::TestFXExperimental::test_partition_node_manipulation, test/test_fx_experimental.py::TestFXExperimental::test_replace_target_nodes_with, test/test_fx_experimental.py::TestFXExperimental::test_saturate_host, test/test_fx_experimental.py::TestFXExperimental::test_size_based_partition, test/test_fx_experimental.py::TestFXExperimental::test_sparse_nn_partition, test/test_fx_experimental.py::TestFXExperimental::test_split_module_dead_code, test/test_fx_experimental.py::TestFXExperimental::test_split_module_default_arg, test/test_fx_experimental.py::TestFXExperimental::test_split_module_input_names, test/test_fx_experimental.py::TestFXExperimental::test_split_module_keep_original_order_and_noop_graph, test/test_fx_experimental.py::TestFXExperimental::test_split_module_kwargs_expansion, test/test_fx_experimental.py::TestFXExperimental::test_split_module_return_node, test/test_fx_experimental.py::TestFXExperimental::test_split_qualname_mapping, test/test_fx_experimental.py::TestFXExperimental::test_subgraph_creation, test/test_fx_experimental.py::TestFXExperimental::test_subgraph_trivial_resnet, test/test_fx_experimental.py::TestFXExperimental::test_subgraph_uniquename, test/test_fx_experimental.py::TestFXExperimental::test_to_folder, test/test_fx_experimental.py::TestFXExperimental::test_traceable_function_with_nonstandard_name, test/test_fx_experimental.py::TestFXExperimental::test_type_matches, test/test_fx_experimental.py::TestTranslationValidation::test_sat, test/test_fx_experimental.py::TestTranslationValidation::test_sat_bitwise, test/test_fx_experimental.py::TestTranslationValidation::test_sympy_to_z3, test/test_fx_experimental.py::TestTranslationValidation::test_unsat, test/test_fx_experimental.py::TestTranslationValidation::test_z3str, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_args_op_overload_cpu, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_H_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_T_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive___getitem___cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive___radd___cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive___rdiv___cpu_float32, 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test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_i0e_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_i1_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_i1e_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_laguerre_polynomial_l_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_legendre_polynomial_p_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_log_ndtr_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_modified_bessel_i0_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_modified_bessel_i1_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_modified_bessel_k0_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_modified_bessel_k1_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_ndtr_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_ndtri_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_scaled_modified_bessel_k0_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_scaled_modified_bessel_k1_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_spherical_bessel_j0_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_xlog1py_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_special_zeta_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_split_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_split_list_args_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_split_with_sizes_copy_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_split_with_sizes_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_sqrt_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_square_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_squeeze_copy_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_squeeze_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_squeeze_multiple_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_stack_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_std_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_std_mean_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_std_mean_unbiased_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_std_unbiased_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_stft_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_sub_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_sum_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_sum_to_size_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_svd_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_svd_lowrank_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_t_copy_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_t_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_take_along_dim_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_take_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_tan_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_tanh_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_tensor_split_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_tensordot_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_tile_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_to_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_to_sparse_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_topk_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_trace_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_transpose_copy_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_transpose_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_trapezoid_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_trapz_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_triangular_solve_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_tril_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_triu_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_true_divide_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_trunc_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_unbind_copy_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_unbind_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_unflatten_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_unfold_copy_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_unfold_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_uniform_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_unique_consecutive_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_unique_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_unsafe_chunk_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_unsafe_split_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_unsqueeze_copy_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_unsqueeze_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_var_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_var_mean_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_var_mean_unbiased_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_var_unbiased_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_vdot_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_view_as_complex_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_view_as_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_view_copy_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_view_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_vsplit_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_vstack_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_where_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_xlogy_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_zero__cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_zeros_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_operator_exhaustive_zeros_like_cpu_float32, test/test_fx_experimental.py::TestNormalizeOperatorsCPU::test_normalize_quantized_eb_cpu 2025-07-17T08:52:28.3437239Z 2025-07-17T08:52:31.5983864Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:52:31.5987313Z import pkg_resources 2025-07-17T08:52:31.7250467Z Running test_per_overload_api 1/1 ... [2025-07-17 08:52:31.724655] 2025-07-17T08:52:31.7251360Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:52:31.7254318Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_per_overload_api.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:52:31.725074] 2025-07-17T08:52:38.2494098Z 2025-07-17T08:52:38.2495498Z test_per_overload_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_per_overload_api_1.1_20525c8f27d78df7_.log 2025-07-17T08:52:38.2498408Z Running 3 items in this shard: test/test_per_overload_api.py::TestPerOverloadAPI::test_basics_opoverload, test/test_per_overload_api.py::TestPerOverloadAPI::test_basics_opoverloadpacket, test/test_per_overload_api.py::TestPerOverloadAPI::test_decompose 2025-07-17T08:52:38.2500321Z 2025-07-17T08:52:42.3361694Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:52:42.3364728Z import pkg_resources 2025-07-17T08:52:42.5189148Z Running test_expanded_weights 1/1 ... [2025-07-17 08:52:42.517883] 2025-07-17T08:52:42.5189989Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:52:42.5192120Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_expanded_weights.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:52:42.518340] 2025-07-17T08:53:39.3412132Z 2025-07-17T08:53:39.3413673Z test_expanded_weights 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_expanded_weights_1.1_830e24f4c7ccb3fd_.log 2025-07-17T08:53:39.3511105Z Running 189 items in this shard: test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_forward_helper_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_forward_helper_failure_args_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_set_grad_sample_if_exists_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_set_grad_sample_if_exists_failure_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_sum_over_all_but_batch_and_last_n_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_unpack_expanded_weight_or_tensor_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_unpack_expanded_weight_or_tensor_failure_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_unpack_expanded_weight_or_tensor_with_custom_function_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_cnn_model_mean_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_cnn_model_sum_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_embedding_model_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_error_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_complex128, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_complex64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_int64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_complex128, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_complex64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_int64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_complex128, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_complex64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_int64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_embedding_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_embedding_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_embedding_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_embedding_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_group_norm_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_group_norm_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_group_norm_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_group_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_instance_norm_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_instance_norm_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_instance_norm_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_instance_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_layer_norm_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_layer_norm_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_layer_norm_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_layer_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_complex128, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_complex64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_int16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_int32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_int64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_int8, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_uint8, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_conv1d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_conv2d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_conv3d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_embedding_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_group_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_instance_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_layer_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_linear_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_conv1d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_conv2d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_conv3d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_embedding_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_group_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_instance_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_layer_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_linear_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_conv1d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_conv2d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_conv3d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_embedding_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_group_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_instance_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_layer_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_linear_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_group_norm_error_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_group_norm_model_num_dim_1_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_group_norm_model_num_dim_2_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_group_norm_model_num_dim_3_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_instance_norm_model_num_dim_1_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_instance_norm_model_num_dim_2_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_instance_norm_model_num_dim_3_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_layer_norm_model_num_dim_1_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_layer_norm_model_num_dim_2_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_layer_norm_model_num_dim_3_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_conv1d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_conv2d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_conv3d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_embedding_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_group_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_instance_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_layer_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_linear_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_circular_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_circular_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad1_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad1_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad1size1_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad1size1_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad2size1_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad2size1_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_reflect_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_reflect_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_replicate_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_replicate_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_stride_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_stride_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_zero_batch_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_zero_batch_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_zeros_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_zeros_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_circular_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_circular_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_dilated_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_dilated_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_no_bias_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_no_bias_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_padding_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_padding_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_reflect_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_reflect_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_replicate_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_replicate_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_strided_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_strided_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_zero_batch_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_zero_batch_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_zeros_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_zeros_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_1x1x1_no_bias_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_1x1x1_no_bias_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_circular_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_circular_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_no_bias_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_no_bias_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_replicate_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_replicate_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_stride_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_stride_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_stride_padding_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_stride_padding_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_zero_batch_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_zero_batch_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_zeros_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_zeros_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Embedding_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Embedding_discontiguous_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Embedding_discontiguous_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Embedding_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_LayerNorm_3d_no_affine_large_feature_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_LayerNorm_3d_no_affine_large_feature_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_no_batch_dim_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_no_batch_dim_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_no_bias_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_no_bias_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_GRU_eval_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_GRU_eval_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_GRU_train_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_GRU_train_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_LSTM_eval_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_LSTM_eval_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_LSTM_train_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_LSTM_train_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_RNN_eval_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_RNN_eval_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_RNN_train_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_RNN_train_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_per_sample_api_compute_batch_size_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_per_sample_api_compute_batch_size_not_pytreeable_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_per_sample_api_failing_cpu 2025-07-17T08:53:39.3606221Z 2025-07-17T08:53:42.5658827Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:53:42.5661594Z import pkg_resources 2025-07-17T08:53:42.6924127Z Running lazy/test_bindings 1/1 ... [2025-07-17 08:53:42.692035] 2025-07-17T08:53:42.6924865Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:53:42.6927674Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_bindings.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:53:42.692410] 2025-07-17T08:53:46.0130951Z 2025-07-17T08:53:46.0132046Z lazy/test_bindings 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_bindings_1.1_16c21755ff92cabf_.log 2025-07-17T08:53:46.0133516Z Running 1 items in this shard: test/lazy/test_bindings.py::test_metrics 2025-07-17T08:53:46.0133982Z 2025-07-17T08:53:49.2761058Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:53:49.2762630Z import pkg_resources 2025-07-17T08:53:49.4028286Z Running dynamo/test_cudagraphs_expandable_segments 1/1 ... [2025-07-17 08:53:49.402453] 2025-07-17T08:53:49.4028915Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:53:49.4031521Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_cudagraphs_expandable_segments.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:53:49.402851] 2025-07-17T08:53:52.8822325Z 2025-07-17T08:53:52.8824452Z dynamo/test_cudagraphs_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_expandable_segments_1.1_9f2d7a56c06ab757_.log 2025-07-17T08:53:52.8825874Z 2025-07-17T08:53:56.1787292Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:53:56.1790085Z import pkg_resources 2025-07-17T08:53:56.3048406Z Running test_native_functions 1/1 ... [2025-07-17 08:53:56.304427] 2025-07-17T08:53:56.3049135Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:53:56.3052090Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_native_functions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:53:56.304837] 2025-07-17T08:54:03.6799545Z 2025-07-17T08:54:03.6801077Z test_native_functions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_native_functions_1.1_09a9529773192859_.log 2025-07-17T08:54:03.6806309Z Running 11 items in this shard: test/test_native_functions.py::TestNativeFunctions::test_intlist_error_with_overload, test/test_native_functions.py::TestNativeFunctions::test_optional_filled_intlist, test/test_native_functions.py::TestNativeFunctions::test_optional_floatlist, test/test_native_functions.py::TestNativeFunctions::test_optional_floatlist_invalid, test/test_native_functions.py::TestNativeFunctions::test_optional_intlist, test/test_native_functions.py::TestNativeFunctions::test_optional_intlist_invalid, test/test_native_functions.py::TestNativeFunctions::test_string_defaults, test/test_native_functions.py::TestNativeFunctions::test_symintlist_error, test/test_native_functions.py::TestNativeFunctions::test_symintlist_error_with_overload, test/test_native_functions.py::TestNativeFunctions::test_symintlist_error_with_overload_but_is_unique, test/test_native_functions.py::TestNativeFunctions::test_vararg_symintlist_error 2025-07-17T08:54:03.6811167Z 2025-07-17T08:54:06.9464179Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:54:06.9467049Z import pkg_resources 2025-07-17T08:54:07.0739086Z Running test_type_hints 1/1 ... [2025-07-17 08:54:07.073529] 2025-07-17T08:54:07.0739883Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:54:07.0743178Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_type_hints.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:54:07.073936] 2025-07-17T08:54:11.6958914Z 2025-07-17T08:54:11.6960095Z test_type_hints 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_type_hints_1.1_2c3e2ee2d82a0c51_.log 2025-07-17T08:54:11.6961016Z Running 1 items in this shard: test/test_type_hints.py::TestTypeHints::test_doc_examples 2025-07-17T08:54:11.6961437Z 2025-07-17T08:54:14.9206568Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:54:14.9209225Z import pkg_resources 2025-07-17T08:54:15.0470681Z Running dynamo/test_export 1/1 ... [2025-07-17 08:54:15.046624] 2025-07-17T08:54:15.0471542Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:54:15.0473853Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_export.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:54:15.047040] 2025-07-17T08:54:18.5500966Z 2025-07-17T08:54:18.5502357Z dynamo/test_export 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_export_1.1_e0f492f41f657604_.log 2025-07-17T08:54:18.5503500Z 2025-07-17T08:54:21.7611122Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:54:21.7613896Z import pkg_resources 2025-07-17T08:54:21.8877320Z Running test_import_stats 1/1 ... [2025-07-17 08:54:21.887293] 2025-07-17T08:54:21.8878117Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:54:21.8880769Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_import_stats.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:54:21.887734] 2025-07-17T08:54:29.4145774Z 2025-07-17T08:54:29.4147112Z test_import_stats 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_import_stats_1.1_9673cbc2962f979d_.log 2025-07-17T08:54:29.4148550Z Running 2 items in this shard: test/test_import_stats.py::TestImportTime::test_time_cuda_device_count, test/test_import_stats.py::TestImportTime::test_time_import_torch 2025-07-17T08:54:29.4149336Z 2025-07-17T08:54:32.6754375Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:54:32.6756829Z import pkg_resources 2025-07-17T08:54:32.8007049Z Running test_module_tracker 1/1 ... [2025-07-17 08:54:32.800308] 2025-07-17T08:54:32.8007722Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:54:32.8009967Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_module_tracker.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:54:32.800697] 2025-07-17T08:54:48.3913343Z 2025-07-17T08:54:48.3914952Z test_module_tracker 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_module_tracker_1.1_1dab3b1e114dee9a_.log 2025-07-17T08:54:48.3924931Z Running 3 items in this shard: test/test_module_tracker.py::TestModuleTracker::test_bw_detection, test/test_module_tracker.py::TestModuleTracker::test_confused_hierarchy, test/test_module_tracker.py::TestModuleTracker::test_module_hierarchy 2025-07-17T08:54:48.3927294Z 2025-07-17T08:54:51.6550908Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:54:51.6553671Z import pkg_resources 2025-07-17T08:54:51.7822317Z Running test_fx_passes 1/1 ... [2025-07-17 08:54:51.781835] 2025-07-17T08:54:51.7823056Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:54:51.7825716Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_passes.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:54:51.782272] 2025-07-17T08:54:52.2381608Z 2025-07-17T08:54:52.2382512Z test_optim 3/3 was successful, full logs can be found in artifacts with path test/test-reports/test_optim_3.3_3ca6795fa31ae6a4_.log 2025-07-17T08:54:52.2637391Z Running 311 items in this shard: test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr1_T_mult_1, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr2, test/test_optim.py::TestLRScheduler::test_add_param_group_does_not_break_reduce_lr_on_plateau_min_lr_list, test/test_optim.py::TestLRScheduler::test_chained_lr1, test/test_optim.py::TestLRScheduler::test_chained_lr3, test/test_optim.py::TestLRScheduler::test_closed_form_constantlr, test/test_optim.py::TestLRScheduler::test_closed_form_cos_anneal_lr, test/test_optim.py::TestLRScheduler::test_closed_form_linearlr, test/test_optim.py::TestLRScheduler::test_closed_form_multi_step_lr, test/test_optim.py::TestLRScheduler::test_compound_cosanneal_and_linearlr, test/test_optim.py::TestLRScheduler::test_compound_cosanneal_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau2, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau3, test/test_optim.py::TestLRScheduler::test_compound_step_and_exp_lr, test/test_optim.py::TestLRScheduler::test_compound_step_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass0, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass1, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass5, test/test_optim.py::TestLRScheduler::test_constantlr_with_epoch, test/test_optim.py::TestLRScheduler::test_cos_anneal_lr, test/test_optim.py::TestLRScheduler::test_cosine_then_cyclic, test/test_optim.py::TestLRScheduler::test_cycle_lr_cycle_momentum_with_beta1_optimizer, test/test_optim.py::TestLRScheduler::test_cycle_lr_exp_range_mode_one_lr, test/test_optim.py::TestLRScheduler::test_cycle_lr_state_dict_picklable, test/test_optim.py::TestLRScheduler::test_error_when_getlr_has_epoch, test/test_optim.py::TestLRScheduler::test_get_last_lr_constantlr, test/test_optim.py::TestLRScheduler::test_get_last_lr_linearlr, test/test_optim.py::TestLRScheduler::test_get_last_lr_sequentiallr, test/test_optim.py::TestLRScheduler::test_lambda_lr_state_dict_fn, test/test_optim.py::TestLRScheduler::test_lambda_lr_state_dict_obj, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass3, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass7, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass0_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass10_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass12_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass13_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass13_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass14_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass3_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass6_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass6_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass9_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass9_weights_only_True, test/test_optim.py::TestLRScheduler::test_new_pattern_no_warning, test/test_optim.py::TestLRScheduler::test_no_cyclic_references_in_step, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_with_overridden_optim_step, test/test_optim.py::TestLRScheduler::test_onecycle_lr_cosine_annealing, test/test_optim.py::TestLRScheduler::test_onecycle_lr_invalid_pct_start, test/test_optim.py::TestLRScheduler::test_onecycle_lr_linear_annealing, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau5, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau6, test/test_optim.py::TestLRScheduler::test_sequentiallr5, test/test_optim.py::TestDifferentiableOptimizer::test_adagrad, test/test_optim.py::TestDifferentiableOptimizer::test_adam_differentiable_lr, test/test_optim.py::TestDifferentiableOptimizer::test_adamw_differentiable_all_hyperparams, test/test_optim.py::TestDifferentiableOptimizer::test_adamw_differentiable_betas, test/test_optim.py::TestDifferentiableOptimizer::test_differentiable_lr, test/test_optim.py::TestDifferentiableOptimizer::test_differentiable_weight_decay_and_lr, test/test_optim.py::TestDifferentiableOptimizer::test_nadam, test/test_optim.py::TestSWAUtils::test_averaged_model_all_devices_ema_False, test/test_optim.py::TestSWAUtils::test_averaged_model_default_avg_fn_picklable, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_False_use_buffers_True, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_True_use_buffers_True, test/test_optim.py::TestSWAUtils::test_update_bn_dnn, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_AdamW_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_NAdam_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_Rprop_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_SGD_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_Adam_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_Adamax_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_RAdam_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_capturable_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_fused_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_fused_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_defaults_changed_to_foreach_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_defaults_changed_to_foreach_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_errors_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_errors_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_errors_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_errors_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_errors_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_foreach_large_tensor_Adadelta_cpu_float16, test/test_optim.py::TestOptimRenewedCPU::test_foreach_large_tensor_Adafactor_cpu_float16, test/test_optim.py::TestOptimRenewedCPU::test_foreach_large_tensor_AdamW_cpu_float16, test/test_optim.py::TestOptimRenewedCPU::test_foreach_large_tensor_Adam_cpu_float16, test/test_optim.py::TestOptimRenewedCPU::test_foreach_large_tensor_Rprop_cpu_float16, test/test_optim.py::TestOptimRenewedCPU::test_foreach_matches_forloop_ASGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_foreach_matches_forloop_Adam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_True_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_True_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_True_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_True_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_True_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_True_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_multigpu_with_lrsched_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_multigpu_with_lrsched_True_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_multigpu_with_lrsched_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_multigpu_with_lrsched_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_fused_cpu_matches_cuda_AdamW_cpu_bfloat16, test/test_optim.py::TestOptimRenewedCPU::test_fused_cpu_matches_cuda_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_fused_cpu_matches_cuda_Adam_cpu_bfloat16, test/test_optim.py::TestOptimRenewedCPU::test_fused_cpu_matches_cuda_Adam_cpu_float16, test/test_optim.py::TestOptimRenewedCPU::test_fused_cpu_matches_cuda_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_fused_cpu_matches_cuda_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_fused_does_not_step_if_foundinf_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_fused_error_on_params_on_meta_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_fused_large_tensor_Adagrad_cpu_float16, test/test_optim.py::TestOptimRenewedCPU::test_fused_matches_forloop_Adagrad_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_fused_matches_forloop_AdamW_cpu_bfloat16, test/test_optim.py::TestOptimRenewedCPU::test_fused_matches_forloop_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_fused_matches_forloop_AdamW_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_fused_matches_forloop_Adam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_fused_matches_forloop_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_fused_matches_forloop_SGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_grads_are_never_inplaced_into_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_grads_are_never_inplaced_into_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_grads_are_never_inplaced_into_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_grads_are_never_inplaced_into_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_grads_are_never_inplaced_into_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_nontensor_step_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_nontensor_step_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_nontensor_step_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_nontensor_step_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_post_hook_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_post_hook_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_post_hook_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_post_hook_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_post_hook_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_pre_hook_and_prepend_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_pre_hook_and_prepend_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_pre_hook_and_prepend_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_pre_hook_and_prepend_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_pre_hook_and_prepend_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_pre_post_hook_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_pre_post_hook_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_pre_post_hook_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_pre_post_hook_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_load_state_dict_pre_post_hook_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_mixed_device_dtype_impl_foreach_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_mixed_device_dtype_impl_foreach_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_mixed_device_dtype_impl_foreach_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_mixed_device_dtype_impl_foreach_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_mixed_device_dtype_impl_foreach_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_mixed_device_dtype_impl_fused_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_mixed_device_dtype_impl_fused_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_mixed_device_dtype_impl_fused_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_mixed_device_dtype_impl_fused_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_mixed_device_dtype_impl_fused_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_False_SGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_second_order_optims_return_consistent_types_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Adagrad_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_AdamW_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Rprop_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_SGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_SGD_cpu_float32 2025-07-17T08:54:52.2841590Z 2025-07-17T08:54:55.5170807Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:54:55.5173611Z import pkg_resources 2025-07-17T08:54:55.6429385Z Running dynamo/test_unittest 1/1 ... [2025-07-17 08:54:55.642528] 2025-07-17T08:54:55.6430165Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:54:55.6432801Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_unittest.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:54:55.642930] 2025-07-17T08:54:59.0380844Z 2025-07-17T08:54:59.0382033Z dynamo/test_unittest 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_unittest_1.1_ac566398ba9b967b_.log 2025-07-17T08:54:59.0382714Z 2025-07-17T08:55:02.5195284Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:55:02.5198072Z import pkg_resources 2025-07-17T08:55:02.6435256Z Running test_logging 1/1 ... [2025-07-17 08:55:02.643085] 2025-07-17T08:55:02.6436007Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:55:02.6438046Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_logging.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:55:02.643472] 2025-07-17T08:55:09.7315116Z 2025-07-17T08:55:09.7316309Z test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_logging_1.1_3a95ea13c2ab8585_.log 2025-07-17T08:55:09.7317634Z Running 1 items in this shard: test/test_logging.py::LoggingTest::testApiUsage 2025-07-17T08:55:09.7318198Z 2025-07-17T08:55:09.9325508Z 2025-07-17T08:55:09.9326892Z test_fx_passes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_passes_1.1_bfba66fd3e74a78f_.log 2025-07-17T08:55:09.9349086Z Running 53 items in this shard: test/test_fx_passes.py::TestFXGraphPasses::test_fuser_pass_deep_model, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition0, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition1, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition10, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition11, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition2, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition3, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition4, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition5, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition6, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition7, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition8, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition9, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition0, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition1, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition2, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition3, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn0_expected_partition0_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn10_expected_partition10_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn11_expected_partition11_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn12_expected_partition12_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn13_expected_partition13_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn14_expected_partition14_bookend_non_compute_pass_True, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn15_expected_partition15_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn16_expected_partition16_bookend_non_compute_pass_True, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn17_expected_partition17_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn18_expected_partition18_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn1_expected_partition1_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn2_expected_partition2_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn3_expected_partition3_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn4_expected_partition4_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn5_expected_partition5_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn6_expected_partition6_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn7_expected_partition7_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn8_expected_partition8_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn9_expected_partition9_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_independent_output_fn0_expected_partition0, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model0, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model1, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model10, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model11, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model12, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model13, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model14, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model15, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model2, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model3, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model4, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model5, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model6, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model7, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model8, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model9 2025-07-17T08:55:09.9370274Z 2025-07-17T08:55:13.0264585Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:55:13.0267587Z import pkg_resources 2025-07-17T08:55:13.1521212Z Running torch_np/test_basic 1/1 ... [2025-07-17 08:55:13.151658] 2025-07-17T08:55:13.1521961Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:55:13.1524183Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_basic.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:55:13.152070] 2025-07-17T08:55:13.2105963Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:55:13.2108775Z import pkg_resources 2025-07-17T08:55:13.3626336Z Running test_tensorexpr_pybind 1/1 ... [2025-07-17 08:55:13.362217] 2025-07-17T08:55:13.3627088Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:55:13.3630247Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensorexpr_pybind.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:55:13.362652] 2025-07-17T08:55:24.1411707Z 2025-07-17T08:55:24.1412989Z test_optim 2/3 was successful, full logs can be found in artifacts with path test/test-reports/test_optim_2.3_0b086c29f9b60be8_.log 2025-07-17T08:55:24.1671855Z Running 341 items in this shard: test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr3, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr_state_dict, test/test_optim.py::TestLRScheduler::test_add_param_group_errors_reduce_lr_on_plateau, test/test_optim.py::TestLRScheduler::test_chained_lr2, test/test_optim.py::TestLRScheduler::test_chained_lr4, test/test_optim.py::TestLRScheduler::test_chained_lr5, test/test_optim.py::TestLRScheduler::test_closed_form_exp_lr, test/test_optim.py::TestLRScheduler::test_compound_cosanneal_and_step_lr, test/test_optim.py::TestLRScheduler::test_compound_exp_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_compound_linearlr_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau4, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass2, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass8, test/test_optim.py::TestLRScheduler::test_constant_initial_params_onecyclelr, test/test_optim.py::TestLRScheduler::test_constant_initial_params_swalr, test/test_optim.py::TestLRScheduler::test_constantlr, test/test_optim.py::TestLRScheduler::test_cosine_lr_state_dict, test/test_optim.py::TestLRScheduler::test_cycle_lr_exp_range_mode, test/test_optim.py::TestLRScheduler::test_cycle_lr_removed_after_out_of_scope, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular2_mode_one_lr, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular_mode_one_lr, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular_mode_one_lr_no_momentum, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular_mode_step_size_up_down, test/test_optim.py::TestLRScheduler::test_lambda_lr, test/test_optim.py::TestLRScheduler::test_linear_linearlr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_linearlr, test/test_optim.py::TestLRScheduler::test_linearlr_start_factor_limits1, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass0, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass12, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass5, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass6, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass8, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass9, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass0_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass10_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass11_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass12_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass14_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass1_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass2_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass3_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass4_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass5_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass8_weights_only_True, test/test_optim.py::TestLRScheduler::test_multi_step_lr, test/test_optim.py::TestLRScheduler::test_multi_step_lr_state_dict, test/test_optim.py::TestLRScheduler::test_multi_step_lr_with_epoch, test/test_optim.py::TestLRScheduler::test_multiplicative_lr, test/test_optim.py::TestLRScheduler::test_new_pattern_no_warning_with_arg, test/test_optim.py::TestLRScheduler::test_new_pattern_no_warning_with_overridden_optim_step, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_resuming, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_resuming_with_arg, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_with_arg, test/test_optim.py::TestLRScheduler::test_onecycle_lr_legacy_state_dict, test/test_optim.py::TestLRScheduler::test_onecycle_lr_linear_annealing_three_phases, test/test_optim.py::TestLRScheduler::test_poly_lr, test/test_optim.py::TestLRScheduler::test_polynomial_lr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau1, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau2, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau3, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau4, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau_state_dict, test/test_optim.py::TestLRScheduler::test_sequentiallr2, test/test_optim.py::TestLRScheduler::test_sequentiallr3, test/test_optim.py::TestLRScheduler::test_sequentiallr4, test/test_optim.py::TestLRScheduler::test_step_lr_state_dict, test/test_optim.py::TestLRScheduler::test_swalr_hypers, test/test_optim.py::TestDifferentiableOptimizer::test_adadelta, test/test_optim.py::TestDifferentiableOptimizer::test_adam_differentiable_all_hyperparams, test/test_optim.py::TestDifferentiableOptimizer::test_adamax, test/test_optim.py::TestDifferentiableOptimizer::test_radam, test/test_optim.py::TestDifferentiableOptimizer::test_rprop, test/test_optim.py::TestSWAUtils::test_averaged_model_all_devices_ema_True, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_False_use_buffers_False, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_True_use_buffers_False, test/test_optim.py::TestSWAUtils::test_averaged_model_state_dict, test/test_optim.py::TestOptimRenewedCPU::test_adamw_serialization_cpu, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_ASGD_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_Adagrad_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_Adamax_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_LBFGS_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_RAdam_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_ASGD_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_Adadelta_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_Adagrad_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_NAdam_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_capturable_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_fused_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_defaults_changed_to_foreach_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_defaults_changed_to_foreach_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_defaults_changed_to_foreach_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_defaults_changed_to_foreach_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_errors_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_errors_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_errors_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_errors_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_errors_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_errors_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_foreach_large_tensor_ASGD_cpu_float16, test/test_optim.py::TestOptimRenewedCPU::test_foreach_large_tensor_RAdam_cpu_float16, test/test_optim.py::TestOptimRenewedCPU::test_foreach_matches_forloop_Adadelta_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_foreach_matches_forloop_Adafactor_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_foreach_matches_forloop_Adagrad_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_foreach_matches_forloop_NAdam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_foreach_matches_forloop_RAdam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_foreach_matches_forloop_RMSprop_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_foreach_matches_forloop_Rprop_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_False_with_lrsched_True_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_forloop_goes_right_direction_contiguous_True_with_lrsched_False_Rprop_cpu_float32, 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test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_SparseAdam_cpu_float32 2025-07-17T08:55:24.1919157Z 2025-07-17T08:55:27.3032551Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:55:27.3035227Z import pkg_resources 2025-07-17T08:55:27.4287084Z Running test_complex 1/1 ... [2025-07-17 08:55:27.428289] 2025-07-17T08:55:27.4287787Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:55:27.4290608Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_complex.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:55:27.428711] 2025-07-17T08:55:32.9076826Z 2025-07-17T08:55:32.9078288Z test_tensorexpr_pybind 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorexpr_pybind_1.1_649940ce23ebf889_.log 2025-07-17T08:55:32.9085737Z Running 17 items in this shard: test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_alloc_in_loop, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_call_raw, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_dtype_error, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_dynamic_shape, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_dynamic_shape_2d, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_external_calls, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_shape_prop, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_shape_prop_module, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_custom_lowering, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_expand, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_permute, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_scalar_inputs, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_t, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_tensor_inputs, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_transpose, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_simple_sum, test/test_tensorexpr_pybind.py::TestExprHandlePyBind::test_unary_ops 2025-07-17T08:55:32.9091812Z 2025-07-17T08:55:34.1535302Z 2025-07-17T08:55:34.1536670Z test_complex 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_complex_1.1_105f3be514f702b1_.log 2025-07-17T08:55:34.1543045Z Running 15 items in this shard: test/test_complex.py::TestComplexTensorCPU::test_all_cpu_complex128, test/test_complex.py::TestComplexTensorCPU::test_all_cpu_complex64, test/test_complex.py::TestComplexTensorCPU::test_any_cpu_complex128, test/test_complex.py::TestComplexTensorCPU::test_any_cpu_complex64, test/test_complex.py::TestComplexTensorCPU::test_conj_copy_cpu_complex128, test/test_complex.py::TestComplexTensorCPU::test_conj_copy_cpu_complex64, test/test_complex.py::TestComplexTensorCPU::test_dtype_inference_cpu_float16, test/test_complex.py::TestComplexTensorCPU::test_dtype_inference_cpu_float32, test/test_complex.py::TestComplexTensorCPU::test_dtype_inference_cpu_float64, test/test_complex.py::TestComplexTensorCPU::test_eq_cpu_complex128, test/test_complex.py::TestComplexTensorCPU::test_eq_cpu_complex64, test/test_complex.py::TestComplexTensorCPU::test_ne_cpu_complex128, test/test_complex.py::TestComplexTensorCPU::test_ne_cpu_complex64, test/test_complex.py::TestComplexTensorCPU::test_to_list_cpu_complex128, test/test_complex.py::TestComplexTensorCPU::test_to_list_cpu_complex64 2025-07-17T08:55:34.1548117Z 2025-07-17T08:55:36.1523963Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:55:36.1526863Z import pkg_resources 2025-07-17T08:55:36.2776593Z Running functorch/test_minifier 1/1 ... [2025-07-17 08:55:36.277266] 2025-07-17T08:55:36.2777418Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:55:36.2780240Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_minifier.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:55:36.277666] 2025-07-17T08:55:37.4393154Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:55:37.4396041Z import pkg_resources 2025-07-17T08:55:37.5673995Z Running test_ops_fwd_gradients 1/1 ... [2025-07-17 08:55:37.566983] 2025-07-17T08:55:37.5674565Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:55:37.5677680Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_fwd_gradients.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:55:37.567406] 2025-07-17T08:55:42.7521161Z 2025-07-17T08:55:42.7522469Z functorch/test_minifier 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_minifier_1.1_0695f820c3d6515f_.log 2025-07-17T08:55:42.7524639Z Running 5 items in this shard: test/functorch/test_minifier.py::TestMinifier::test_has_add_mul, test/functorch/test_minifier.py::TestMinifier::test_has_mul_minifier, test/functorch/test_minifier.py::TestMinifier::test_input_returned, test/functorch/test_minifier.py::TestMinifier::test_module, test/functorch/test_minifier.py::TestMinifier::test_tup_use 2025-07-17T08:55:42.7526249Z 2025-07-17T08:55:45.9228294Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:55:45.9231008Z import pkg_resources 2025-07-17T08:55:46.0488273Z Running dynamo/test_misc 1/1 ... [2025-07-17 08:55:46.048320] 2025-07-17T08:55:46.0488957Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:55:46.0490767Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_misc.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:55:46.048757] 2025-07-17T08:55:50.6865088Z 2025-07-17T08:55:50.6866466Z dynamo/test_misc 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_misc_1.1_4ca4c454a4457c6a_.log 2025-07-17T08:55:50.6867637Z 2025-07-17T08:55:53.3597762Z 2025-07-17T08:55:53.3599159Z test_ops_fwd_gradients 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_fwd_gradients_1.1_4d0bf77d7634c293_.log 2025-07-17T08:55:53.5031033Z Running 3189 items in this shard: test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_H_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_H_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_T_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_T_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___getitem___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___getitem___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___radd___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___radd___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rdiv___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rdiv___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rmatmul___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rmatmul___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rmod___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rmul___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rmul___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rpow___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rpow___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rsub___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rsub___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__batch_norm_with_update_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__chunk_cat_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__chunk_cat_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__native_batch_norm_legit_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__segment_reduce_lengths_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__segment_reduce_offsets_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__softmax_backward_data_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__unsafe_masked_index_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__unsafe_masked_index_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__unsafe_masked_index_put_accumulate_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad__upsample_bilinear2d_aa_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_abs_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_abs_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_acos_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_acos_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_acosh_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_acosh_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_add_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_add_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addbmm_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addbmm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addcdiv_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addcdiv_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addcmul_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addcmul_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addmm_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addmm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addmm_decomposed_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addmm_decomposed_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addmv_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addmv_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addr_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_addr_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_alias_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_alias_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_all_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_all_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_allclose_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_allclose_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_amax_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_amin_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_aminmax_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_angle_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_angle_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_any_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_any_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_arange_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_argmax_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_argmin_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_argsort_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_argwhere_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_argwhere_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_as_strided_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_as_strided_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_as_strided_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_as_strided_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_as_strided_partial_views_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_as_strided_partial_views_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_as_strided_scatter_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_as_strided_scatter_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_asin_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_asin_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_asinh_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_asinh_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_atan2_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_atan_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_atan_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_atanh_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_atanh_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_atleast_1d_cpu_complex128, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nan_to_num_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nanmean_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nanmedian_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nanquantile_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nansum_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_narrow_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_narrow_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_narrow_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_narrow_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_native_batch_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_native_dropout_backward_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_native_layer_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ne_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ne_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_neg_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_neg_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_empty_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_empty_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_empty_strided_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_empty_strided_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_full_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_full_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_ones_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_ones_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_zeros_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_zeros_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nextafter_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_avg_pool1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_avg_pool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_avg_pool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_max_pool1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_max_pool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_max_pool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_alpha_dropout_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_avg_pool1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_avg_pool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_avg_pool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_batch_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_bilinear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_binary_cross_entropy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_binary_cross_entropy_with_logits_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_celu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_channel_shuffle_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_channel_shuffle_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv1d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv2d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv3d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose1d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose2d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose3d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_cosine_embedding_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_cosine_similarity_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_cross_entropy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_ctc_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_dropout2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_dropout3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_dropout_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_elu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_embedding_bag_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_embedding_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_feature_alpha_dropout_with_train_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_feature_alpha_dropout_without_train_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_feature_alpha_dropout_without_train_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_fractional_max_pool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_fractional_max_pool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_gaussian_nll_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_gelu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_glu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_grid_sample_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_group_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_hardshrink_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_hardsigmoid_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_hardswish_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_hardtanh_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_hinge_embedding_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_huber_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_instance_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_area_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_bicubic_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_bilinear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_linear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_nearest-exact_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_nearest_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_trilinear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_kl_div_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_l1_loss_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_l1_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_layer_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_leaky_relu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_linear_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_linear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_local_response_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_logsigmoid_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_margin_ranking_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_pool1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_pool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_pool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool1d_grad_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool2d_grad_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool3d_grad_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_mish_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_mse_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_multi_head_attention_forward_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_multi_margin_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_multilabel_margin_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_multilabel_soft_margin_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_nll_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_normalize_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_normalize_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_circular_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_circular_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_constant_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_constant_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_reflect_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_reflect_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_replicate_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_replicate_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_replicate_negative_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_replicate_negative_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pairwise_distance_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pairwise_distance_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pdist_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pixel_shuffle_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pixel_shuffle_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pixel_unshuffle_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pixel_unshuffle_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_poisson_nll_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_prelu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_relu6_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_relu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_rms_norm_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_rms_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_rrelu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_scaled_dot_product_attention_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_selu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_silu_complex_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_silu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_smooth_l1_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_soft_margin_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softmin_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softmin_with_dtype_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softmin_with_dtype_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softplus_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softshrink_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softsign_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softsign_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_tanhshrink_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_tanhshrink_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_threshold_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_triplet_margin_loss_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_triplet_margin_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_triplet_margin_with_distance_loss_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_triplet_margin_with_distance_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_unfold_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_unfold_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_upsample_bilinear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_upsample_nearest_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nonzero_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nonzero_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nonzero_static_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nonzero_static_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_norm_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_norm_fro_cpu_complex128, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_modified_bessel_i1_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_modified_bessel_k0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_modified_bessel_k1_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_ndtr_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_ndtri_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_polygamma_special_polygamma_n_0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_scaled_modified_bessel_k0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_scaled_modified_bessel_k1_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_t_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_u_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_v_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_w_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_spherical_bessel_j0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_xlog1py_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_zeta_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_list_args_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_list_args_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_with_sizes_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_with_sizes_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_with_sizes_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_with_sizes_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sqrt_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sqrt_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_square_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_square_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_multiple_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_multiple_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_stack_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_stack_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_mean_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_mean_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_mean_unbiased_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_mean_unbiased_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_unbiased_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_unbiased_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_stft_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_stft_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sub_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sub_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sum_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sum_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sum_to_size_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sum_to_size_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_svd_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_svd_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_svd_lowrank_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_svd_lowrank_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_t_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_t_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_t_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_t_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_take_along_dim_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_take_along_dim_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_take_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_take_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tan_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tan_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tanh_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tanh_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tensor_split_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tensor_split_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tensordot_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tensordot_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tile_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tile_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_to_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_to_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_to_sparse_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_to_sparse_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_topk_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_torch_ops_aten__safe_softmax_default_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trace_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trace_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_transpose_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_transpose_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_transpose_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_transpose_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trapezoid_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trapezoid_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trapz_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trapz_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_triangular_solve_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_triangular_solve_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tril_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tril_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_triu_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_triu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_true_divide_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_true_divide_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trunc_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unbind_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unbind_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unbind_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unbind_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unflatten_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unflatten_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unfold_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unfold_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unfold_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unfold_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_uniform_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_uniform_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unique_consecutive_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unique_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsafe_chunk_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsafe_chunk_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsafe_split_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsafe_split_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsqueeze_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsqueeze_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsqueeze_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsqueeze_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_mean_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_mean_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_mean_unbiased_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_mean_unbiased_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_unbiased_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_unbiased_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vdot_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vdot_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_as_complex_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_as_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_as_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_as_real_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vsplit_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vsplit_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vstack_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vstack_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_where_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_where_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_xlogy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zero__cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zero__cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zeros_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zeros_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zeros_like_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zeros_like_cpu_float64 2025-07-17T08:55:53.6397975Z 2025-07-17T08:55:53.8491477Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:55:53.8493049Z import pkg_resources 2025-07-17T08:55:53.9751182Z Running torch_np/numpy_tests/core/test_einsum 1/1 ... [2025-07-17 08:55:53.974703] 2025-07-17T08:55:53.9752032Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:55:53.9754777Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_einsum.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:55:53.975128] 2025-07-17T08:55:56.5549622Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:55:56.5551190Z import pkg_resources 2025-07-17T08:55:56.6799473Z Running higher_order_ops/test_invoke_quant 1/1 ... [2025-07-17 08:55:56.679563] 2025-07-17T08:55:56.6800219Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:55:56.6802053Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'higher_order_ops/test_invoke_quant.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:55:56.679910] 2025-07-17T08:56:03.7550978Z 2025-07-17T08:56:03.7552799Z higher_order_ops/test_invoke_quant 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_invoke_quant_1.1_65b5eaecff2569ff_.log 2025-07-17T08:56:03.7559067Z Running 14 items in this shard: test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantEager::test_construct_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantEager::test_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantEager::test_multiple, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantEager::test_simple, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantAotEager::test_construct_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantAotEager::test_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantAotEager::test_multiple, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantAotEager::test_simple, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_construct_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_multiple, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_pattern_matching, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_prologue, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_simple 2025-07-17T08:56:03.7564538Z 2025-07-17T08:56:06.9357571Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:56:06.9360524Z import pkg_resources 2025-07-17T08:56:07.0620641Z Running cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 ... [2025-07-17 08:56:07.061640] 2025-07-17T08:56:07.0621739Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:56:07.0624569Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:56:07.062047] 2025-07-17T08:56:19.7952522Z 2025-07-17T08:56:19.7954570Z cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp_extensions.libtorch_agnostic_extension.test.test_libtorch_agnostic_1.1_f92cb15840c8d37c_.log 2025-07-17T08:56:19.7960970Z Running 9 items in this shard: test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_divide_neg_exp_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_exp_neg_is_leaf_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_identity_does_not_hog_memory_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_is_contiguous_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_abs_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_ones_like_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_transpose_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_neg_exp_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_slow_sgd_cpu 2025-07-17T08:56:19.7966550Z 2025-07-17T08:56:22.9828607Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:56:22.9831638Z import pkg_resources 2025-07-17T08:56:23.1112058Z Running test_stateless 1/1 ... [2025-07-17 08:56:23.110777] 2025-07-17T08:56:23.1112854Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:56:23.1114808Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_stateless.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:56:23.111153] 2025-07-17T08:56:34.4502732Z 2025-07-17T08:56:34.4504242Z torch_np/test_basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_basic_1.1_db2002e22fc43097_.log 2025-07-17T08:56:34.4802057Z Running 453 items in this shard: test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func0, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func1, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func10, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func11, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func12, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func13, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func14, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func15, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func16, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func17, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func18, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func19, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func2, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func20, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func21, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func22, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func23, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func24, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func25, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func26, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func27, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func28, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func29, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func3, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func30, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func31, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func32, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func33, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func34, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func35, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func36, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func37, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func38, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func39, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func4, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func40, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func41, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func42, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func43, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func44, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func45, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func46, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func47, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func48, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func49, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func5, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func50, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func51, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func52, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func53, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func54, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func55, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func56, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func57, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func58, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func59, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func6, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func60, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func61, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func62, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func63, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func64, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func65, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func66, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func67, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func68, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func69, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func7, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func70, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func71, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func72, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func73, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func74, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func8, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func9, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func0, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func1, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func10, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func11, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func12, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func13, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func14, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func15, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func16, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func17, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func18, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func19, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func2, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func20, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func21, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func22, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func23, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func24, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func25, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func26, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func27, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func28, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func29, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func3, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func30, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func31, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func32, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func33, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func34, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func35, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func36, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func37, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func38, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func39, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func4, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func40, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func41, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func42, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func43, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func44, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func45, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func46, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func47, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func48, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func49, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func5, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func50, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func51, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func52, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func53, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func54, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func55, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func56, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func57, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func58, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func59, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func6, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func60, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func61, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func62, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func63, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func64, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func65, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func66, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func67, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func68, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func69, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func7, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func70, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func71, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func72, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func73, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func74, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func8, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func9, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func0, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func1, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func10, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func11, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func12, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func13, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func14, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func15, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func16, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func17, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func18, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func19, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func2, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func20, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func21, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func22, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func23, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func24, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func25, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func26, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func27, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func28, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func29, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func3, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func30, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func31, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func32, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func33, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func34, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func35, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func36, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func37, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func38, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func39, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func4, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func40, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func41, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func42, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func43, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func44, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func45, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func46, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func47, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func48, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func49, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func5, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func50, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func51, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func52, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func53, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func54, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func55, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func56, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func57, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func58, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func59, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func6, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func60, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func61, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func62, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func63, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func64, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func65, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func66, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func67, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func68, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func69, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func7, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func70, test/torch_np/test_basic.py::TestOneArr::test_asarray_tensor_func71, 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test/torch_np/test_basic.py::TestCopyTo::test_copytobcast, test/torch_np/test_basic.py::TestDivmod::test_divmod_no_out, test/torch_np/test_basic.py::TestDivmod::test_divmod_out, test/torch_np/test_basic.py::TestDivmod::test_divmod_out_both_pos_and_kw, test/torch_np/test_basic.py::TestDivmod::test_divmod_out_list, test/torch_np/test_basic.py::TestDivmod::test_divmod_pos_only, test/torch_np/test_basic.py::TestSmokeNotImpl::test_nimpl_basic, test/torch_np/test_basic.py::TestDefaultDtype::test_defaultdtype_defaults, test/torch_np/test_basic.py::TestDefaultDtype::test_set_default_float_dt_float32, test/torch_np/test_basic.py::TestDefaultDtype::test_set_default_float_dt_pytorch, test/torch_np/test_basic.py::TestDefaultDtype::test_set_default_float_float32, test/torch_np/test_basic.py::TestExport::test_exported_objects, test/torch_np/test_basic.py::TestCtorNested::test_arrays_in_lists, test/torch_np/test_basic.py::TestMisc::test_f16_on_cuda, test/torch_np/test_basic.py::TestMisc::test_ndarrays_to_tensors 2025-07-17T08:56:34.5095749Z 2025-07-17T08:56:37.8341065Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:56:37.8342628Z import pkg_resources 2025-07-17T08:56:37.9616482Z Running profiler/test_profiler 1/1 ... [2025-07-17 08:56:37.961214] 2025-07-17T08:56:37.9617084Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:56:37.9619359Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_profiler.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:56:37.961615] 2025-07-17T08:56:57.3900946Z 2025-07-17T08:56:57.3902192Z test_stateless 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_stateless_1.1_a329522550c6a7ba_.log 2025-07-17T08:56:57.3926246Z Running 50 items in this shard: test/test_stateless.py::TestStatelessFunctionalAPI::test_circular_references_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_circular_references_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_batch_norm_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_batch_norm_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_member_reference_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_member_reference_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_multiple_dicts_error, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_tuple_dicts, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_data_parallel_error_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_data_parallel_error_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_data_parallel_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_data_parallel_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_gradient_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_gradient_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_jit_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_jit_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_kwargs_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_kwargs_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_in_place_operator_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_in_place_operator_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_module_fail_reset_to_original_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_module_fail_reset_to_original_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_some_weights_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_some_weights_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_special_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_special_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_strict_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_strict_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_some_weights_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_some_weights_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_weights_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_weights_strict_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_weights_strict_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_weights_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrized_module_change_parametrization_original_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrized_module_change_parametrization_original_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_setattr_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_setattr_strict_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_setattr_strict_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_setattr_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_tied_weights_errors_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_tied_weights_errors_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_tied_weights_no_error_without_flag, test/test_stateless.py::TestStatelessFunctionalAPI::test_tied_weights_warns_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_tied_weights_warns_torch_func, test/test_stateless.py::TestStatelessDeprecation::test_private_stateless_warns, test/test_stateless.py::TestStatelessDeprecation::test_stateless_functional_call_warns, test/test_stateless.py::TestPythonOptimizeMode::test_runs_with_optimize_flag 2025-07-17T08:56:57.3948702Z 2025-07-17T08:57:00.5933483Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:57:00.5936322Z import pkg_resources 2025-07-17T08:57:00.7210552Z Running nn/test_multihead_attention 1/1 ... [2025-07-17 08:57:00.720664] 2025-07-17T08:57:00.7211461Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:57:00.7214369Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_multihead_attention.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:57:00.721066] 2025-07-17T08:57:56.5912472Z 2025-07-17T08:57:56.5914388Z torch_np/numpy_tests/core/test_einsum 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_einsum_1.1_1c0951660e9c09dd_.log 2025-07-17T08:57:56.5949528Z Running 50 items in this shard: test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_broadcasting_dot_cases, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_collapse, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_combined_views_mapping, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_complex, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_different_paths_dtype_B, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_different_paths_dtype_D, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_different_paths_dtype_F, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_different_paths_dtype_b, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_different_paths_dtype_d, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_different_paths_dtype_e, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_different_paths_dtype_f, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_different_paths_dtype_h, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_different_paths_dtype_i, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_different_paths_dtype_l, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_edge_cases, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_all_contig_non_contig_output, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_broadcast, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_errors, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_failed_on_p9_and_s390x, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_fixed_collapsingbug, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_fixedstridebug, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_misc, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_sums_cfloat128, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_sums_cfloat64, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_sums_float16, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_sums_float32, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_sums_float64, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_sums_int16, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_sums_int32, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_sums_int64, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_sums_int8, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_sums_uint8, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_views, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_expand, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_hadamard_like_products, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_index_transformations, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_inner_product, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_out_is_res, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_output_order, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_random_cases, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_small_boolean_arrays, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_subscript_range, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsumPath::test_edge_paths, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsumPath::test_long_paths, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsumPath::test_memory_contraints, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsumPath::test_path_type_input, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsumPath::test_path_type_input_internal_trace, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsumPath::test_path_type_input_invalid, test/torch_np/numpy_tests/core/test_einsum.py::TestEinsumPath::test_spaces, test/torch_np/numpy_tests/core/test_einsum.py::TestMisc::test_overlap 2025-07-17T08:57:56.5983781Z 2025-07-17T08:57:59.8778006Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:57:59.8781263Z import pkg_resources 2025-07-17T08:58:00.0431290Z Running torch_np/numpy_tests/core/test_numeric 1/1 ... [2025-07-17 08:58:00.042722] 2025-07-17T08:58:00.0432245Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:58:00.0434595Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_numeric.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:58:00.043102] 2025-07-17T08:58:14.1892599Z 2025-07-17T08:58:14.1894097Z nn/test_multihead_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_multihead_attention_1.1_64b04a0d26548a2b_.log 2025-07-17T08:58:14.1906311Z Running 19 items in this shard: test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attention_average_attn_weights_False, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attention_average_attn_weights_True, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_3d_attn_mask, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_fast_path_invalid_shape, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_invalid_shape, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_nested_tensor_outside_fast_path, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_no_bias, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_batch_first_cpu_float16, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_batch_first_cpu_float32, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_batch_first_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_cpu_float16, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_cpu_float32, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_fast_path_query_and_bias_have_different_dtypes_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_fast_path_small_test_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_in_proj_bias_none_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_in_proj_weight_none_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_self_attn_two_masks_fast_path_cpu, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_self_attn_two_masks_fast_path_mock_cpu 2025-07-17T08:58:14.1917822Z 2025-07-17T08:58:15.6730478Z Uploading artifacts took 1.48 seconds 2025-07-17T08:58:17.3405617Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:58:17.3407258Z import pkg_resources 2025-07-17T08:58:17.4657549Z Running xpu/test_conv 1/1 ... [2025-07-17 08:58:17.465402] 2025-07-17T08:58:17.4657979Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:58:17.4661144Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'xpu/test_conv.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:58:17.465776] 2025-07-17T08:58:21.2249294Z 2025-07-17T08:58:21.2250439Z xpu/test_conv 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_conv_1.1_e36470703730b0f3_.log 2025-07-17T08:58:21.2251561Z Running 0 items in this shard: 2025-07-17T08:58:21.2251852Z 2025-07-17T08:58:24.4789645Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:58:24.4792625Z import pkg_resources 2025-07-17T08:58:24.6049925Z Running test_weak 1/1 ... [2025-07-17 08:58:24.604600] 2025-07-17T08:58:24.6050639Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:58:24.6053403Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_weak.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:58:24.604988] 2025-07-17T08:58:31.2318778Z 2025-07-17T08:58:31.2320279Z profiler/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_profiler_1.1_0211dba63cab6a09_.log 2025-07-17T08:58:31.2346310Z Running 70 items in this shard: test/profiler/test_profiler.py::TestProfilerCUDA::test_cudagraph_profiling_workaround, test/profiler/test_profiler.py::TestProfilerCUDA::test_custom_module_input_op_ids, test/profiler/test_profiler.py::TestProfilerCUDA::test_mem_leak, test/profiler/test_profiler.py::TestProfilerITT::test_custom_module_input_op_ids, test/profiler/test_profiler.py::TestProfiler::test_basic_chrome_trace, test/profiler/test_profiler.py::TestProfiler::test_basic_profile, test/profiler/test_profiler.py::TestProfiler::test_concrete_inputs_profiling, test/profiler/test_profiler.py::TestProfiler::test_concrete_inputs_profiling_toggling, test/profiler/test_profiler.py::TestProfiler::test_cpu_annotation_overlap, test/profiler/test_profiler.py::TestProfiler::test_disable_external_correlation, test/profiler/test_profiler.py::TestProfiler::test_dynamic_toggle, test/profiler/test_profiler.py::TestProfiler::test_event_list, test/profiler/test_profiler.py::TestProfiler::test_export_stacks, test/profiler/test_profiler.py::TestProfiler::test_flops, test/profiler/test_profiler.py::TestProfiler::test_forked_process, test/profiler/test_profiler.py::TestProfiler::test_guarded_record_function_fast, test/profiler/test_profiler.py::TestProfiler::test_high_level_trace, test/profiler/test_profiler.py::TestProfiler::test_is_profiler_enabled, test/profiler/test_profiler.py::TestProfiler::test_kineto, test/profiler/test_profiler.py::TestProfiler::test_kineto_multigpu, test/profiler/test_profiler.py::TestProfiler::test_kineto_profiler_api, test/profiler/test_profiler.py::TestProfiler::test_kineto_profiler_multiple_steppers, test/profiler/test_profiler.py::TestProfiler::test_kineto_profiler_with_environment_variable, test/profiler/test_profiler.py::TestProfiler::test_lazy_build_tree, test/profiler/test_profiler.py::TestProfiler::test_memory_profiler, test/profiler/test_profiler.py::TestProfiler::test_module_hierarchy, test/profiler/test_profiler.py::TestProfiler::test_nested_tensor_with_shapes, test/profiler/test_profiler.py::TestProfiler::test_oom_tracing, test/profiler/test_profiler.py::TestProfiler::test_override_time_units, test/profiler/test_profiler.py::TestProfiler::test_profile_all_threads, test/profiler/test_profiler.py::TestProfiler::test_profiler_correlation_id, test/profiler/test_profiler.py::TestProfiler::test_profiler_cuda_sync_events, test/profiler/test_profiler.py::TestProfiler::test_profiler_disable_fwd_bwd_link, test/profiler/test_profiler.py::TestProfiler::test_profiler_fwd_bwd_link, test/profiler/test_profiler.py::TestProfiler::test_profiler_metadata, test/profiler/test_profiler.py::TestProfiler::test_profiler_op_event_args, test/profiler/test_profiler.py::TestProfiler::test_profiler_op_event_kwargs, test/profiler/test_profiler.py::TestProfiler::test_profiler_strides, test/profiler/test_profiler.py::TestProfiler::test_profiler_time_scale, test/profiler/test_profiler.py::TestProfiler::test_profiler_tracing, test/profiler/test_profiler.py::TestProfiler::test_profiler_type, test/profiler/test_profiler.py::TestProfiler::test_record_function_fast, test/profiler/test_profiler.py::TestProfiler::test_schedule_function_count, test/profiler/test_profiler.py::TestProfiler::test_skip_first_wait, test/profiler/test_profiler.py::TestProfiler::test_source, test/profiler/test_profiler.py::TestProfiler::test_tensorboard_trace_handler, test/profiler/test_profiler.py::TestProfiler::test_user_annotation, test/profiler/test_profiler.py::TestExperimentalUtils::test_bfs, test/profiler/test_profiler.py::TestExperimentalUtils::test_dfs, test/profiler/test_profiler.py::TestExperimentalUtils::test_fuzz_symbolize, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_conv2d_bias_followed_by_batchnorm2d_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_debug_autotuner, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_extra_cuda_copy_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_extra_cuda_copy_pattern_benchmark, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_for_loop_indexing_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_fp32_matmul_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_grad_not_set_to_none_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_matmul_dim_fp16_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_name_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_optimizer_single_tensor_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_overload_names, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_pattern_match_helper, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_pattern_matcher_json_report, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_synchronized_dataloader_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_compute_idle_time, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_compute_queue_depth, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_compute_queue_depth_when_no_cuda_events, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_compute_self_time, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_get_optimizable_events, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_intervals_overlap 2025-07-17T08:58:31.2370979Z 2025-07-17T08:58:34.4331139Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:58:34.4332837Z import pkg_resources 2025-07-17T08:58:34.5593157Z Running dynamo/test_graph_deduplication 1/1 ... [2025-07-17 08:58:34.558903] 2025-07-17T08:58:34.5594082Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:58:34.5596244Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_graph_deduplication.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:58:34.559283] 2025-07-17T08:58:38.0062151Z 2025-07-17T08:58:38.0063711Z dynamo/test_graph_deduplication 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_graph_deduplication_1.1_cd603241b8390dfc_.log 2025-07-17T08:58:38.0065154Z 2025-07-17T08:58:41.3253563Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:58:41.4507485Z import pkg_resources 2025-07-17T08:58:41.4508252Z Running distributions/test_constraints 1/1 ... [2025-07-17 08:58:41.450314] 2025-07-17T08:58:41.4509026Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:58:41.4511100Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'distributions/test_constraints.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:58:41.450741] 2025-07-17T08:58:42.3989815Z 2025-07-17T08:58:42.3992223Z test_weak 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_weak_1.1_78287a13d05c4a23_.log 2025-07-17T08:58:42.4003737Z Running 39 items in this shard: test/test_weak.py::WeakTest::test_make_weak_keyed_dict_from_dict, test/test_weak.py::WeakTest::test_make_weak_keyed_dict_from_weak_keyed_dict, test/test_weak.py::WeakTest::test_make_weak_keyed_dict_repr, test/test_weak.py::WeakTest::test_threaded_weak_key_dict_copy, test/test_weak.py::WeakTest::test_threaded_weak_key_dict_deepcopy, test/test_weak.py::WeakTest::test_weak_keyed_bad_delitem, test/test_weak.py::WeakTest::test_weak_keyed_delitem, test/test_weak.py::WeakTest::test_weak_keyed_dict_popitem, test/test_weak.py::WeakTest::test_weak_keyed_dict_setdefault, test/test_weak.py::WeakTest::test_weak_keyed_dict_update, test/test_weak.py::WeakTest::test_weak_keyed_union_operators, test/test_weak.py::WeakKeyDictionaryTestCase::test_bool, test/test_weak.py::WeakKeyDictionaryTestCase::test_constructor, test/test_weak.py::WeakKeyDictionaryTestCase::test_get, test/test_weak.py::WeakKeyDictionaryTestCase::test_getitem, test/test_weak.py::WeakKeyDictionaryTestCase::test_items, test/test_weak.py::WeakKeyDictionaryTestCase::test_keys, test/test_weak.py::WeakKeyDictionaryTestCase::test_len, test/test_weak.py::WeakKeyDictionaryTestCase::test_pop, test/test_weak.py::WeakKeyDictionaryTestCase::test_popitem, test/test_weak.py::WeakKeyDictionaryTestCase::test_read, test/test_weak.py::WeakKeyDictionaryTestCase::test_setdefault, test/test_weak.py::WeakKeyDictionaryTestCase::test_update, test/test_weak.py::WeakKeyDictionaryTestCase::test_values, test/test_weak.py::WeakKeyDictionaryTestCase::test_write, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_bool, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_constructor, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_get, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_getitem, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_items, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_keys, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_len, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_pop, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_popitem, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_read, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_setdefault, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_update, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_values, test/test_weak.py::WeakKeyDictionaryScriptObjectTestCase::test_write 2025-07-17T08:58:42.4015028Z 2025-07-17T08:58:45.1709167Z 2025-07-17T08:58:45.1711336Z distributions/test_constraints 1/1 was successful, full logs can be found in artifacts with path test/test-reports/distributions.test_constraints_1.1_0ccd6bbe8b778e00_.log 2025-07-17T08:58:45.1765743Z Running 136 items in this shard: test/distributions/test_constraints.py::test_constraint[False-constraint_fn0-False-value0], test/distributions/test_constraints.py::test_constraint[False-constraint_fn1-False-value1], test/distributions/test_constraints.py::test_constraint[False-constraint_fn2-False-value2], test/distributions/test_constraints.py::test_constraint[False-constraint_fn3-True-value3], test/distributions/test_constraints.py::test_constraint[False-constraint_fn4-False-value4], test/distributions/test_constraints.py::test_constraint[False-constraint_fn5-False-value5], test/distributions/test_constraints.py::test_constraint[False-constraint_fn6-True-value6], test/distributions/test_constraints.py::test_constraint[False-constraint_fn7-True-value7], test/distributions/test_constraints.py::test_constraint[False-constraint_fn8-False-value8], test/distributions/test_constraints.py::test_constraint[False-constraint_fn9-True-value9], test/distributions/test_constraints.py::test_constraint[False-constraint_fn10-False-value10], test/distributions/test_constraints.py::test_constraint[False-constraint_fn11-False-value11], test/distributions/test_constraints.py::test_constraint[False-constraint_fn12-True-value12], test/distributions/test_constraints.py::test_constraint[False-constraint_fn13-True-value13], test/distributions/test_constraints.py::test_constraint[False-constraint_fn14-False-value14], test/distributions/test_constraints.py::test_constraint[False-constraint_fn15-True-value15], test/distributions/test_constraints.py::test_constraint[False-constraint_fn16-True-value16], test/distributions/test_constraints.py::test_constraint[False-constraint_fn17-True-value17], test/distributions/test_constraints.py::test_constraint[True-constraint_fn0-False-value0], test/distributions/test_constraints.py::test_constraint[True-constraint_fn1-False-value1], test/distributions/test_constraints.py::test_constraint[True-constraint_fn2-False-value2], test/distributions/test_constraints.py::test_constraint[True-constraint_fn3-True-value3], test/distributions/test_constraints.py::test_constraint[True-constraint_fn4-False-value4], test/distributions/test_constraints.py::test_constraint[True-constraint_fn5-False-value5], test/distributions/test_constraints.py::test_constraint[True-constraint_fn6-True-value6], test/distributions/test_constraints.py::test_constraint[True-constraint_fn7-True-value7], test/distributions/test_constraints.py::test_constraint[True-constraint_fn8-False-value8], test/distributions/test_constraints.py::test_constraint[True-constraint_fn9-True-value9], test/distributions/test_constraints.py::test_constraint[True-constraint_fn10-False-value10], test/distributions/test_constraints.py::test_constraint[True-constraint_fn11-False-value11], test/distributions/test_constraints.py::test_constraint[True-constraint_fn12-True-value12], test/distributions/test_constraints.py::test_constraint[True-constraint_fn13-True-value13], test/distributions/test_constraints.py::test_constraint[True-constraint_fn14-False-value14], test/distributions/test_constraints.py::test_constraint[True-constraint_fn15-True-value15], test/distributions/test_constraints.py::test_constraint[True-constraint_fn16-True-value16], test/distributions/test_constraints.py::test_constraint[True-constraint_fn17-True-value17], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn0-args0], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn1-args1], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn2-args2], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThan-args3], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThan-args4], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThan-args5], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThan-args6], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThanEq-args7], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThanEq-args8], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThanEq-args9], test/distributions/test_constraints.py::test_biject_to[False-_LessThan-args10], test/distributions/test_constraints.py::test_biject_to[False-_LessThan-args11], test/distributions/test_constraints.py::test_biject_to[False-_LessThan-args12], test/distributions/test_constraints.py::test_biject_to[False-_LessThan-args13], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn14-args14], test/distributions/test_constraints.py::test_biject_to[False-_Interval-args15], test/distributions/test_constraints.py::test_biject_to[False-_Interval-args16], test/distributions/test_constraints.py::test_biject_to[False-_Interval-args17], test/distributions/test_constraints.py::test_biject_to[False-_HalfOpenInterval-args18], test/distributions/test_constraints.py::test_biject_to[False-_HalfOpenInterval-args19], test/distributions/test_constraints.py::test_biject_to[False-_HalfOpenInterval-args20], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn21-args21], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn22-args22], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn23-args23], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn24-args24], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn0-args0], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn1-args1], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn2-args2], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThan-args3], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThan-args4], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThan-args5], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThan-args6], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThanEq-args7], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThanEq-args8], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThanEq-args9], test/distributions/test_constraints.py::test_biject_to[True-_LessThan-args10], test/distributions/test_constraints.py::test_biject_to[True-_LessThan-args11], test/distributions/test_constraints.py::test_biject_to[True-_LessThan-args12], test/distributions/test_constraints.py::test_biject_to[True-_LessThan-args13], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn14-args14], test/distributions/test_constraints.py::test_biject_to[True-_Interval-args15], test/distributions/test_constraints.py::test_biject_to[True-_Interval-args16], test/distributions/test_constraints.py::test_biject_to[True-_Interval-args17], test/distributions/test_constraints.py::test_biject_to[True-_HalfOpenInterval-args18], test/distributions/test_constraints.py::test_biject_to[True-_HalfOpenInterval-args19], test/distributions/test_constraints.py::test_biject_to[True-_HalfOpenInterval-args20], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn21-args21], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn22-args22], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn23-args23], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn24-args24], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn0-args0], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn1-args1], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn2-args2], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThan-args3], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThan-args4], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThan-args5], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThan-args6], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThanEq-args7], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThanEq-args8], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThanEq-args9], test/distributions/test_constraints.py::test_transform_to[False-_LessThan-args10], test/distributions/test_constraints.py::test_transform_to[False-_LessThan-args11], test/distributions/test_constraints.py::test_transform_to[False-_LessThan-args12], test/distributions/test_constraints.py::test_transform_to[False-_LessThan-args13], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn14-args14], test/distributions/test_constraints.py::test_transform_to[False-_Interval-args15], test/distributions/test_constraints.py::test_transform_to[False-_Interval-args16], test/distributions/test_constraints.py::test_transform_to[False-_Interval-args17], test/distributions/test_constraints.py::test_transform_to[False-_HalfOpenInterval-args18], test/distributions/test_constraints.py::test_transform_to[False-_HalfOpenInterval-args19], test/distributions/test_constraints.py::test_transform_to[False-_HalfOpenInterval-args20], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn21-args21], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn22-args22], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn23-args23], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn24-args24], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn0-args0], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn1-args1], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn2-args2], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThan-args3], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThan-args4], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThan-args5], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThan-args6], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThanEq-args7], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThanEq-args8], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThanEq-args9], test/distributions/test_constraints.py::test_transform_to[True-_LessThan-args10], test/distributions/test_constraints.py::test_transform_to[True-_LessThan-args11], test/distributions/test_constraints.py::test_transform_to[True-_LessThan-args12], test/distributions/test_constraints.py::test_transform_to[True-_LessThan-args13], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn14-args14], test/distributions/test_constraints.py::test_transform_to[True-_Interval-args15], test/distributions/test_constraints.py::test_transform_to[True-_Interval-args16], test/distributions/test_constraints.py::test_transform_to[True-_Interval-args17], test/distributions/test_constraints.py::test_transform_to[True-_HalfOpenInterval-args18], test/distributions/test_constraints.py::test_transform_to[True-_HalfOpenInterval-args19], test/distributions/test_constraints.py::test_transform_to[True-_HalfOpenInterval-args20], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn21-args21], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn22-args22], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn23-args23], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn24-args24] 2025-07-17T08:58:45.1818481Z 2025-07-17T08:58:45.6600308Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:58:45.6603604Z import pkg_resources 2025-07-17T08:58:45.7893245Z Running test_tensorboard 1/1 ... [2025-07-17 08:58:45.788860] 2025-07-17T08:58:45.7894545Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:58:45.7897140Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensorboard.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:58:45.789256] 2025-07-17T08:58:48.4480968Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:58:48.4484254Z import pkg_resources 2025-07-17T08:58:48.5730186Z Running profiler/test_cpp_thread 1/1 ... [2025-07-17 08:58:48.572564] 2025-07-17T08:58:48.5731070Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:58:48.5734109Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_cpp_thread.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:58:48.572982] 2025-07-17T08:58:53.4463211Z 2025-07-17T08:58:53.4464756Z profiler/test_cpp_thread 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_cpp_thread_1.1_36422407796e60c4_.log 2025-07-17T08:58:53.4471103Z Running 6 items in this shard: test/profiler/test_cpp_thread.py::CppThreadTestCUDA::test_profile_memory_cuda, test/profiler/test_cpp_thread.py::CppThreadTestCUDA::test_with_enable_profiler_in_child_thread_cuda, test/profiler/test_cpp_thread.py::CppThreadTestCUDA::test_without_enable_profiler_in_child_thread_cuda, test/profiler/test_cpp_thread.py::CppThreadTestXPU::test_profile_memory_xpu, test/profiler/test_cpp_thread.py::CppThreadTestXPU::test_with_enable_profiler_in_child_thread_xpu, test/profiler/test_cpp_thread.py::CppThreadTestXPU::test_without_enable_profiler_in_child_thread_xpu 2025-07-17T08:58:53.4476116Z 2025-07-17T08:58:56.6974922Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:58:56.6977415Z import pkg_resources 2025-07-17T08:58:56.8240804Z Running dynamo/test_decorators 1/1 ... [2025-07-17 08:58:56.823642] 2025-07-17T08:58:56.8241748Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:58:56.8244214Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_decorators.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:58:56.824046] 2025-07-17T08:59:00.2476510Z 2025-07-17T08:59:00.2478384Z dynamo/test_decorators 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_decorators_1.1_3e34aca28c044f4b_.log 2025-07-17T08:59:00.2480696Z 2025-07-17T08:59:03.5823804Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:59:03.5826875Z import pkg_resources 2025-07-17T08:59:03.7082393Z Running functorch/test_ac_knapsack 1/1 ... [2025-07-17 08:59:03.707781] 2025-07-17T08:59:03.7083588Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:59:03.7085138Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ac_knapsack.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:59:03.708156] 2025-07-17T08:59:09.5320192Z 2025-07-17T08:59:09.5322086Z functorch/test_ac_knapsack 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ac_knapsack_1.1_5b275c8d89d6f439_.log 2025-07-17T08:59:09.5329974Z Running 15 items in this shard: test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_full_joint_nx_graph, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_get_knapsack_memory_input, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_get_knapsack_runtime_input, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_get_non_ac_peak_memory, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_get_theoretical_max_runtime, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_inialize_from_graph, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_recomputable_node_only_graph, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_recomputable_node_only_graph_with_larger_graph_context, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_simplified_fx_joint_graph, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_evaluate_distribution_of_results_for_knapsack_algo, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_evaluate_knapsack_output_accounting_for_backward_pass, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_evaluate_knapsack_output_not_accounting_for_backward_pass, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_evaluate_knapsack_output_with_wrong_sized_values, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_get_backward_memory_from_topologically_sorted_graph, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_get_knee_point_memory_budget 2025-07-17T08:59:09.5337279Z 2025-07-17T08:59:13.0988113Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:59:13.0991356Z import pkg_resources 2025-07-17T08:59:13.2267262Z Running dynamo/test_base_hop 1/1 ... [2025-07-17 08:59:13.226153] 2025-07-17T08:59:13.2268218Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:59:13.2273505Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_base_hop.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:59:13.226583] 2025-07-17T08:59:15.9512646Z 2025-07-17T08:59:15.9514713Z torch_np/numpy_tests/core/test_numeric 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_numeric_1.1_0316809d8eac04f1_.log 2025-07-17T08:59:15.9625445Z Running 275 items in this shard: test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_copies, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_negative_resize, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_repeats, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_reshape_from_zero, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_zeroresize, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_choose, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_clip, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_compress, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_count_nonzero, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_cumproduct, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_diagonal, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_accuracy, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype2, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype3, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype4, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype5, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype6, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype7, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_edgecases_val_2147483647_ndigits_-1, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_edgecases_val_2147483647_ndigits_-10, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_edgecases_val_2147483647_ndigits_-9, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_mean, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_prod, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_ptp, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_ravel, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_repeat, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_reshape, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_round, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_round_2, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_round_py_consistency, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_searchsorted, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_size, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_squeeze, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_std, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_sum, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_swapaxes, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_take, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_trace, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_transpose, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_var, test/torch_np/numpy_tests/core/test_numeric.py::TestIsscalar::test_isscalar, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_and_eq, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_and_is, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_or_eq, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_or_is, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_xor_eq, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_xor_is, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_logical, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolArray::test_all_any, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolArray::test_logical_and_or_xor, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolArray::test_logical_not_abs, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolCmp::test_double, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolCmp::test_float, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_default, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_divide_err, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_errobj, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_set, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_D, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_F, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_G, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_d, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_e, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_f, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_g, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_warnings, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_can_cast, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_can_cast_2, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_can_cast_values, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_coercion, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_coercion_2, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_promote_types_endian, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_result_type, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_tesult_type_2, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_2592_dtype0_count_10_error_index_5, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_2592_dtype0_count_10_error_index_9, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_empty_result, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_failed_itemsetting, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_lengths, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_too_few_items, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_types, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_values, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_?, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_B, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_D, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_F, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_b, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_d, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_e, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_f, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_h, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_i, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_l, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_list, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_countnonzero_axis_empty, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_countnonzero_keepdims, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_onedim, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_onedim_differs, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_trivial, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_trivial_differs, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_twodim, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_zerod, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_zerod_differs, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_sparse, test/torch_np/numpy_tests/core/test_numeric.py::TestIndex::test_boolean, test/torch_np/numpy_tests/core/test_numeric.py::TestIndex::test_boolean_edgecase, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_large_neg_int64, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_neg_width_boundaries, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_negative, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_positive, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_sufficient_width, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_zero, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_base3, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_base_range, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_negative, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_positive, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_array_equal, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_array_equal_equal_nan, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_array_equiv, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_none_compares_elementwise, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_array_double, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_complex, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_func_takes_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_inplace_array, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_inplace_simple, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_nan, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_non_contig, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_property, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_scalar_nan_propagation_arr0_amin0_amax0, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_value_min_max_flip_amin2_amax2, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_value_min_max_flip_amin_1_amax1, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_value_min_max_flip_amin_1_amax_0, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_array_int32, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_array_outint32, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_memory_overlap, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_simple, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_simple2, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_simple_int32, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_transposed, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_noncontig_inplace, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_2_dtype_D, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_2_dtype_F, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_2_dtype_e, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_?, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_B, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_b, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_d, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_f, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_h, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_i, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_l, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_complex, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_double, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_inplace_01, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_inplace_02, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int32_inout_casting0, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int32_inout_casting_unsafe, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int32_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int64_inout, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int64_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_nonnative, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_01, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_02, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_03, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_04, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_05, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_06, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_07, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_08, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_09, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_10, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_11, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_12, test/torch_np/numpy_tests/core/test_numeric.py::TestAllclose::test_equalnan, test/torch_np/numpy_tests/core/test_numeric.py::TestAllclose::test_ip_allclose, test/torch_np/numpy_tests/core/test_numeric.py::TestAllclose::test_ip_not_allclose, test/torch_np/numpy_tests/core/test_numeric.py::TestAllclose::test_min_int, test/torch_np/numpy_tests/core/test_numeric.py::TestAllclose::test_no_parameter_modification, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_equal_nan, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_ip_all_isclose, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_ip_isclose, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_ip_isclose_allclose, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_ip_none_isclose, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_no_parameter_modification, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_non_finite_scalar, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_scalar_return, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_basic, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_ddof1, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_ddof2, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_out_scalar, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_scalars, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVarComplex::test_basic, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVarComplex::test_scalars, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_empty, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_for_reference_leak, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_full, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_ones, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_zeros, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc0_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc0_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc1_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc1_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc2_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc2_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc3_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc3_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_empty_like, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_filled_like, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_ones_like, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_zeros_like, test/torch_np/numpy_tests/core/test_numeric.py::TestCorrelate::test_complex, test/torch_np/numpy_tests/core/test_numeric.py::TestCorrelate::test_float, test/torch_np/numpy_tests/core/test_numeric.py::TestCorrelate::test_mode, test/torch_np/numpy_tests/core/test_numeric.py::TestCorrelate::test_no_overwrite, test/torch_np/numpy_tests/core/test_numeric.py::TestCorrelate::test_zero_size, test/torch_np/numpy_tests/core/test_numeric.py::TestConvolve::test_mode, test/torch_np/numpy_tests/core/test_numeric.py::TestConvolve::test_no_overwrite, test/torch_np/numpy_tests/core/test_numeric.py::TestConvolve::test_numpy_doc_examples, test/torch_np/numpy_tests/core/test_numeric.py::TestConvolve::test_object, test/torch_np/numpy_tests/core/test_numeric.py::TestDtypePositional::test_dtype_positional, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_2D, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_list, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_nd_nd_0, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_nd_nd_1, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_nd_nd_2, test/torch_np/numpy_tests/core/test_numeric.py::TestStringFunction::test_set_string_function, test/torch_np/numpy_tests/core/test_numeric.py::TestRoll::test_roll1d, test/torch_np/numpy_tests/core/test_numeric.py::TestRoll::test_roll2d, test/torch_np/numpy_tests/core/test_numeric.py::TestRoll::test_roll_empty, test/torch_np/numpy_tests/core/test_numeric.py::TestRollaxis::test_exceptions, test/torch_np/numpy_tests/core/test_numeric.py::TestRollaxis::test_results, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_errors, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_move_multiples, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_move_new_position, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_move_to_end, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_preserve_order, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_2x2, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_2x3, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_3x3, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_broadcasting, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_broadcasting_shapes, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_uint8_int32_mixed_dtypes, test/torch_np/numpy_tests/core/test_numeric.py::TestOuterMisc::test_outer_out_param, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype0_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype0_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype0_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype1_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype1_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype1_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype2_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype2_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype2_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype3_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype3_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype3_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_scalar_input, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_simple, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_single_input, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_sparse, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_C_and_F_simul, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_non_array_input, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_require_each, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_unknown_requirement, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_broadcast_error_kwargs, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_broadcast_in_args, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_broadcast_single_arg, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_number_of_arguments, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_shape_mismatch_error_message, test/torch_np/numpy_tests/core/test_numeric.py::TestTensordot::test_zero_dimension, test/torch_np/numpy_tests/core/test_numeric.py::TestTensordot::test_zero_dimension_einsum, test/torch_np/numpy_tests/core/test_numeric.py::TestTensordot::test_zero_dimensional 2025-07-17T08:59:15.9727120Z 2025-07-17T08:59:20.1506924Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:59:20.1510445Z import pkg_resources 2025-07-17T08:59:20.3157880Z Running dynamo/test_sources 1/1 ... [2025-07-17 08:59:20.315390] 2025-07-17T08:59:20.3158523Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:59:20.3161044Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sources.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:59:20.315809] 2025-07-17T08:59:21.2874795Z 2025-07-17T08:59:21.2876365Z dynamo/test_base_hop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_base_hop_1.1_d7ee0540c7157a32_.log 2025-07-17T08:59:21.2877407Z 2025-07-17T08:59:23.7334529Z 2025-07-17T08:59:23.7336340Z dynamo/test_sources 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sources_1.1_b66d35d0ea0522cc_.log 2025-07-17T08:59:23.7339417Z 2025-07-17T08:59:25.3122826Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:59:25.3126391Z import pkg_resources 2025-07-17T08:59:25.4371449Z Running test_datapipe 1/1 ... [2025-07-17 08:59:25.436714] 2025-07-17T08:59:25.4372284Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:59:25.4377296Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_datapipe.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:59:25.437185] 2025-07-17T08:59:27.7868885Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:59:27.7871006Z import pkg_resources 2025-07-17T08:59:27.9408221Z Running functorch/test_logging 1/1 ... [2025-07-17 08:59:27.940437] 2025-07-17T08:59:27.9409190Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:59:27.9412198Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_logging.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:59:27.940849] 2025-07-17T08:59:33.7663801Z 2025-07-17T08:59:33.7665730Z functorch/test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_logging_1.1_c2075b8f8c21576c_.log 2025-07-17T08:59:33.7668765Z Running 1 items in this shard: test/functorch/test_logging.py::TestAOTLogging::test_logging 2025-07-17T08:59:33.7670197Z 2025-07-17T08:59:37.2420291Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:59:37.2423321Z import pkg_resources 2025-07-17T08:59:37.3716567Z Running torch_np/test_indexing 1/1 ... [2025-07-17 08:59:37.371210] 2025-07-17T08:59:37.3717562Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:59:37.3720185Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_indexing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:59:37.371645] 2025-07-17T08:59:39.2075971Z 2025-07-17T08:59:39.2077363Z test_tensorboard 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorboard_1.1_c57495ce7c132234_.log 2025-07-17T08:59:39.2096833Z Running 50 items in this shard: test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_autograd_np, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_histogram, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_histogram_raw, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_np, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_write, test/test_tensorboard.py::TestTensorBoardUtils::test_convert_to_HWC_dtype_remains_same, test/test_tensorboard.py::TestTensorBoardUtils::test_numpy_vid_uint8, test/test_tensorboard.py::TestTensorBoardUtils::test_prepare_video, test/test_tensorboard.py::TestTensorBoardUtils::test_to_HWC, test/test_tensorboard.py::TestTensorBoardWriter::test_writer, test/test_tensorboard.py::TestTensorBoardSummaryWriter::test_pathlib, test/test_tensorboard.py::TestTensorBoardSummaryWriter::test_summary_writer_close, test/test_tensorboard.py::TestTensorBoardSummaryWriter::test_summary_writer_ctx, test/test_tensorboard.py::TestTensorBoardEmbedding::test_embedding, test/test_tensorboard.py::TestTensorBoardEmbedding::test_embedding_64, test/test_tensorboard.py::TestTensorBoardSummary::test_audio, test/test_tensorboard.py::TestTensorBoardSummary::test_custom_scalars, test/test_tensorboard.py::TestTensorBoardSummary::test_empty_input, test/test_tensorboard.py::TestTensorBoardSummary::test_float32_image, test/test_tensorboard.py::TestTensorBoardSummary::test_histogram_auto, test/test_tensorboard.py::TestTensorBoardSummary::test_histogram_doane, test/test_tensorboard.py::TestTensorBoardSummary::test_histogram_fd, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_3_channel_batched, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_boxes, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_one_channel, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_one_channel_batched, test/test_tensorboard.py::TestTensorBoardSummary::test_image_without_channel, test/test_tensorboard.py::TestTensorBoardSummary::test_list_input, test/test_tensorboard.py::TestTensorBoardSummary::test_mesh, test/test_tensorboard.py::TestTensorBoardSummary::test_scalar_new_style, test/test_tensorboard.py::TestTensorBoardSummary::test_text, test/test_tensorboard.py::TestTensorBoardSummary::test_uint8_image, test/test_tensorboard.py::TestTensorBoardSummary::test_video, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_mlp_graph, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_nested_nn_squential, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_pytorch_graph, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_pytorch_graph_dict_input, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_torchvision_smoke, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_wrong_input_size, test/test_tensorboard.py::TestTensorBoardFigure::test_figure, test/test_tensorboard.py::TestTensorBoardFigure::test_figure_list, test/test_tensorboard.py::TestTensorBoardNumpy::test_pytorch_np_expect_fail, test/test_tensorboard.py::TestTensorBoardNumpy::test_scalar, test/test_tensorboard.py::TestTensorProtoSummary::test_complex_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_empty_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_float_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_half_tensor_proto_bfloat16_proto_type_14, test/test_tensorboard.py::TestTensorProtoSummary::test_half_tensor_proto_float16_proto_type_19, test/test_tensorboard.py::TestTensorProtoSummary::test_int_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_scalar_tensor_proto 2025-07-17T08:59:39.2114962Z 2025-07-17T08:59:42.6476011Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:59:42.6479060Z import pkg_resources 2025-07-17T08:59:42.7750267Z Running dynamo/test_deviceguard 1/1 ... [2025-07-17 08:59:42.774605] 2025-07-17T08:59:42.7751397Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:59:42.7753711Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_deviceguard.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:59:42.774988] 2025-07-17T08:59:43.8475457Z 2025-07-17T08:59:43.8477556Z torch_np/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_indexing_1.1_60a2b4968caf8b0a_.log 2025-07-17T08:59:43.8480225Z Running 5 items in this shard: test/torch_np/test_indexing.py::TestAdvancedIndexing::test_advanced_separation_patterns, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_broadcast_and_numpy_compatibility, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_comprehensive_indexing, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_ellipsis, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_special_index_types 2025-07-17T08:59:43.8482232Z 2025-07-17T08:59:46.1798394Z 2025-07-17T08:59:46.1799856Z dynamo/test_deviceguard 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_deviceguard_1.1_9dda23613cfa2bc4_.log 2025-07-17T08:59:46.1800718Z 2025-07-17T08:59:47.0632034Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:59:47.0635329Z import pkg_resources 2025-07-17T08:59:47.1908983Z Running test_content_store 1/1 ... [2025-07-17 08:59:47.190445] 2025-07-17T08:59:47.1910050Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:59:47.1912602Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_content_store.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:59:47.190847] 2025-07-17T08:59:49.4553435Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:59:49.4556607Z import pkg_resources 2025-07-17T08:59:49.5820218Z Running lazy/test_step_closures 1/1 ... [2025-07-17 08:59:49.581596] 2025-07-17T08:59:49.5821180Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T08:59:49.5823555Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_step_closures.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 08:59:49.581984] 2025-07-17T08:59:56.7090976Z 2025-07-17T08:59:56.7092593Z lazy/test_step_closures 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_step_closures_1.1_faf1ed473203b0e1_.log 2025-07-17T08:59:56.7095953Z Running 4 items in this shard: test/lazy/test_step_closures.py::ClosuresTest::test_asynchronous, test/lazy/test_step_closures.py::ClosuresTest::test_asynchronous_exception, test/lazy/test_step_closures.py::ClosuresTest::test_synchronous, test/lazy/test_step_closures.py::ClosuresTest::test_synchronous_exception 2025-07-17T08:59:56.7098028Z 2025-07-17T08:59:59.9717874Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T08:59:59.9719681Z import pkg_resources 2025-07-17T09:00:00.0991224Z Running test_ops_gradients 1/1 ... [2025-07-17 09:00:00.098747] 2025-07-17T09:00:00.0992142Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:00:00.0994165Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_gradients.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:00:00.099123] 2025-07-17T09:00:04.6846891Z 2025-07-17T09:00:04.6848447Z test_content_store 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_content_store_1.1_c1bfa06cc858f396_.log 2025-07-17T09:00:04.6850613Z Running 4 items in this shard: test/test_content_store.py::TestContentStoreCPU::test_basic_cpu, test/test_content_store.py::TestContentStoreCPU::test_load_tensor_cpu, test/test_content_store.py::TestContentStoreCPU::test_repeated_hash_cpu, test/test_content_store.py::TestContentStoreCPU::test_scalar_cpu 2025-07-17T09:00:04.6852012Z 2025-07-17T09:00:08.0001141Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:00:08.0002787Z import pkg_resources 2025-07-17T09:00:08.1292802Z Running test_pruning_op 1/1 ... [2025-07-17 09:00:08.128838] 2025-07-17T09:00:08.1293732Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:00:08.1296746Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_pruning_op.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:00:08.129270] 2025-07-17T09:00:12.8511157Z 2025-07-17T09:00:12.8512599Z test_pruning_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_pruning_op_1.1_c422e7b1bc99afde_.log 2025-07-17T09:00:12.8515453Z Running 2 items in this shard: test/test_pruning_op.py::PruningOpTest::test_rowwise_prune_op_32bit_indices, test/test_pruning_op.py::PruningOpTest::test_rowwise_prune_op_64bit_indices 2025-07-17T09:00:12.8516725Z 2025-07-17T09:00:14.3262283Z 2025-07-17T09:00:14.3263434Z test_datapipe 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_datapipe_1.1_58905e1ef239fb63_.log 2025-07-17T09:00:14.3296097Z Running 94 items in this shard: test/test_datapipe.py::TestDataChunk::test_as_string, test/test_datapipe.py::TestDataChunk::test_getitem, test/test_datapipe.py::TestDataChunk::test_iter, test/test_datapipe.py::TestDataChunk::test_len, test/test_datapipe.py::TestDataChunk::test_random_shuffle, test/test_datapipe.py::TestDataChunk::test_reverse, test/test_datapipe.py::TestDataChunk::test_sort, test/test_datapipe.py::TestStreamWrapper::test_api, test/test_datapipe.py::TestStreamWrapper::test_dir, test/test_datapipe.py::TestStreamWrapper::test_pickle, test/test_datapipe.py::TestStreamWrapper::test_repr, test/test_datapipe.py::TestIterableDataPipeBasic::test_demux_mux_datapipe, test/test_datapipe.py::TestIterableDataPipeBasic::test_groupby_iterable_datapipe, test/test_datapipe.py::TestIterableDataPipeBasic::test_listdirfiles_iterable_datapipe, test/test_datapipe.py::TestIterableDataPipeBasic::test_listdirfilesdeterministic_iterable_datapipe, test/test_datapipe.py::TestIterableDataPipeBasic::test_map_with_col_file_handle_datapipe, test/test_datapipe.py::TestIterableDataPipeBasic::test_openfilesfromdisk_iterable_datapipe, test/test_datapipe.py::TestIterableDataPipeBasic::test_routeddecoder_iterable_datapipe, test/test_datapipe.py::TestCaptureDataFrame::test_basic_capture, test/test_datapipe.py::TestDataFramesPipes::test_batch, test/test_datapipe.py::TestDataFramesPipes::test_capture, test/test_datapipe.py::TestDataFramesPipes::test_collate, test/test_datapipe.py::TestDataFramesPipes::test_filter, test/test_datapipe.py::TestDataFramesPipes::test_shuffle, test/test_datapipe.py::TestDataFramesPipes::test_unbatch, test/test_datapipe.py::TestFunctionalIterDataPipe::test_batch_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_collate_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_concat_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_demux_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_docstring, test/test_datapipe.py::TestFunctionalIterDataPipe::test_filter_datapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_fork_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_iterable_wrapper_datapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_map_dict_with_col_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_map_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_map_tuple_list_with_col_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_mux_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_sampler_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_serializable, test/test_datapipe.py::TestFunctionalIterDataPipe::test_serializable_with_dill, test/test_datapipe.py::TestFunctionalIterDataPipe::test_shuffler_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_stream_reader_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_unbatch_iterdatapipe, test/test_datapipe.py::TestFunctionalIterDataPipe::test_zip_iterdatapipe, test/test_datapipe.py::TestFunctionalMapDataPipe::test_batch_mapdatapipe, test/test_datapipe.py::TestFunctionalMapDataPipe::test_concat_mapdatapipe, test/test_datapipe.py::TestFunctionalMapDataPipe::test_docstring, test/test_datapipe.py::TestFunctionalMapDataPipe::test_map_mapdatapipe, test/test_datapipe.py::TestFunctionalMapDataPipe::test_sequence_wrapper_datapipe, test/test_datapipe.py::TestFunctionalMapDataPipe::test_serializable, test/test_datapipe.py::TestFunctionalMapDataPipe::test_serializable_with_dill, test/test_datapipe.py::TestFunctionalMapDataPipe::test_shuffler_mapdatapipe, test/test_datapipe.py::TestFunctionalMapDataPipe::test_zip_mapdatapipe, test/test_datapipe.py::TestTyping::test_compile_time, test/test_datapipe.py::TestTyping::test_construct_time, test/test_datapipe.py::TestTyping::test_isinstance, test/test_datapipe.py::TestTyping::test_issubinstance, test/test_datapipe.py::TestTyping::test_protocol, test/test_datapipe.py::TestTyping::test_reinforce, test/test_datapipe.py::TestTyping::test_runtime, test/test_datapipe.py::TestTyping::test_subtype, test/test_datapipe.py::TestGraph::test_simple_traverse, test/test_datapipe.py::TestGraph::test_traverse_circular_datapipe, test/test_datapipe.py::TestGraph::test_traverse_forked, test/test_datapipe.py::TestGraph::test_traverse_mapdatapipe, test/test_datapipe.py::TestGraph::test_traverse_mixdatapipe, test/test_datapipe.py::TestGraph::test_traverse_unhashable_datapipe, test/test_datapipe.py::TestSerialization::test_spawn_lambdas_iter, test/test_datapipe.py::TestSerialization::test_spawn_lambdas_map, test/test_datapipe.py::TestCircularSerialization::test_circular_serialization_with_dill, test/test_datapipe.py::TestCircularSerialization::test_circular_serialization_with_pickle, test/test_datapipe.py::TestSharding::test_legacy_custom_sharding, test/test_datapipe.py::TestSharding::test_legacy_custom_sharding_with_old_dataloader, test/test_datapipe.py::TestSharding::test_multi_sharding, test/test_datapipe.py::TestSharding::test_old_dataloader, test/test_datapipe.py::TestSharding::test_sharding_groups, test/test_datapipe.py::TestSharding::test_sharding_groups_in_legacy_grouping_package, test/test_datapipe.py::TestSharding::test_sharding_length, test/test_datapipe.py::TestSharding::test_simple_sharding, test/test_datapipe.py::TestIterDataPipeSingletonConstraint::test_iterdatapipe_singleton_buggy, test/test_datapipe.py::TestIterDataPipeSingletonConstraint::test_iterdatapipe_singleton_constraint_multiple_outputs, test/test_datapipe.py::TestIterDataPipeSingletonConstraint::test_iterdatapipe_singleton_generator, test/test_datapipe.py::TestIterDataPipeSingletonConstraint::test_iterdatapipe_singleton_new_object, test/test_datapipe.py::TestIterDataPipeSingletonConstraint::test_iterdatapipe_singleton_self_next, test/test_datapipe.py::TestIterDataPipeCountSampleYielded::test_iterdatapipe_sample_yielded_generator_function, test/test_datapipe.py::TestIterDataPipeCountSampleYielded::test_iterdatapipe_sample_yielded_generator_function_exception, test/test_datapipe.py::TestIterDataPipeCountSampleYielded::test_iterdatapipe_sample_yielded_next, test/test_datapipe.py::TestIterDataPipeCountSampleYielded::test_iterdatapipe_sample_yielded_next_exception, test/test_datapipe.py::TestIterDataPipeCountSampleYielded::test_iterdatapipe_sample_yielded_return_self, test/test_datapipe.py::TestIterDataPipeGraphFastForward::test_simple_snapshot_custom_non_generator, test/test_datapipe.py::TestIterDataPipeGraphFastForward::test_simple_snapshot_custom_self_next, test/test_datapipe.py::TestIterDataPipeGraphFastForward::test_simple_snapshot_graph, test/test_datapipe.py::TestIterDataPipeGraphFastForward::test_simple_snapshot_graph_repeated, test/test_datapipe.py::TestIterDataPipeGraphFastForward::test_simple_snapshot_graph_with_serialization 2025-07-17T09:00:14.3327475Z 2025-07-17T09:00:16.1528773Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:00:16.1531860Z import pkg_resources 2025-07-17T09:00:16.2786501Z Running test_set_default_mobile_cpu_allocator 1/1 ... [2025-07-17 09:00:16.278244] 2025-07-17T09:00:16.2787497Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:00:16.2790746Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_set_default_mobile_cpu_allocator.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:00:16.278620] 2025-07-17T09:00:17.5990427Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:00:17.5993550Z import pkg_resources 2025-07-17T09:00:17.7255236Z Running test_monitor 1/1 ... [2025-07-17 09:00:17.725074] 2025-07-17T09:00:17.7256070Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:00:17.7258103Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_monitor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:00:17.725482] 2025-07-17T09:00:21.0001161Z 2025-07-17T09:00:21.0002992Z test_set_default_mobile_cpu_allocator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_set_default_mobile_cpu_allocator_1.1_8f5e691f1cc2ba18_.log 2025-07-17T09:00:21.0006165Z Running 2 items in this shard: test/test_set_default_mobile_cpu_allocator.py::TestSetDefaultMobileCPUAllocator::test_exception, test/test_set_default_mobile_cpu_allocator.py::TestSetDefaultMobileCPUAllocator::test_no_exception 2025-07-17T09:00:21.0008212Z 2025-07-17T09:00:22.5472847Z 2025-07-17T09:00:22.5474500Z test_monitor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_monitor_1.1_627a0fe759580742_.log 2025-07-17T09:00:22.5477947Z Running 6 items in this shard: test/test_monitor.py::TestMonitor::test_event_handler, test/test_monitor.py::TestMonitor::test_fixed_count_stat, test/test_monitor.py::TestMonitor::test_interval_stat, test/test_monitor.py::TestMonitor::test_log_event, test/test_monitor.py::TestMonitor::test_wait_counter, test/test_monitor.py::TestMonitorTensorboard::test_event_handler 2025-07-17T09:00:22.5480163Z 2025-07-17T09:00:23.7057485Z 2025-07-17T09:00:23.7059073Z test_ops_gradients 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_gradients_1.1_607dee4586f41990_.log 2025-07-17T09:00:23.9727548Z Running 5379 items in this shard: test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_H_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_H_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpyCatCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpyCubeCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpyMulCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpyMulScalarCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpyNMSCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpyNonzeroCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpySortCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpySplitCopyCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpySplitCopyWithIntCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpyTakeCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpyViewCopyCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_T_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_T_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___getitem___cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___getitem___cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___radd___cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___radd___cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rdiv___cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rdiv___cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rmatmul___cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rmatmul___cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rmod___cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rmul___cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rmul___cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rpow___cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rpow___cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rsub___cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rsub___cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__batch_norm_with_update_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__chunk_cat_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__chunk_cat_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__native_batch_norm_legit_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__segment_reduce_lengths_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__segment_reduce_offsets_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__softmax_backward_data_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__unsafe_masked_index_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__unsafe_masked_index_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__unsafe_masked_index_put_accumulate_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__upsample_bilinear2d_aa_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_abs_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_abs_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_acos_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_acos_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_acosh_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_acosh_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_add_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_add_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addbmm_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addbmm_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addcdiv_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addcdiv_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addcmul_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addcmul_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addmm_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addmm_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addmm_decomposed_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addmm_decomposed_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addmv_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addmv_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addr_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_addr_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_alias_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_alias_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_all_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_all_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_allclose_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_allclose_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_amax_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_amin_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_aminmax_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_angle_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_angle_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_any_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_any_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_arange_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_argmax_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_argmin_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_argsort_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_argwhere_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_argwhere_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_as_strided_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_as_strided_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_as_strided_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_as_strided_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_as_strided_partial_views_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_as_strided_partial_views_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_as_strided_scatter_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_as_strided_scatter_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_asin_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_asin_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_asinh_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_asinh_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_atan2_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_atan_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_atan_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_atanh_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_atanh_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_atleast_1d_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_atleast_1d_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_atleast_2d_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_atleast_2d_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_atleast_3d_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_atleast_3d_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_baddbmm_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_baddbmm_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_bernoulli_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_bfloat16_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_bfloat16_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_block_diag_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_block_diag_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_bmm_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_bmm_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_bool_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_bool_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_broadcast_tensors_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_broadcast_tensors_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_broadcast_to_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_broadcast_to_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_bucketize_cpu_float64, 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test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_ceil_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_cfloat_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_cfloat_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_chalf_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_chalf_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_char_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_char_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_cholesky_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_cholesky_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_cholesky_inverse_cpu_complex128, 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test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_softmax_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_softmax_with_dtype_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_softmax_with_dtype_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sort_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sparse_mm_reduce_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sparse_sampled_addmm_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sparse_sampled_addmm_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_airy_ai_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_bessel_j0_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_bessel_j1_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_bessel_y0_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_bessel_y1_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_chebyshev_polynomial_t_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_chebyshev_polynomial_u_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_chebyshev_polynomial_v_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_chebyshev_polynomial_w_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_entr_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_erfcx_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_hermite_polynomial_h_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_hermite_polynomial_he_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_i0e_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_i1_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_i1e_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_laguerre_polynomial_l_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_legendre_polynomial_p_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_log_ndtr_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_modified_bessel_i0_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_modified_bessel_i1_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_modified_bessel_k0_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_modified_bessel_k1_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_ndtr_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_ndtri_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_polygamma_special_polygamma_n_0_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_scaled_modified_bessel_k0_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_scaled_modified_bessel_k1_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_shifted_chebyshev_polynomial_t_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_shifted_chebyshev_polynomial_u_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_shifted_chebyshev_polynomial_v_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_shifted_chebyshev_polynomial_w_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_spherical_bessel_j0_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_xlog1py_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_special_zeta_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_split_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_split_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_split_list_args_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_split_list_args_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_split_with_sizes_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_split_with_sizes_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_split_with_sizes_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_split_with_sizes_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sqrt_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sqrt_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_square_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_square_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_squeeze_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_squeeze_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_squeeze_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_squeeze_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_squeeze_multiple_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_squeeze_multiple_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_stack_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_stack_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_std_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_std_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_std_mean_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_std_mean_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_std_mean_unbiased_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_std_mean_unbiased_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_std_unbiased_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_std_unbiased_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_stft_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_stft_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sub_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sub_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sum_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sum_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sum_to_size_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_sum_to_size_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_svd_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_svd_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_svd_lowrank_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_svd_lowrank_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_t_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_t_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_t_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_t_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_take_along_dim_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_take_along_dim_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_take_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_take_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tan_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tan_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tanh_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tanh_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tensor_split_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tensor_split_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tensordot_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tensordot_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tile_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tile_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_to_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_to_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_to_sparse_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_to_sparse_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_topk_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_torch_ops_aten__safe_softmax_default_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trace_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trace_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_transpose_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_transpose_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_transpose_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_transpose_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trapezoid_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trapezoid_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trapz_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trapz_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_triangular_solve_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_triangular_solve_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tril_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tril_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_triu_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_triu_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_true_divide_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_true_divide_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trunc_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unbind_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unbind_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unbind_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unbind_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unflatten_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unflatten_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unfold_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unfold_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unfold_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unfold_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_uniform_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_uniform_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unique_consecutive_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unique_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unsafe_chunk_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unsafe_chunk_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unsafe_split_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unsafe_split_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unsqueeze_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unsqueeze_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unsqueeze_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unsqueeze_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_mean_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_mean_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_mean_unbiased_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_mean_unbiased_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_unbiased_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_unbiased_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_vdot_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_vdot_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_view_as_complex_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_view_as_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_view_as_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_view_as_real_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_view_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_view_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_view_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_view_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_vsplit_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_vsplit_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_vstack_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_vstack_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_where_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_where_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_xlogy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_zero__cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_zero__cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_zeros_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_zeros_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_zeros_like_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_zeros_like_cpu_float64 2025-07-17T09:00:24.1860483Z 2025-07-17T09:00:24.3479205Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:00:24.3480893Z import pkg_resources 2025-07-17T09:00:24.4759266Z Running dynamo/test_package 1/1 ... [2025-07-17 09:00:24.475529] 2025-07-17T09:00:24.4759924Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:00:24.4762522Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_package.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:00:24.475951] 2025-07-17T09:00:25.9390583Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:00:25.9393614Z import pkg_resources 2025-07-17T09:00:26.0643083Z Running test_segment_reductions 1/1 ... [2025-07-17 09:00:26.063873] 2025-07-17T09:00:26.0644098Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:00:26.0646855Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_segment_reductions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:00:26.064323] 2025-07-17T09:00:27.0260497Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:00:27.0262157Z import pkg_resources 2025-07-17T09:00:27.1519644Z Running test_out_dtype_op 1/1 ... [2025-07-17 09:00:27.151550] 2025-07-17T09:00:27.1520325Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:00:27.1522350Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_out_dtype_op.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:00:27.151951] 2025-07-17T09:00:31.5704287Z 2025-07-17T09:00:31.5705774Z dynamo/test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_package_1.1_e6f622b701b9070c_.log 2025-07-17T09:00:34.8631958Z 2025-07-17T09:00:34.8635141Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:00:34.8638222Z import pkg_resources 2025-07-17T09:00:34.9888232Z Running test_cuda_sanitizer 1/1 ... [2025-07-17 09:00:34.988392] 2025-07-17T09:00:34.9889402Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:00:34.9891812Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_sanitizer.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:00:34.988801] 2025-07-17T09:00:38.4173468Z 2025-07-17T09:00:38.4175053Z test_cuda_sanitizer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_sanitizer_1.1_5c50da1cd2f4acfc_.log 2025-07-17T09:00:38.4176039Z Running 0 items in this shard: 2025-07-17T09:00:38.4176322Z 2025-07-17T09:00:38.9885380Z 2025-07-17T09:00:38.9887039Z test_out_dtype_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_out_dtype_op_1.1_1f7e58db44fa5aab_.log 2025-07-17T09:00:38.9893828Z Running 12 items in this shard: test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_dynamo, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_inductor_decomp, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_inductor_decomp_trace, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_int_mm_default_trace, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_make_fx, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_mm_numerical, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_mul_scalar_numerical, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_no_autograd, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_non_functional, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_non_op_overload, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_op_functional, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_wrong_output 2025-07-17T09:00:38.9899780Z 2025-07-17T09:00:41.6708916Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:00:41.6711813Z import pkg_resources 2025-07-17T09:00:41.7973999Z Running test_model_exports_to_core_aten 1/1 ... [2025-07-17 09:00:41.796928] 2025-07-17T09:00:41.7975245Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:00:41.7977469Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_model_exports_to_core_aten.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:00:41.797348] 2025-07-17T09:00:42.1595304Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:00:42.1598710Z import pkg_resources 2025-07-17T09:00:42.3069344Z Running test_mkldnn 1/1 ... [2025-07-17 09:00:42.306554] 2025-07-17T09:00:42.3069927Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:00:42.3072687Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:00:42.306925] 2025-07-17T09:00:46.5694494Z 2025-07-17T09:00:46.5695945Z test_model_exports_to_core_aten 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_model_exports_to_core_aten_1.1_0af5f84d27ccbb0f_.log 2025-07-17T09:00:46.5697613Z Running 1 items in this shard: test/test_model_exports_to_core_aten.py::TestQuantizePT2EModels::test_vit_aten_export 2025-07-17T09:00:46.5698161Z 2025-07-17T09:00:50.2889798Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:00:50.2892797Z import pkg_resources 2025-07-17T09:00:50.4165481Z Running test_jit 2/2 ... [2025-07-17 09:00:50.416029] 2025-07-17T09:00:50.4166771Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:00:50.4171781Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:00:50.416477] 2025-07-17T09:02:58.0696207Z 2025-07-17T09:02:58.0697289Z test_segment_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_segment_reductions_1.1_6116b676332efdc3_.log 2025-07-17T09:02:58.0738107Z Running 74 items in this shard: test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_unsafe_flag_cpu_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_unsafe_flag_cpu_int64 2025-07-17T09:02:58.0773360Z 2025-07-17T09:03:01.4396521Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:03:01.4399609Z import pkg_resources 2025-07-17T09:03:01.6008279Z Running dynamo/test_compiler_bisector 1/1 ... [2025-07-17 09:03:01.600432] 2025-07-17T09:03:01.6008813Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:03:01.6010969Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_compiler_bisector.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:03:01.600798] 2025-07-17T09:03:08.6914508Z 2025-07-17T09:03:08.6916120Z dynamo/test_compiler_bisector 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_compiler_bisector_1.1_14ae8a130dbb195a_.log 2025-07-17T09:03:08.6916910Z 2025-07-17T09:03:11.9202109Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:03:11.9205126Z import pkg_resources 2025-07-17T09:03:12.0465197Z Running dynamo/test_aot_autograd 1/1 ... [2025-07-17 09:03:12.046082] 2025-07-17T09:03:12.0465983Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:03:12.0468108Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_aot_autograd.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:03:12.046480] 2025-07-17T09:03:15.6843608Z 2025-07-17T09:03:15.6845181Z dynamo/test_aot_autograd 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_aot_autograd_1.1_2578644f113bdf55_.log 2025-07-17T09:03:15.6846649Z 2025-07-17T09:03:19.2149406Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:03:19.2152294Z import pkg_resources 2025-07-17T09:03:19.3427079Z Running dynamo/test_callback 1/1 ... [2025-07-17 09:03:19.341792] 2025-07-17T09:03:19.3427646Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:03:19.3429061Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_callback.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:03:19.342223] 2025-07-17T09:03:26.3010978Z 2025-07-17T09:03:26.3012683Z dynamo/test_callback 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_callback_1.1_9ef9cd99208b609a_.log 2025-07-17T09:03:26.3014066Z 2025-07-17T09:03:29.6126444Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:03:29.6128042Z import pkg_resources 2025-07-17T09:03:29.7389698Z Running dynamo/test_torchrec 1/1 ... [2025-07-17 09:03:29.738576] 2025-07-17T09:03:29.7390440Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:03:29.7393678Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_torchrec.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:03:29.739005] 2025-07-17T09:03:33.5009880Z 2025-07-17T09:03:33.5011352Z dynamo/test_torchrec 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_torchrec_1.1_43457df9ae70b170_.log 2025-07-17T09:03:33.5012461Z 2025-07-17T09:03:36.9403775Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:03:36.9405412Z import pkg_resources 2025-07-17T09:03:37.0688335Z Running test_matmul_cuda 1/1 ... [2025-07-17 09:03:37.068334] 2025-07-17T09:03:37.0689145Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:03:37.0691503Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_matmul_cuda.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:03:37.068729] 2025-07-17T09:03:40.5946854Z 2025-07-17T09:03:40.5948495Z test_matmul_cuda 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_matmul_cuda_1.1_336f737cdd693a8f_.log 2025-07-17T09:03:40.5949502Z Running 0 items in this shard: 2025-07-17T09:03:40.5949697Z 2025-07-17T09:03:44.1866233Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:03:44.1869144Z import pkg_resources 2025-07-17T09:03:44.3135982Z Running optim/test_swa_utils 1/1 ... [2025-07-17 09:03:44.313230] 2025-07-17T09:03:44.3136692Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:03:44.3140036Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'optim/test_swa_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:03:44.313628] 2025-07-17T09:03:48.0584418Z 2025-07-17T09:03:48.0585671Z optim/test_swa_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/optim.test_swa_utils_1.1_1817c9643f9fe111_.log 2025-07-17T09:03:48.0586359Z 2025-07-17T09:03:51.7349374Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:03:51.7352058Z import pkg_resources 2025-07-17T09:03:51.9423419Z Running test_sparse_semi_structured 1/1 ... [2025-07-17 09:03:51.941874] 2025-07-17T09:03:51.9424979Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:03:51.9431189Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sparse_semi_structured.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:03:51.942509] 2025-07-17T09:04:02.5411516Z 2025-07-17T09:04:02.5413026Z test_sparse_semi_structured 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_semi_structured_1.1_de124f3d1f3b879e_.log 2025-07-17T09:04:02.5449862Z Running 42 items in this shard: test/test_sparse_semi_structured.py::SparseSemiStructuredTensorCompileTest::test_mlp_contiguous_relu_compile_cusparselt, test/test_sparse_semi_structured.py::SparseSemiStructuredTensorCompileTest::test_mlp_contiguous_relu_compile_cutlass, test/test_sparse_semi_structured.py::SparseSemiStructuredTensorCompileTest::test_sp24_compile, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_indices, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_linear, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_min_sparse_shape, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mlp, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mm_sparse_first_NN, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mm_sparse_first_NT, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mm_sparse_first_TN, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mm_sparse_second_NN, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mm_sparse_second_NT, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_to_sparse_semi_structured, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_unsupported_dim, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_unsupported_dtype, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_unsupported_shape, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_values, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_gemm, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_pack_both_ways_edge_case1, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_pack_both_ways_id, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_pack_both_ways_meta_correctness, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_prune_dense_static_sort, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_pruning_algo_largest_abs_values_greedy, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_sp24_apply, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_sp24_apply_dense, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_sp24_matmuls, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_sp24_matmuls_bmm, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_sp24_matmuls_mat_vec, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUTLASS::test_conversions, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUTLASS::test_conversions_all_patterns, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUTLASS::test_linear_cutlass, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUTLASS::test_sparse_semi_structured_ops_cutlass, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cslt_sparse_mm_alpha, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cslt_sparse_mm_alpha_compile_autotune, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cslt_sparse_mm_alpha_mixed_dtype, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cslt_sparse_mm_mixed_dtype, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cslt_sparse_mm_search, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_csrc_cslt_sparse_mm_search, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cusparselt_backend, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_sparse_fp8fp8_mm, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_sparse_semi_structured_scaled_mm, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_sparse_semi_structured_scaled_mm_fp8 2025-07-17T09:04:02.5486986Z 2025-07-17T09:04:06.9927529Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:04:06.9930593Z import pkg_resources 2025-07-17T09:04:07.1765023Z Running functorch/test_control_flow 1/1 ... [2025-07-17 09:04:07.176067] 2025-07-17T09:04:07.1766042Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:04:07.1769315Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_control_flow.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:04:07.176543] 2025-07-17T09:07:01.9039301Z 2025-07-17T09:07:01.9040594Z test_mkldnn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_1.1_91c7aa85eedc334a_.log 2025-07-17T09:07:01.9077979Z Running 90 items in this shard: test/test_mkldnn.py::TestMkldnnCPU::test_0_dimension_tensor_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_adaptive_avg_pool2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_adaptive_avg_pool2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_add_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_autograd_from_mkldnn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_autograd_to_mkldnn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool2d_stride_none_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool3d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_3d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_clone_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv1d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv1d_functional_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv2d_legacy_jit_model_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_1d_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_1d_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_2d_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_2d_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_3d_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_3d_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_nhwc_fp32_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_nhwc_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_nhwc_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose1d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose_nhwc_fp32_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose_nhwc_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose_nhwc_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conversion_byte_char_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conversion_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_copy_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_default_use_parent_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_detach_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_empty_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_gelu_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_gelu_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_generic_precision_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_invalid_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_is_mkldnn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_is_mkldnn_jit_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_legacy_new_failure_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_linear_backward_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_linear_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_linear_lowp_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_linear_lowp_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_linear_non_contiguous_weight_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_lstm_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_matmul_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_matmul_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool2d_stride_none_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool3d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool_unsupported_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_conv_shapecheck_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_error_on_zero_stride_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_scaled_mm_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_setflags_nowarn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mlkdnn_get_set_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mul_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_prelu_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_prelu_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu__cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu_inplace_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_repr_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_reshape_backward_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_reshape_blocked_format_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_reshape_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_resnet18_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_resnext50_32x4d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_set_data_tensorimpl_type_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_sigmoid_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_softmax_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_tanh_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_transpose_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_transpose_invalid_dime_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_unsupported_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_view_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_zero__cpu 2025-07-17T09:07:01.9118170Z 2025-07-17T09:07:05.0565221Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:07:05.0568161Z import pkg_resources 2025-07-17T09:07:05.1831316Z Running torch_np/numpy_tests/core/test_scalarmath 1/1 ... [2025-07-17 09:07:05.182664] 2025-07-17T09:07:05.1832222Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:07:05.1834522Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalarmath.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:07:05.183040] 2025-07-17T09:07:38.0998156Z 2025-07-17T09:07:38.0999583Z torch_np/numpy_tests/core/test_scalarmath 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalarmath_1.1_d5080da43242bd69_.log 2025-07-17T09:07:38.1129013Z Running 238 items in this shard: test/torch_np/numpy_tests/core/test_scalarmath.py::TestTypes::test_leak, test/torch_np/numpy_tests/core/test_scalarmath.py::TestTypes::test_type_add, test/torch_np/numpy_tests/core/test_scalarmath.py::TestTypes::test_type_create, test/torch_np/numpy_tests/core/test_scalarmath.py::TestTypes::test_types, test/torch_np/numpy_tests/core/test_scalarmath.py::TestBaseMath::test_blocked, test/torch_np/numpy_tests/core/test_scalarmath.py::TestBaseMath::test_lower_align, test/torch_np/numpy_tests/core/test_scalarmath.py::TestPower::test_integers_to_negative_integer_power, test/torch_np/numpy_tests/core/test_scalarmath.py::TestPower::test_large_types, test/torch_np/numpy_tests/core/test_scalarmath.py::TestPower::test_mixed_types, test/torch_np/numpy_tests/core/test_scalarmath.py::TestPower::test_modular_power, test/torch_np/numpy_tests/core/test_scalarmath.py::TestPower::test_small_types, test/torch_np/numpy_tests/core/test_scalarmath.py::TestModulus::test_float_modulus_corner_cases_dt_d, test/torch_np/numpy_tests/core/test_scalarmath.py::TestModulus::test_float_modulus_corner_cases_dt_e, test/torch_np/numpy_tests/core/test_scalarmath.py::TestModulus::test_float_modulus_corner_cases_dt_f, test/torch_np/numpy_tests/core/test_scalarmath.py::TestModulus::test_float_modulus_exact, test/torch_np/numpy_tests/core/test_scalarmath.py::TestModulus::test_float_modulus_roundoff, test/torch_np/numpy_tests/core/test_scalarmath.py::TestModulus::test_modulus_basic, test/torch_np/numpy_tests/core/test_scalarmath.py::TestComplexDivision::test_branches, test/torch_np/numpy_tests/core/test_scalarmath.py::TestComplexDivision::test_signed_zeros, test/torch_np/numpy_tests/core/test_scalarmath.py::TestComplexDivision::test_zero_division, test/torch_np/numpy_tests/core/test_scalarmath.py::TestConversion::test_iinfo_long_values_1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestConversion::test_iinfo_long_values_2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestConversion::test_int_from_long, test/torch_np/numpy_tests/core/test_scalarmath.py::TestConversion::test_int_raise_behaviour, test/torch_np/numpy_tests/core/test_scalarmath.py::TestConversion::test_numpy_scalar_relational_operators, test/torch_np/numpy_tests/core/test_scalarmath.py::TestConversion::test_numpy_scalar_relational_operators_2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestConversion::test_scalar_comparison_to_none, test/torch_np/numpy_tests/core/test_scalarmath.py::TestRepr::test_float_repr, test/torch_np/numpy_tests/core/test_scalarmath.py::TestMultiply::test_no_seq_repeat_basic_array_like, 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test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____ge_____rop_____le___op5_cmp_True_subtype2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____ge_____rop_____le___op5_cmp_True_subtype3, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____gt_____rop_____lt___op4_cmp_True_subtype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____gt_____rop_____lt___op4_cmp_True_subtype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____gt_____rop_____lt___op4_cmp_True_subtype2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____gt_____rop_____lt___op4_cmp_True_subtype3, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____le_____rop_____ge___op1_cmp_True_subtype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____le_____rop_____ge___op1_cmp_True_subtype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____le_____rop_____ge___op1_cmp_True_subtype2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____le_____rop_____ge___op1_cmp_True_subtype3, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____lt_____rop_____gt___op0_cmp_True_subtype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____lt_____rop_____gt___op0_cmp_True_subtype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____lt_____rop_____gt___op0_cmp_True_subtype2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____lt_____rop_____gt___op0_cmp_True_subtype3, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____mod_____rop_____rmod___op9_cmp_False_subtype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____mod_____rop_____rmod___op9_cmp_False_subtype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____mod_____rop_____rmod___op9_cmp_False_subtype2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____mod_____rop_____rmod___op9_cmp_False_subtype3, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____mul_____rop_____rmul___op10_cmp_False_subtype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____mul_____rop_____rmul___op10_cmp_False_subtype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____mul_____rop_____rmul___op10_cmp_False_subtype2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____mul_____rop_____rmul___op10_cmp_False_subtype3, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____ne_____rop_____ne___op3_cmp_True_subtype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____ne_____rop_____ne___op3_cmp_True_subtype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____ne_____rop_____ne___op3_cmp_True_subtype2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____ne_____rop_____ne___op3_cmp_True_subtype3, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____pow_____rop_____rpow___op11_cmp_False_subtype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____pow_____rop_____rpow___op11_cmp_False_subtype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____pow_____rop_____rpow___op11_cmp_False_subtype2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____pow_____rop_____rpow___op11_cmp_False_subtype3, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____sub_____rop_____rsub___op12_cmp_False_subtype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____sub_____rop_____rsub___op12_cmp_False_subtype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____sub_____rop_____rsub___op12_cmp_False_subtype2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____sub_____rop_____rsub___op12_cmp_False_subtype3, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____truediv_____rop_____rtruediv___op7_cmp_False_subtype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____truediv_____rop_____rtruediv___op7_cmp_False_subtype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____truediv_____rop_____rtruediv___op7_cmp_False_subtype2, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_pyscalar_subclasses___op_____truediv_____rop_____rtruediv___op7_cmp_False_subtype3, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____add_____rop_____radd___op8_cmp_False_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____add_____rop_____radd___op8_cmp_False_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____eq_____rop_____eq___op2_cmp_True_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____eq_____rop_____eq___op2_cmp_True_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____floordiv_____rop_____rfloordiv___op6_cmp_False_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____floordiv_____rop_____rfloordiv___op6_cmp_False_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____ge_____rop_____le___op5_cmp_True_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____ge_____rop_____le___op5_cmp_True_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____gt_____rop_____lt___op4_cmp_True_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____gt_____rop_____lt___op4_cmp_True_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____le_____rop_____ge___op1_cmp_True_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____le_____rop_____ge___op1_cmp_True_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____lt_____rop_____gt___op0_cmp_True_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____lt_____rop_____gt___op0_cmp_True_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____mod_____rop_____rmod___op9_cmp_False_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____mod_____rop_____rmod___op9_cmp_False_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____mul_____rop_____rmul___op10_cmp_False_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____mul_____rop_____rmul___op10_cmp_False_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____ne_____rop_____ne___op3_cmp_True_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____ne_____rop_____ne___op3_cmp_True_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____pow_____rop_____rpow___op11_cmp_False_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____pow_____rop_____rpow___op11_cmp_False_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____sub_____rop_____rsub___op12_cmp_False_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____sub_____rop_____rsub___op12_cmp_False_sctype1, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____truediv_____rop_____rtruediv___op7_cmp_False_sctype0, test/torch_np/numpy_tests/core/test_scalarmath.py::TestScalarSubclassingMisc::test_subclass_deferral___op_____truediv_____rop_____rtruediv___op7_cmp_False_sctype1 2025-07-17T09:07:38.1250626Z 2025-07-17T09:07:41.3427012Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:07:41.3430025Z import pkg_resources 2025-07-17T09:07:41.4682349Z Running torch_np/numpy_tests/core/test_getlimits 1/1 ... [2025-07-17 09:07:41.467829] 2025-07-17T09:07:41.4683359Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:07:41.4685529Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_getlimits.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:07:41.468207] 2025-07-17T09:07:46.7424215Z 2025-07-17T09:07:46.7425989Z torch_np/numpy_tests/core/test_getlimits 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_getlimits_1.1_bf6e3d6a7063d13f_.log 2025-07-17T09:07:46.7438286Z Running 17 items in this shard: test/torch_np/numpy_tests/core/test_getlimits.py::TestPythonFloat::test_singleton, test/torch_np/numpy_tests/core/test_getlimits.py::TestHalf::test_singleton, test/torch_np/numpy_tests/core/test_getlimits.py::TestSingle::test_singleton, test/torch_np/numpy_tests/core/test_getlimits.py::TestDouble::test_singleton, test/torch_np/numpy_tests/core/test_getlimits.py::TestFinfo::test_basic, test/torch_np/numpy_tests/core/test_getlimits.py::TestFinfo::test_basic_missing, test/torch_np/numpy_tests/core/test_getlimits.py::TestIinfo::test_basic, test/torch_np/numpy_tests/core/test_getlimits.py::TestIinfo::test_unsigned_max_T0, test/torch_np/numpy_tests/core/test_getlimits.py::TestIinfo::test_unsigned_max_T1, test/torch_np/numpy_tests/core/test_getlimits.py::TestIinfo::test_unsigned_max_T2, test/torch_np/numpy_tests/core/test_getlimits.py::TestIinfo::test_unsigned_max_T3, test/torch_np/numpy_tests/core/test_getlimits.py::TestRepr::test_finfo_repr, test/torch_np/numpy_tests/core/test_getlimits.py::TestRepr::test_iinfo_repr, test/torch_np/numpy_tests/core/test_getlimits.py::TestMisc::test_instances, test/torch_np/numpy_tests/core/test_getlimits.py::TestMisc::test_known_types, test/torch_np/numpy_tests/core/test_getlimits.py::TestMisc::test_plausible_finfo, test/torch_np/numpy_tests/core/test_getlimits.py::TestMisc::test_subnormal_warning 2025-07-17T09:07:46.7449702Z 2025-07-17T09:07:49.8443562Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:07:49.8445346Z import pkg_resources 2025-07-17T09:07:49.9712632Z Running torch_np/numpy_tests/core/test_dtype 1/1 ... [2025-07-17 09:07:49.970791] 2025-07-17T09:07:49.9713383Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:07:49.9714747Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_dtype.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:07:49.971193] 2025-07-17T09:07:58.3992417Z 2025-07-17T09:07:58.3994079Z torch_np/numpy_tests/core/test_dtype 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_dtype_1.1_5c0a8fc63ed46cf0_.log 2025-07-17T09:07:58.4087670Z Running 136 items in this shard: test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_equivalent_dtype_hashing, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_invalid_types, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Bool, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Bytes0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Complex128, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Complex32, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Complex64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Datetime64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Float128, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Float16, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Float32, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Float64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Int16, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Int32, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Int64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Int8, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Object0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Str0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Timedelta64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_UInt16, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_UInt32, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_UInt64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_UInt8, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Uint32, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Uint64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Void0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_richcompare_invalid_dtype_comparison_operation0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_richcompare_invalid_dtype_comparison_operation1, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_richcompare_invalid_dtype_comparison_operation2, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_richcompare_invalid_dtype_comparison_operation3, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_richcompare_invalid_dtype_equality, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_run_t0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_run_t1, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_run_t2, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_run_t3, test/torch_np/numpy_tests/core/test_dtype.py::TestDtypeAttributeDeletion::test_dtype_non_writable_attributes_deletion, test/torch_np/numpy_tests/core/test_dtype.py::TestDtypeAttributeDeletion::test_dtype_writable_attributes_deletion, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_builtin_t0, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_builtin_t1, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_builtin_t2, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_builtin_t3, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_builtin_t4, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_DType28, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_bool_0, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_bytes_22, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_complex128_20, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_complex256_21, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_complex64_19, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_datetime64_26, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_float128_18, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_float16_15, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_float32_16, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_float64_17, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_int16_2, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_int32_3, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_int64_4, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_int64_5, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_int64_6, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_int64_7, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_int8_1, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_object_25, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_str_23, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_timedelta64_27, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_uint16_9, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_uint32_10, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_uint64_11, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_uint64_12, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_uint64_13, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_uint64_14, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_uint8_8, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_void_24, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_other_value_based_complex64_complex64_None, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_other_value_based_float16_complex64_None, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_other_value_based_float32_complex64_None, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_other_value_based_other_4294967295_expected1_expected_weak1, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_other_value_based_other_65535_expected0_expected_weak0, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other0_expected0, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other1_expected1, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other2_expected2, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other3_expected3, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other4_expected4, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other5_expected5, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other6_expected6, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes0_expected0, 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test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes9_expected9, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_python_integer_promotion_val_18446744073709551616, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_python_integer_promotion_val_2, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_python_integer_promotion_val_200, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_python_integer_promotion_val_4294967296, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_python_integer_promotion_val_9223372036854775808, test/torch_np/numpy_tests/core/test_dtype.py::TestMisc::test_dtypes_are_true, test/torch_np/numpy_tests/core/test_dtype.py::TestMisc::test_keyword_argument, test/torch_np/numpy_tests/core/test_dtype.py::TestFromDTypeAttribute::test_recursion, test/torch_np/numpy_tests/core/test_dtype.py::TestFromDTypeAttribute::test_simple, 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test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_O, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_P, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_Q, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_S, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_U, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_V, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_b, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_d, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_e, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_f, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_g, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_h, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_i, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_l, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_m, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_n, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_p, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_q, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_subscript_scalar, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_subscript_tuple_arg_len_0, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_subscript_tuple_arg_len_1, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_subscript_tuple_arg_len_2, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_subscript_tuple_arg_len_3 2025-07-17T09:07:58.4191465Z 2025-07-17T09:08:01.6532071Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:08:01.6533628Z import pkg_resources 2025-07-17T09:08:01.7810129Z Running functorch/test_vmap_registrations 1/1 ... [2025-07-17 09:08:01.780618] 2025-07-17T09:08:01.7810709Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:08:01.7813379Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_vmap_registrations.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:08:01.781009] 2025-07-17T09:09:19.1136235Z 2025-07-17T09:09:19.1137515Z functorch/test_vmap_registrations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_registrations_1.1_ceed8e5f10f26c28_.log 2025-07-17T09:09:19.2266596Z Running 1717 items in this shard: test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[_test::cat], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[_test::get_first], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[_test::leaky_relu], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__and__.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__and__.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__iand__.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__iand__.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__ior__.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__ior__.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__ixor__.Scalar], 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test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_cast_Char], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_cast_Double], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_cast_Float], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_cast_Half], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_cast_Int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_cast_Long], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_cast_Short], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_choose_qparams_per_tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_convolution.deprecated], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_convolution_double_backward], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_convolution_mode], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_cufft_clear_plan_cache], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_cufft_get_plan_cache_max_size], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_cufft_get_plan_cache_size], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_cufft_set_plan_cache_max_size], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_debug_has_internal_overlap], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_dim_arange], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_embedding_bag_sparse_backward], 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test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_pack_padded_sequence_backward], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_pad_circular], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_pad_enum], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_pad_packed_sequence], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_propagate_xla_data], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_remove_batch_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_reshape_from_tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_rowwise_prune], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_saturate_weight_to_fp16], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_scaled_dot_product_attention_math], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_shape_as_tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_sobol_engine_draw], 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test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::unflatten.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::unflatten_dense_tensors], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::unsafe_chunk], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_bicubic2d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_bilinear2d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_linear1d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_nearest1d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_nearest2d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_nearest3d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_trilinear3d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::value_selecting_reduction_backward], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vander], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var.correction_names], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var.dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var.names_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean.correction_names], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean.dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean.names_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::view_as], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vsplit.array], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vsplit.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vstack], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where.ScalarOther], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where.ScalarSelf], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where] 2025-07-17T09:09:19.3360921Z 2025-07-17T09:09:22.4221310Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:09:22.4223125Z import pkg_resources 2025-07-17T09:09:22.5492875Z Running dynamo/test_comptime 1/1 ... [2025-07-17 09:09:22.548966] 2025-07-17T09:09:22.5493347Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:09:22.5496653Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_comptime.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:09:22.549363] 2025-07-17T09:09:26.0501867Z 2025-07-17T09:09:26.0503280Z dynamo/test_comptime 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_comptime_1.1_a8567e036e97be4a_.log 2025-07-17T09:09:26.0504593Z 2025-07-17T09:09:29.2748246Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:09:29.2751021Z import pkg_resources 2025-07-17T09:09:29.4008913Z Running torch_np/numpy_tests/core/test_shape_base 1/1 ... [2025-07-17 09:09:29.400438] 2025-07-17T09:09:29.4009894Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:09:29.4012023Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_shape_base.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:09:29.400863] 2025-07-17T09:09:50.6135692Z 2025-07-17T09:09:50.6220327Z torch_np/numpy_tests/core/test_shape_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_shape_base_1.1_f9cd4eb70bf8ec82_.log 2025-07-17T09:09:50.6322731Z Running 119 items in this shard: test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast1d::test_0D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast1d::test_1D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast1d::test_2D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast1d::test_3D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast1d::test_r1array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast2d::test_0D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast2d::test_1D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast2d::test_2D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast2d::test_3D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast2d::test_r2array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast3d::test_0D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast3d::test_1D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast3d::test_2D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast3d::test_3D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_0D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_1D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_2D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_casting_and_dtype, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_casting_and_dtype_type_error, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_empty_input, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_generator, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_non_iterable, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_0D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_1D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_2D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_2D_array2, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_casting_and_dtype, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_casting_and_dtype_type_error, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_empty_input, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_generator, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_non_iterable, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_bad_out_shape, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_concatenate, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_concatenate_axis_None, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_exceptions, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_large_concatenate_axis_None, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_operator_concat, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_c8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_c8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_c8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_c8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_c8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f4_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f4_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f4_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f4_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f4_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_i8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_i8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_i8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_i8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_i8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_c8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_c8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_c8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_c8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_c8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f4_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f4_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f4_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f4_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f4_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_i8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_i8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_i8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_i8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_i8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_simple, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_returns_copy, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_c8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_c8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_c8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_c8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_c8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f4_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f4_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f4_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f4_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f4_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_i8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_i8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_i8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_i8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_i8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_3d, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_complicated, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_memory_order, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_mixed_1d_and_2d, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_simple_column_wise, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_simple_row_wise, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_total_size_estimate, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_with_1d_arrays_column_wise, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_with_1d_arrays_multiple_rows, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_with_1d_arrays_row_wise, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_with_mismatched_shape, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_different_ndims, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_different_ndims_depths, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_empty_lists, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_invalid_nesting, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_nested, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_no_lists, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_returns_copy, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_tuple 2025-07-17T09:09:50.6423535Z 2025-07-17T09:09:54.2426114Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:09:54.2429151Z import pkg_resources 2025-07-17T09:09:54.4250547Z Running nn/test_packed_sequence 1/1 ... [2025-07-17 09:09:54.424516] 2025-07-17T09:09:54.4251411Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:09:54.4256148Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_packed_sequence.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:09:54.424974] 2025-07-17T09:10:18.3299598Z 2025-07-17T09:10:18.3301183Z nn/test_packed_sequence 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_packed_sequence_1.1_b3cf9aa67c2f5cea_.log 2025-07-17T09:10:18.3306562Z Running 12 items in this shard: test/nn/test_packed_sequence.py::PackedSequenceTest::test_pack_padded_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pack_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pad_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pad_sequence_with_non_iterable_sequences, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pad_sequence_with_tensor_sequences, test/nn/test_packed_sequence.py::PackedSequenceTest::test_to, test/nn/test_packed_sequence.py::PackedSequenceTest::test_to_memory_format, test/nn/test_packed_sequence.py::PackedSequenceTest::test_total_length, test/nn/test_packed_sequence.py::PackedSequenceTest::test_type_casts, test/nn/test_packed_sequence.py::PackedSequenceTest::test_unpack_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_unpad_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_wrong_order 2025-07-17T09:10:18.3310767Z 2025-07-17T09:10:21.5339579Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:10:21.5342475Z import pkg_resources 2025-07-17T09:10:21.6604305Z Running test_futures 1/1 ... [2025-07-17 09:10:21.659997] 2025-07-17T09:10:21.6604910Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:10:21.6606406Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_futures.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:10:21.660367] 2025-07-17T09:10:33.3936470Z 2025-07-17T09:10:33.3938102Z test_futures 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_futures_1.1_92a16b37cc3d0b89_.log 2025-07-17T09:10:33.3950379Z Running 22 items in this shard: test/test_futures.py::TestFuture::test_add_done_callback_error_is_ignored, test/test_futures.py::TestFuture::test_add_done_callback_maintains_callback_order, test/test_futures.py::TestFuture::test_add_done_callback_no_arg_error_is_ignored, test/test_futures.py::TestFuture::test_add_done_callback_simple, test/test_futures.py::TestFuture::test_chained_then, test/test_futures.py::TestFuture::test_collect_all, test/test_futures.py::TestFuture::test_done, test/test_futures.py::TestFuture::test_done_exception, test/test_futures.py::TestFuture::test_interleaving_then_and_add_done_callback_maintains_callback_order, test/test_futures.py::TestFuture::test_interleaving_then_and_add_done_callback_propagates_error, test/test_futures.py::TestFuture::test_mark_future_twice, test/test_futures.py::TestFuture::test_pickle_future, test/test_futures.py::TestFuture::test_set_exception, test/test_futures.py::TestFuture::test_set_exception_multithreading, test/test_futures.py::TestFuture::test_then, test/test_futures.py::TestFuture::test_then_no_arg, test/test_futures.py::TestFuture::test_then_raise, test/test_futures.py::TestFuture::test_then_wrong_arg, test/test_futures.py::TestFuture::test_wait, test/test_futures.py::TestFuture::test_wait_all, test/test_futures.py::TestFuture::test_wait_multi_thread, test/test_futures.py::TestFuture::test_wait_none 2025-07-17T09:10:33.3960988Z 2025-07-17T09:10:36.5957120Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:10:36.5960580Z import pkg_resources 2025-07-17T09:10:36.7219109Z Running torch_np/numpy_tests/fft/test_pocketfft 1/1 ... [2025-07-17 09:10:36.720831] 2025-07-17T09:10:36.7220334Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:10:36.7222825Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/fft/test_pocketfft.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:10:36.721250] 2025-07-17T09:11:01.0566940Z 2025-07-17T09:11:01.0567768Z test_jit 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_2.2_7138c1c826376324_.log 2025-07-17T09:11:01.1163280Z Running 1266 items in this shard: test/test_jit.py::TestTracer::test_call_traced_module_from_traced_module, test/test_jit.py::TestTracer::test_canonicalize_tensor_iterator, test/test_jit.py::TestTracer::test_constant, test/test_jit.py::TestTracer::test_conv, test/test_jit.py::TestTracer::test_export_no_reorder, test/test_jit.py::TestTracer::test_force_outplace_check_fill, test/test_jit.py::TestTracer::test_ge, test/test_jit.py::TestTracer::test_index_put, test/test_jit.py::TestTracer::test_index_put_trace_without_view, test/test_jit.py::TestTracer::test_inplace_flags, test/test_jit.py::TestTracer::test_input_dict_empty, test/test_jit.py::TestTracer::test_input_dict_empty_list, test/test_jit.py::TestTracer::test_input_dict_of_dicts, test/test_jit.py::TestTracer::test_input_dict_remembers_keys, test/test_jit.py::TestTracer::test_input_flatten, test/test_jit.py::TestTracer::test_input_list_mixed_type, test/test_jit.py::TestTracer::test_input_list_of_tuples, test/test_jit.py::TestTracer::test_input_list_toplevel_flatten, test/test_jit.py::TestTracer::test_large_nbr_kernel_args, test/test_jit.py::TestTracer::test_lhs_index_trivial, test/test_jit.py::TestTracer::test_nested_inplace, test/test_jit.py::TestTracer::test_non_tensor_tracing, test/test_jit.py::TestTracer::test_python_function, test/test_jit.py::TestTracer::test_repeated_output, test/test_jit.py::TestTracer::test_shared_param, test/test_jit.py::TestTracer::test_tensor_with_grad_as_constant, test/test_jit.py::TestTracer::test_trace_annotation, test/test_jit.py::TestTracer::test_trace_arange, test/test_jit.py::TestTracer::test_trace_autograd_function, test/test_jit.py::TestTracer::test_trace_casts, test/test_jit.py::TestTracer::test_trace_checker_slice_lhs, test/test_jit.py::TestTracer::test_trace_checking_with_deprecated_name, test/test_jit.py::TestTracer::test_trace_detach, test/test_jit.py::TestTracer::test_trace_detach_inplace, test/test_jit.py::TestTracer::test_trace_detach_inplace_redispatch, test/test_jit.py::TestTracer::test_trace_dict_input, test/test_jit.py::TestTracer::test_trace_export_fns, test/test_jit.py::TestTracer::test_trace_indexed_assignment, test/test_jit.py::TestTracer::test_trace_legacy_ctor, test/test_jit.py::TestTracer::test_trace_module_argument_names_captured, test/test_jit.py::TestTracer::test_trace_multi_output_function, test/test_jit.py::TestTracer::test_trace_namedtuple, test/test_jit.py::TestTracer::test_trace_nested_fn, test/test_jit.py::TestTracer::test_trace_numel, test/test_jit.py::TestTracer::test_trace_optioanl_dtype, test/test_jit.py::TestTracer::test_trace_partial_func_argument_names_captured, test/test_jit.py::TestTracer::test_trace_records_names, test/test_jit.py::TestTracer::test_trace_single_tuple, test/test_jit.py::TestTracer::test_trace_slice, test/test_jit.py::TestTracer::test_trace_slice_setitem_dynamic_shape, test/test_jit.py::TestTracer::test_trace_tensor_factory, test/test_jit.py::TestTracer::test_trace_topk, test/test_jit.py::TestTracer::test_trace_tuple, test/test_jit.py::TestTracer::test_trace_variable_instantiation, test/test_jit.py::TestTracer::test_trace_with_conditional_property, test/test_jit.py::TestTracer::test_trace_with_nested_strided_tensor_output, test/test_jit.py::TestTracer::test_trace_with_tensor_list_output, test/test_jit.py::TestTracer::test_trace_with_tuple_tensor, test/test_jit.py::TestTracer::test_tracing_backward_hook_error, test/test_jit.py::TestTracer::test_tracing_multiple_methods, test/test_jit.py::TestTracer::test_type_same_device, test/test_jit.py::TestTracer::test_typeas_trace_check, test/test_jit.py::TestTracer::test_wrapped_number, test/test_jit.py::TestMixTracingScripting::test_call_script_module_from_traced_module, test/test_jit.py::TestMixTracingScripting::test_call_tracing_mod_from_script_module, test/test_jit.py::TestMixTracingScripting::test_script_inline_trace_multiple_args, test/test_jit.py::TestMixTracingScripting::test_trace_dict_mix_script, test/test_jit.py::TestMixTracingScripting::test_trace_linear, test/test_jit.py::TestMixTracingScripting::test_trace_mixed_by_script_with_dict_output, test/test_jit.py::TestMixTracingScripting::test_trace_of_script, test/test_jit.py::TestMixTracingScripting::test_trace_parameter, test/test_jit.py::TestMixTracingScripting::test_trace_script_returning_complex_dict, test/test_jit.py::TestMixTracingScripting::test_trace_with_size, test/test_jit.py::TestMixTracingScripting::test_tracing_slicing, test/test_jit.py::TestRecursiveScript::test_attributes, test/test_jit.py::TestRecursiveScript::test_class_compile, test/test_jit.py::TestRecursiveScript::test_constants_with_final, test/test_jit.py::TestRecursiveScript::test_dir, test/test_jit.py::TestRecursiveScript::test_error_stack, test/test_jit.py::TestRecursiveScript::test_failed_function_compilation, test/test_jit.py::TestRecursiveScript::test_function_attribute_in_submodule, test/test_jit.py::TestRecursiveScript::test_init_error, test/test_jit.py::TestRecursiveScript::test_module_basic, test/test_jit.py::TestRecursiveScript::test_module_name, test/test_jit.py::TestRecursiveScript::test_module_repr, test/test_jit.py::TestRecursiveScript::test_optional_module, test/test_jit.py::TestRecursiveScript::test_override_instance_method_ignore, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_basic, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_escape_hatch, test/test_jit.py::TestRecursiveScript::test_repeated_error_stack, test/test_jit.py::TestRecursiveScript::test_script_function_attribute, test/test_jit.py::TestTypeSharing::test_assign_python_attr, test/test_jit.py::TestTypeSharing::test_builtin_function_same, test/test_jit.py::TestTypeSharing::test_constants, test/test_jit.py::TestTypeSharing::test_module_dict_same_type_different_name, test/test_jit.py::TestTypeSharing::test_mutate_attr_value, test/test_jit.py::TestTypeSharing::test_python_function_attribute_same, test/test_jit.py::TestTypeSharing::test_script_module_containing_traced_module, test/test_jit.py::TestTypeSharing::test_submodules, test/test_jit.py::TestTypeSharing::test_type_shared_ignored_attributes, test/test_jit.py::TestTypeSharing::test_type_sharing_disabled, test/test_jit.py::TestLogging::test_time_measurement_counter_script, test/test_jit.py::TestBackends::test_save_load, test/test_jit.py::TestBackendsWithCompiler::test_execution, test/test_jit.py::TestNnapiBackend::test_avg_pool2d, test/test_jit.py::TestNnapiBackend::test_dequantize, test/test_jit.py::TestNnapiBackend::test_flatten, test/test_jit.py::TestNnapiBackend::test_mean, test/test_jit.py::TestNnapiBackend::test_pointwise_binary_const, test/test_jit.py::TestNnapiBackend::test_reshape, test/test_jit.py::TestNnapiBackend::test_softmax, test/test_jit.py::TestNnapiBackend::test_unsqueeze, test/test_jit.py::TestNnapiBackend::test_upsample_nearest2d, test/test_jit.py::TestList::test_comprehension_out_type_not_in_type, test/test_jit.py::TestList::test_comprehensions_basic, test/test_jit.py::TestList::test_comprehensions_basic_float, test/test_jit.py::TestList::test_copy_list_mutable, test/test_jit.py::TestList::test_dict_keyword_is_correctly_typed, test/test_jit.py::TestList::test_dict_keyword_with_dict_comprehension_and_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_empty_iterable, test/test_jit.py::TestList::test_dict_keyword_with_iterable, test/test_jit.py::TestList::test_dict_keyword_with_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_kwargs_using_container_values, test/test_jit.py::TestList::test_dict_keyword_with_mapping_and_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_previously_declared_variable, test/test_jit.py::TestList::test_list_count_not_existing, test/test_jit.py::TestList::test_list_len, test/test_jit.py::TestList::test_list_none, test/test_jit.py::TestList::test_list_ops, test/test_jit.py::TestList::test_list_slice, test/test_jit.py::TestList::test_list_sort, test/test_jit.py::TestList::test_list_variance, test/test_jit.py::TestList::test_min_bool_list, test/test_jit.py::TestList::test_min_max_single_list, test/test_jit.py::TestList::test_mutable_list_append_if, test/test_jit.py::TestList::test_mutable_list_append_loop, test/test_jit.py::TestList::test_mutable_list_append_loop_if, test/test_jit.py::TestList::test_mutable_list_clear, test/test_jit.py::TestList::test_mutable_list_clear_empty, test/test_jit.py::TestList::test_mutable_list_insert, test/test_jit.py::TestList::test_mutable_list_insert_neg_out_of_bounds, test/test_jit.py::TestList::test_mutable_list_insert_negative, test/test_jit.py::TestList::test_mutable_list_nested_loop, test/test_jit.py::TestList::test_mutable_list_pop2, test/test_jit.py::TestList::test_mutable_list_pop_at, test/test_jit.py::TestList::test_mutable_list_pop_at_negative, test/test_jit.py::TestList::test_mutable_list_pop_slice, test/test_jit.py::TestList::test_mutable_list_remove_tensor, test/test_jit.py::TestList::test_mutable_list_reverse_empty, test/test_jit.py::TestList::test_no_element_type_annotation, test/test_jit.py::TestList::test_tensor_list_count_not_existing, test/test_jit.py::TestList::test_tensor_list_index_not_existing, test/test_jit.py::TestList::test_to_list_gpu, test/test_jit.py::TestDict::test_copy, test/test_jit.py::TestDict::test_del, test/test_jit.py::TestDict::test_dict_preserves_order, test/test_jit.py::TestDict::test_dict_to_python, test/test_jit.py::TestDict::test_keys, test/test_jit.py::TestDict::test_len, test/test_jit.py::TestDict::test_loop, test/test_jit.py::TestDict::test_optional_dict_construct, test/test_jit.py::TestDict::test_pop, test/test_jit.py::TestDict::test_popitem, test/test_jit.py::TestDict::test_update_existing_key, test/test_jit.py::TestDict::test_values, test/test_jit.py::TestNamedTuple::test_namedtuple, test/test_jit.py::TestNamedTuple::test_namedtuple_as_attr, test/test_jit.py::TestNamedTuple::test_namedtuple_constant, test/test_jit.py::TestNamedTuple::test_namedtuple_kwarg_construct, test/test_jit.py::TestNamedTuple::test_namedtuple_lower, test/test_jit.py::TestNamedTuple::test_namedtuple_resolution, test/test_jit.py::TestNamedTuple::test_namedtuple_resolution_forwardref, test/test_jit.py::TestNamedTuple::test_namedtuple_slice_unpack, test/test_jit.py::TestNamedTuple::test_namedtuple_wrong_types, test/test_jit.py::TestScriptDict::test_items, test/test_jit.py::TestScriptDict::test_reference_semantics, test/test_jit.py::TestScriptDict::test_setitem, test/test_jit.py::TestScriptList::test_append, test/test_jit.py::TestScriptList::test_bool, test/test_jit.py::TestScriptList::test_contains, test/test_jit.py::TestScriptList::test_count, test/test_jit.py::TestScriptList::test_defaultdict, test/test_jit.py::TestScriptList::test_extend, test/test_jit.py::TestScriptList::test_getitem, test/test_jit.py::TestScriptList::test_insert, test/test_jit.py::TestScriptList::test_nested, test/test_jit.py::TestScriptList::test_reference_semantics, test/test_jit.py::TestScriptList::test_remove, test/test_jit.py::TestScriptList::test_repr, test/test_jit.py::TestAsync::test_async_future_type_python, test/test_jit.py::TestAsync::test_async_grad_guard_no_grad, test/test_jit.py::TestAsync::test_async_python, test/test_jit.py::TestAsync::test_async_script_capture, test/test_jit.py::TestAsync::test_async_script_error, test/test_jit.py::TestAsync::test_no_future_subtype_message, test/test_jit.py::TestAsync::test_trace_fork_wait, test/test_jit.py::TestAsync::test_trace_fork_wait_inline, test/test_jit.py::TestAsync::test_trace_fork_wait_leaking, test/test_jit.py::TestAsync::test_trace_modulecalls_with_different_output_types, test/test_jit.py::TestAwait::test_await_class_arg, test/test_jit.py::TestAwait::test_await_eager_lazy, test/test_jit.py::TestAwait::test_await_getattr_implicit_convertion, test/test_jit.py::TestAwait::test_await_isinstance, test/test_jit.py::TestAwait::test_await_python, test/test_jit.py::TestAwait::test_await_type_python, test/test_jit.py::TestAwait::test_awaitable_to_await, test/test_jit.py::TestAwait::test_nowait, test/test_jit.py::TestAwait::test_script, test/test_jit.py::TestDataParallel::test_tensor_sharing_with_forward, test/test_jit.py::TestModels::test_alexnet, test/test_jit.py::TestModels::test_dcgan_models, test/test_jit.py::TestModels::test_neural_style_cuda, test/test_jit.py::TestModels::test_reinforcement_learning_cuda, test/test_jit.py::TestModels::test_script_module_script_resnet, test/test_jit.py::TestModels::test_snli, test/test_jit.py::TestModels::test_super_resolution, test/test_jit.py::TestModels::test_time_sequence_prediction, test/test_jit.py::TestAutodiffJit::test_autodiff_requires_grad_nograd, test/test_jit.py::TestAutodiffJit::test_requires_grad_outputs_profiled_twice, test/test_jit.py::TestAutodiffJit::test_requires_grad_outputs_side_effects, test/test_jit.py::TestAutodiffSubgraphSlicing::test_bias_as_arg, test/test_jit.py::TestAutodiffSubgraphSlicing::test_chunk_constant_script_ad, test/test_jit.py::TestAutodiffSubgraphSlicing::test_constructed_bias, test/test_jit.py::TestAutodiffSubgraphSlicing::test_diff_graph_inline_threshold, test/test_jit.py::TestAutodiffSubgraphSlicing::test_differentiable_graph_ops_requires_grad, test/test_jit.py::TestAutodiffSubgraphSlicing::test_does_not_create_cycles, test/test_jit.py::TestAutodiffSubgraphSlicing::test_does_not_merge_unrelated, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merge_respects_aliasing, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merges_dense, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merges_up, test/test_jit.py::TestAutodiffSubgraphSlicing::test_prune_grad, test/test_jit.py::TestAutodiffSubgraphSlicing::test_requires_grad_for_tensor_list, test/test_jit.py::TestAutodiffSubgraphSlicing::test_simple_merge, test/test_jit.py::TestAutodiffSubgraphSlicing::test_simple_no_merge, test/test_jit.py::TestCustomOperators::test_getting_invalid_attr, test/test_jit.py::TestCustomOperators::test_passing_and_returning_lists, test/test_jit.py::TestCustomOperators::test_passing_one_positional_but_not_the_second, test/test_jit.py::TestCustomOperators::test_script_graph_for_custom_ops_matches_traced_graph, test/test_jit.py::TestCustomOperators::test_where_no_scalar, test/test_jit.py::TestGraphRewritePasses::test_fuse_linear, test/test_jit.py::TestClassType::test_cast_overloads, test/test_jit.py::TestClassType::test_class_constant, test/test_jit.py::TestClassType::test_class_constructs_itself, test/test_jit.py::TestClassType::test_class_sorting, test/test_jit.py::TestClassType::test_class_specialization, test/test_jit.py::TestClassType::test_conditional_set_attr, test/test_jit.py::TestClassType::test_custom_delete, test/test_jit.py::TestClassType::test_default_args, test/test_jit.py::TestClassType::test_get_attr, test/test_jit.py::TestClassType::test_get_with_method, test/test_jit.py::TestClassType::test_imported_classes, test/test_jit.py::TestClassType::test_in, test/test_jit.py::TestClassType::test_init_compiled_first, test/test_jit.py::TestClassType::test_optional_type_promotion, test/test_jit.py::TestClassType::test_properties, test/test_jit.py::TestClassType::test_recursive_class, test/test_jit.py::TestClassType::test_recursive_script_builtin_type_resolution, test/test_jit.py::TestClassType::test_recursive_scripting, test/test_jit.py::TestClassType::test_recursive_scripting_failed, test/test_jit.py::TestClassType::test_save_load_with_classes, test/test_jit.py::TestClassType::test_save_load_with_classes_returned, test/test_jit.py::TestClassType::test_set_attr_in_method, test/test_jit.py::TestClassType::test_set_attr_non_initialized, test/test_jit.py::TestClassType::test_staticmethod, test/test_jit.py::TestClassType::test_type_annotation, test/test_jit.py::TestClassType::test_type_annotations, test/test_jit.py::TestClassType::test_unresolved_class_attributes, test/test_jit.py::TestBuiltins::test_del_multiple_operands, test/test_jit.py::TestBuiltins::test_has_attr_invalid_args, test/test_jit.py::TestTensorBuiltins::test_method_on_number, test/test_jit.py::TestTensorBuiltins::test_tensor_item, test/test_jit.py::TestTensorBuiltins::test_tensor_properties, test/test_jit.py::TestTensorBuiltins::test_tensor_subscript_assign, test/test_jit.py::TestTensorBuiltins::test_tensor_subscript_assign_device, test/test_jit.py::TestIgnoreContextManager::test_with_ignore_context_manager_with_just_inp, test/test_jit.py::TestIgnoreContextManager::test_with_ignore_context_manager_with_just_out, test/test_jit.py::TestSymbolicShapeAnalysis::test_arange_shape, test/test_jit.py::TestSymbolicShapeAnalysis::test_binary_shape_functions, test/test_jit.py::TestSymbolicShapeAnalysis::test_partial_eval_graph_conv, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_analysis, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_function_includes, test/test_jit.py::TestSymbolicShapeAnalysis::test_shared_shape_graph, test/test_jit.py::TestSymbolicShapeAnalysis::test_squeeze_dims, test/test_jit.py::TestSymbolicShapeAnalysis::test_sym_ir_parsing, test/test_jit.py::TestSymbolicShapeAnalysis::test_unary_shape_fns_inplace, test/test_jit.py::TestFreezing::test_freeze_interface_within_object, test/test_jit.py::TestFreezing::test_freeze_module_detach_gradient, test/test_jit.py::TestFreezing::test_freeze_module_in_training_mode, test/test_jit.py::TestFreezing::test_freeze_module_return_sub_module, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr2, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr3, test/test_jit.py::TestFreezing::test_freeze_module_with_fork2, test/test_jit.py::TestFreezing::test_freeze_module_with_inplace_mutable, test/test_jit.py::TestFreezing::test_freeze_module_with_mutable_list, test/test_jit.py::TestFreezing::test_freeze_module_with_mutable_tensor, test/test_jit.py::TestFreezing::test_freeze_module_with_nestedaliasing, test/test_jit.py::TestFreezing::test_freeze_module_with_nestedaliasingscalar, test/test_jit.py::TestFreezing::test_freeze_module_with_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_tuple, test/test_jit.py::TestFreezing::test_freeze_module_with_tupleoutput_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method2, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method_on_submodule, test/test_jit.py::TestFreezing::test_freeze_recursive_interfaces_with_reassignment, test/test_jit.py::TestFreezing::test_module_getattr_indirection, test/test_jit.py::TestFrozenOptimizations::test_collapse_adjacent_conversions, test/test_jit.py::TestFrozenOptimizations::test_conv_add_folding, test/test_jit.py::TestFrozenOptimizations::test_conv_bn_folding_not_forward, test/test_jit.py::TestFrozenOptimizations::test_conv_mul_add_bn, test/test_jit.py::TestFrozenOptimizations::test_conv_to_mkldnn, test/test_jit.py::TestFrozenOptimizations::test_freeze_conv_relu_fusion, test/test_jit.py::TestFrozenOptimizations::test_freeze_conv_relu_fusion_not_forward, test/test_jit.py::TestFrozenOptimizations::test_freeze_remove_dropout, test/test_jit.py::TestFrozenOptimizations::test_freeze_remove_feature_dropout, test/test_jit.py::TestFrozenOptimizations::test_hardswish_hardsigmoid, test/test_jit.py::TestFrozenOptimizations::test_incompatible_perf_formats, test/test_jit.py::TestFrozenOptimizations::test_linear_bn_folding, test/test_jit.py::TestFrozenOptimizations::test_linear_bn_folding_autocast_scenario_cuda, test/test_jit.py::TestFrozenOptimizations::test_linear_concat_different_input, test/test_jit.py::TestFrozenOptimizations::test_linear_multiple_blocks, test/test_jit.py::TestFrozenOptimizations::test_linear_non_constant_weight, test/test_jit.py::TestFrozenOptimizations::test_mkldnn_fuser_broadcasting, test/test_jit.py::TestFrozenOptimizations::test_numel_less_than_size_with_padding, test/test_jit.py::TestFrozenOptimizations::test_remove_detach, test/test_jit.py::TestFrozenOptimizations::test_remove_detach_not_applied, test/test_jit.py::TestMKLDNNReinplacing::test_always_alive_values, test/test_jit.py::TestMKLDNNReinplacing::test_successful, test/test_jit.py::TestPeephole::test_conv_dim_folding, test/test_jit.py::TestPeephole::test_integer_refinement, test/test_jit.py::TestPeephole::test_noop_peephole, test/test_jit.py::TestPeephole::test_normalized_is_op, test/test_jit.py::TestPeephole::test_normalized_rsub, test/test_jit.py::TestPeephole::test_optimize_out_comparison_same_value, test/test_jit.py::TestPeephole::test_peephole, test/test_jit.py::TestPeephole::test_peephole_arith, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_dict_modified, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_get_input_arg, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_keys_might_overlap, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_missing_key, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_unsupported_type, test/test_jit.py::TestPeephole::test_peephole_dict_len, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_keys_might_overlap, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_overlapping_keys, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_unsupported_type, test/test_jit.py::TestPeephole::test_peephole_dynamic, test/test_jit.py::TestPeephole::test_peephole_int, test/test_jit.py::TestPeephole::test_peephole_list_ops, test/test_jit.py::TestPeephole::test_peephole_no_output_aliasing, test/test_jit.py::TestPeephole::test_peephole_slice_optimization_not_applied_non_const_args, test/test_jit.py::TestPeephole::test_peephole_with_non_output_writes, test/test_jit.py::TestPeephole::test_peephole_with_writes, test/test_jit.py::TestPeephole::test_refine_integer_values, test/test_jit.py::TestAliasAnalysis::test_multiple_compilation_units, test/test_jit.py::TestAliasAnalysis::test_nested_list_construct_not_wildcard, test/test_jit.py::TestAliasAnalysis::test_recursive_calls, test/test_jit.py::TestSaveLoad::test_different_functions, test/test_jit.py::TestSaveLoad::test_save_load_meta_tensors_to_device, test/test_jit.py::TestSaveLoad::test_save_load_params_buffers_submodules, test/test_jit.py::TestSaveLoad::test_save_load_with_extra_files, test/test_jit.py::TestSaveLoad::test_save_namedtuple_input_only, test/test_jit.py::TestSaveLoad::test_save_namedtuple_input_only_forwardref, test/test_jit.py::TestSaveLoad::test_save_namedtuple_output_only, test/test_jit.py::TestSaveLoad::test_save_nonexit_file, test/test_jit.py::TestSaveLoadFlatbuffer::test_different_functions, test/test_jit.py::TestSaveLoadFlatbuffer::test_different_interfaces, test/test_jit.py::TestSaveLoadFlatbuffer::test_many_collisions, test/test_jit.py::TestSaveLoadFlatbuffer::test_module_info_flatbuffer, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_load_with_extra_files, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_namedtuple_input_only, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_namedtuple_output_only, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar_inplace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar_scalar, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_tensor, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_tensor_out, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_linspace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_linspace_out, test/test_jit.py::TestModuleContainers::test_custom_container_forward, test/test_jit.py::TestModuleContainers::test_empty_dict_override_contains, test/test_jit.py::TestModuleContainers::test_moduledict, test/test_jit.py::TestModuleContainers::test_moduledict_getitem, test/test_jit.py::TestModuleContainers::test_moduledict_keyerror, test/test_jit.py::TestModuleContainers::test_normal_list_attribute_with_modules_error, test/test_jit.py::TestModuleContainers::test_parameterdict_script_getitem, test/test_jit.py::TestModuleContainers::test_parameterlist_script_iter, test/test_jit.py::TestModuleContainers::test_typed_module_dict, test/test_jit.py::TestModuleContainers::test_typed_module_list, test/test_jit.py::TestPythonBindings::test_add_input, test/test_jit.py::TestPythonBindings::test_cu_create_function, test/test_jit.py::TestPythonBindings::test_graph_iterator_keepalive, test/test_jit.py::TestPythonBindings::test_invalidation, test/test_jit.py::TestPythonIr::test_python_ir_utils, test/test_jit.py::TestPythonIr::test_python_ir_utils_graph, test/test_jit.py::TestRemoveMutation::test_aten_inplace, test/test_jit.py::TestRemoveMutation::test_if_output, test/test_jit.py::TestRemoveMutation::test_list_indexing_removal, test/test_jit.py::TestRemoveMutation::test_lists_append, test/test_jit.py::TestTorchbind::test_hasattr, test/test_jit.py::TestTorchbind::test_lambda_as_constructor, test/test_jit.py::TestTorchbind::test_torchbind_attr_exception, test/test_jit.py::TestTorchbind::test_torchbind_class_attribute, test/test_jit.py::TestTorchbind::test_torchbind_def_property_getter_setter, test/test_jit.py::TestTorchbind::test_torchbind_def_property_just_getter, test/test_jit.py::TestTorchbind::test_torchbind_lambda_method, test/test_jit.py::TestTorchbind::test_torchbind_take_as_arg, test/test_jit.py::TestTorchbind::test_torchbind_take_instance_as_method_arg, test/test_jit.py::TestTorchbind::test_torchbind_tracing, test/test_jit.py::TestModuleInterface::test_freeze_module_with_interface, test/test_jit.py::TestModuleInterface::test_freeze_module_with_mutated_interface, test/test_jit.py::TestModuleInterface::test_module_apis_interface, test/test_jit.py::TestModuleInterface::test_module_doc_string, test/test_jit.py::TestModuleInterface::test_module_interface, test/test_jit.py::TestModuleInterface::test_module_interface_inheritance, test/test_jit.py::TestModuleInterface::test_module_swap, test/test_jit.py::TestModuleInterface::test_module_swap_no_module_interface, test/test_jit.py::TestModuleInterface::test_module_swap_wrong_module, test/test_jit.py::TestModuleInterface::test_not_submodule_interface_call, test/test_jit.py::TestWith::test_with_errors, test/test_jit.py::TestWith::test_with_record_function, test/test_jit.py::TestEnum::test_enum_as_const, test/test_jit.py::TestEnum::test_enum_comp_diff_classes, test/test_jit.py::TestEnum::test_enum_explicit_script, test/test_jit.py::TestEnum::test_enum_iterate, test/test_jit.py::TestEnum::test_enum_value, test/test_jit.py::TestEnum::test_non_existent_enum_value, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_char_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_char_placeholder_and_true_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_digit_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_digit_placeholder_and_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_float_placeholder_and_float_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_multiple_placeholders, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_percent_in_string, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_string_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_string_placeholder_and_format_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_too_few_arguments, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_unknown_format_specifier, test/test_jit.py::TestProfiler::test_aliasing_merge, test/test_jit.py::TestProfiler::test_autograd_fallback_graph, test/test_jit.py::TestProfiler::test_fallback_graph_not_specialized, test/test_jit.py::TestProfiler::test_iterative_fusion, test/test_jit.py::TestProfiler::test_local_fusion_strategy, test/test_jit.py::TestProfiler::test_not_optimizing_property, test/test_jit.py::TestProfiler::test_tensor_constant, test/test_jit.py::TestProfiler::test_tensor_type_not_determined_by_inputs, test/test_jit.py::TestProfiler::test_use_not_profiled, test/test_jit.py::TestSlice::test_slice_dynamic_index, test/test_jit.py::TestSlice::test_slice_kwarg, test/test_jit.py::TestSlice::test_slice_one_none, test/test_jit.py::TestSlice::test_slice_stop_only_with_nones, test/test_jit.py::TestSlice::test_slice_string, test/test_jit.py::TestSlice::test_slice_tensor_multidim, test/test_jit.py::TestSlice::test_slice_three_nones, test/test_jit.py::TestSlice::test_tuple_slicing, test/test_jit.py::TestIgnorableArgs::test_add_out_ignorable_args, test/test_jit.py::TestIgnorableArgs::test_slice_ignorable_args_for_slice, test/test_jit.py::TestHooks::test_hook_compilation_hint, test/test_jit.py::TestHooks::test_hook_method_name_collision, test/test_jit.py::TestHooks::test_module_forward_multiple_inputs, test/test_jit.py::TestHooks::test_module_forward_single_input, test/test_jit.py::TestHooks::test_module_hook_return_nothing, test/test_jit.py::TestHooks::test_module_multiple_hooks_multiple_inputs, test/test_jit.py::TestHooks::test_module_multiple_hooks_single_input, test/test_jit.py::TestHooks::test_submodule_called_directly_with_hooks, test/test_jit.py::TestHooks::test_submodule_forward_multiple_inputs, test/test_jit.py::TestHooks::test_submodule_forward_single_input, test/test_jit.py::TestHooks::test_submodule_same_hook_repeated, test/test_jit.py::TestWarn::test_warn_once_per_func, test/test_jit.py::TestWarn::test_warn_only_once, test/test_jit.py::TestWarn::test_warn_only_once_in_loop_func, test/test_jit.py::TestIsinstance::test_dict_nested, test/test_jit.py::TestIsinstance::test_dict_tensor, test/test_jit.py::TestIsinstance::test_in_while_loop, test/test_jit.py::TestIsinstance::test_list, test/test_jit.py::TestIsinstance::test_list_nested, test/test_jit.py::TestIsinstance::test_list_no_contained_type, test/test_jit.py::TestIsinstance::test_list_tensor, test/test_jit.py::TestIsinstance::test_nontuple_container_rhs_throws_in_eager, test/test_jit.py::TestIsinstance::test_optional, test/test_jit.py::TestIsinstance::test_optional_nested, test/test_jit.py::TestIsinstance::test_optional_no_contained_type, test/test_jit.py::TestIsinstance::test_tensor_type_false, test/test_jit.py::TestIsinstance::test_tuple, test/test_jit.py::TestPythonBuiltinOP::test_advancedindex, test/test_jit.py::TestPythonBuiltinOP::test_matmul_py3, test/test_jit.py::TestPythonBuiltinOP::test_mul, test/test_jit.py::TestPythonBuiltinOP::test_stepped_tuple_slicing, test/test_jit.py::TestPythonBuiltinOP::test_str_to_float, test/test_jit.py::TestPythonBuiltinOP::test_triple, test/test_jit.py::TestTyping::test_dict_comprehension_scope, test/test_jit.py::TestTyping::test_dict_in_not_in, test/test_jit.py::TestTyping::test_dict_invalid_annotations, test/test_jit.py::TestTyping::test_dict_type_refinement_annotation_key_mismatch, test/test_jit.py::TestTyping::test_dict_type_refinement_annotation_value_mismatch, test/test_jit.py::TestTyping::test_for_in_dict, test/test_jit.py::TestTyping::test_for_in_string, test/test_jit.py::TestTyping::test_for_tuple_unpack, test/test_jit.py::TestTyping::test_inherited_annotations_python_310, test/test_jit.py::TestTyping::test_list_io, test/test_jit.py::TestTyping::test_list_type_refinement_annotation_element_mismatch, test/test_jit.py::TestTyping::test_multiple_assign, test/test_jit.py::TestTyping::test_namedtuple_error_source_attribution, test/test_jit.py::TestTyping::test_namedtuple_good_error, test/test_jit.py::TestTyping::test_namedtuple_redefine, test/test_jit.py::TestTyping::test_nested_list, test/test_jit.py::TestTyping::test_singleton_tuple_unpack, test/test_jit.py::TestTyping::test_sum_list_diff_elms, test/test_jit.py::TestTyping::test_sum_list_literal, test/test_jit.py::TestTyping::test_tuple_create_return, test/test_jit.py::TestTyping::test_tuple_io, test/test_jit.py::TestTyping::test_tuple_keyword, test/test_jit.py::TestTyping::test_tuple_specialization, test/test_jit.py::TestHash::test_hash_float, test/test_jit.py::TestHash::test_hash_int, test/test_jit.py::TestHash::test_hash_none, test/test_jit.py::TestHash::test_hash_string, test/test_jit.py::TestHash::test_hash_tuple_nested_unhashable_type, test/test_jit.py::TestComplex::test_binary_op_complex_tensor, test/test_jit.py::TestComplex::test_complex_constants_and_ops, test/test_jit.py::TestComplex::test_complex_constructor, test/test_jit.py::TestComplex::test_complex_parse, test/test_jit.py::TestComplex::test_complexdict, test/test_jit.py::TestComplex::test_infj_nanj_pickle, test/test_jit.py::TestComplex::test_torch_complex_constructor_with_tensor, test/test_jit.py::TestJitUtils::test_checkscriptassertraisesregex, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_hybrid, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_keyword_only, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_positional_only, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_positional_or_keyword, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_var_positional, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_class_level_jit_annotation, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_list, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_list_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_optional, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_tensor, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_falsy_base_type, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_nonempty_container, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_attribute, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_dict, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_list, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_list_lowercase, test/test_jit.py::TestTypesAndAnnotation::test_ignore_with_types, test/test_jit.py::TestTypesAndAnnotation::test_ignoring_fn_with_nonscriptable_types, test/test_jit.py::TestTypesAndAnnotation::test_ignoring_module_attributes, test/test_jit.py::TestTypesAndAnnotation::test_inferred_type_error_message, test/test_jit.py::TestTypesAndAnnotation::test_optional_no_element_type_annotation, test/test_jit.py::TestTypesAndAnnotation::test_parser_bug, test/test_jit.py::TestTypesAndAnnotation::test_pep585_type, test/test_jit.py::TestTypesAndAnnotation::test_type_annotate_py3, test/test_jit.py::TestMisc::test_broadcasting_list, test/test_jit.py::TestMisc::test_export_opnames_interface, test/test_jit.py::TestMisc::test_future_isinstance, test/test_jit.py::TestMisc::test_hacked_twin, test/test_jit.py::TestMisc::test_jit_get_operation_order, test/test_jit.py::TestMisc::test_kwarg_support, test/test_jit.py::TestMisc::test_legacy_tensor_constructor, test/test_jit.py::TestMisc::test_math_inf, test/test_jit.py::TestMisc::test_parse_ir_single_element_tensor_negative, test/test_jit.py::TestMisc::test_parse_ir_single_element_tensor_positive, 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test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_nn_functional_conv2d_cpu_int64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_nn_functional_conv_transpose2d_cpu_complex64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_nn_functional_conv_transpose2d_cpu_int64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_nn_functional_hardswish_cpu_bfloat16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_nn_functional_hardswish_cpu_float32, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_nn_functional_max_pool1d_cpu_bfloat16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_nn_functional_max_pool1d_cpu_float16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_nn_functional_max_pool1d_cpu_float32, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_nn_functional_max_pool1d_cpu_float64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_nn_functional_max_pool2d_cpu_bfloat16, 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test/test_jit.py::TestDeviceAnalysis::test_custom_device_op, test/test_jit.py::TestDeviceAnalysis::test_device_apply, test/test_jit.py::TestDeviceAnalysis::test_device_arg, test/test_jit.py::TestDeviceAnalysis::test_if_loop_mix, test/test_jit.py::TestDeviceAnalysis::test_mobilenet, test/test_jit.py::TestDeviceAnalysis::test_nested_loops, test/test_jit.py::TestDeviceAnalysis::test_set_dtype, test/test_jit.py::TestDCE::test_mutated_simple, test/test_jit.py::TestDCE::test_setattr_no_aliasdb, test/test_jit.py::TestDCE::test_setattr_removed, test/test_jit.py::TestSparse::test_freeze_sparse_coo, test/test_jit.py::TestSparse::test_freeze_sparse_csr, test/test_jit.py::TestSparse::test_serialize_sparse_coo, test/test_jit.py::TestTensorMethods::test_getitem, test/test_jit.py::TestTensorMethods::test_getitem_invalid, test/test_jit.py::TestDataclasses::test__post_init__, test/test_jit.py::TestDataclasses::test_comparators, test/test_jit.py::TestDataclasses::test_custom__eq__, test/test_jit.py::TestDataclasses::test_no_source, test/test_jit.py::TestDataclasses::test_use_unregistered_dataclass_raises, test/test_jit.py::TestGenerator::test_save_load, test/test_jit.py::TestGenerator::test_trace, test/test_jit.py::TestJit::test_Sequential, test/test_jit.py::TestJit::test_T_mT_H_mH, test/test_jit.py::TestJit::test_attrs, test/test_jit.py::TestJit::test_big, test/test_jit.py::TestJit::test_constant_insertion, test/test_jit.py::TestJit::test_constant_prop_aliasing_type, test/test_jit.py::TestJit::test_constant_prop_exception, test/test_jit.py::TestJit::test_constant_prop_if_inline, test/test_jit.py::TestJit::test_constant_prop_none, test/test_jit.py::TestJit::test_constant_prop_print, test/test_jit.py::TestJit::test_constants_pkl, test/test_jit.py::TestJit::test_cpp, test/test_jit.py::TestJit::test_cse, test/test_jit.py::TestJit::test_cse_not_introduce_aliasing, test/test_jit.py::TestJit::test_cu_escaped_number, test/test_jit.py::TestJit::test_cuda_export_restore, test/test_jit.py::TestJit::test_debug_flush_compilation_cache, test/test_jit.py::TestJit::test_diff_subgraph_clones_constants, test/test_jit.py::TestJit::test_dropout, test/test_jit.py::TestJit::test_dropout_cuda, test/test_jit.py::TestJit::test_einsum, test/test_jit.py::TestJit::test_element_size, test/test_jit.py::TestJit::test_export_lstm, test/test_jit.py::TestJit::test_export_opnames, test/test_jit.py::TestJit::test_export_rnn, test/test_jit.py::TestJit::test_flags, test/test_jit.py::TestJit::test_function_default_values, test/test_jit.py::TestJit::test_hide_source_ranges_context_manager, test/test_jit.py::TestJit::test_inferred_as_tensor, test/test_jit.py::TestJit::test_layout, test/test_jit.py::TestJit::test_matrix_transpose, test/test_jit.py::TestJit::test_nn_conv, test/test_jit.py::TestJit::test_nn_lp_pool2d, test/test_jit.py::TestJit::test_nn_padding, test/test_jit.py::TestJit::test_nn_padding_functional, test/test_jit.py::TestJit::test_no_erroneous_warnings, 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test/test_jit.py::TestScript::test_wrong_use_as_tuple, test/test_jit.py::TestScript::test_zero_dimension_tensor_trace, test/test_jit.py::TestScript::test_zeros, test/test_jit.py::TestScript::test_zip_enumerate_modulelist, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_weights_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_weights_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_Bilinear, test/test_jit.py::TestJitGeneratedModule::test_nn_CELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad1size1, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad_same, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad_same2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad_valid, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_reflect_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_replicate_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_zeros_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_depthwise_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_depthwise_strided, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_groups_thnn, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_pad_same_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_pad_valid, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_padding, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_reflect_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_replicate_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_strided, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_zero_batch, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_dilated_strided, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_pad_same, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_replicate_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_zero_batch, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose3d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_CosineEmbeddingLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_CrossMapLRN2d, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_discontiguous, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_max, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_mean_padding_idx, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_Embedding_discontiguous, test/test_jit.py::TestJitGeneratedModule::test_nn_Flatten, test/test_jit.py::TestJitGeneratedModule::test_nn_Flatten_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold_no_batch_dim_input, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold_no_batch_dim_int_input, test/test_jit.py::TestJitGeneratedModule::test_nn_GELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_GLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Hardshrink_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Hardswish_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_delta, test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce_scalar_log_target, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_with_log_target_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_LayerNorm_3d_no_affine_large_feature, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_LogSigmoid_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_MarginRankingLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_Mish_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_0d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_1d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_weights_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_1d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_p_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiheadAttention, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLossNd_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_weights, test/test_jit.py::TestJitGeneratedModule::test_nn_PReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_broadcast_rhs, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_with_non_default_args, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_RNNCell, test/test_jit.py::TestJitGeneratedModule::test_nn_ReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_ReplicationPad3d, test/test_jit.py::TestJitGeneratedModule::test_nn_Sigmoid_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_zero_beta, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_Softplus_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Tanh_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Tanhshrink_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Threshold_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerDecoderLayer_relu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerEncoderLayer_relu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_TripletMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_TripletMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_Unfold, test/test_jit.py::TestJitGeneratedModule::test_nn_Unfold_int_input, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_tuple_skewed_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_tuple_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_2d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_tuple_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_scale_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_tuple_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_1d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_2d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_tuple_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_tuple_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_scale_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_tuple_3d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_dim0, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_spatial, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_spatial_special, test/test_jit.py::TestJitGeneratedModule::test_nn_multimarginloss_1d_input_0d_target_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_spatial, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_spatial_special, test/test_jit.py::TestProducerVersion::test_version 2025-07-17T09:11:01.1665288Z 2025-07-17T09:11:04.2629876Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:11:04.2632740Z import pkg_resources 2025-07-17T09:11:04.3882846Z Running test_serialization 1/1 ... [2025-07-17 09:11:04.387877] 2025-07-17T09:11:04.3883726Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:11:04.3886754Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_serialization.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:11:04.388313] 2025-07-17T09:11:40.6904009Z 2025-07-17T09:11:40.6907838Z torch_np/numpy_tests/fft/test_pocketfft 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.fft.test_pocketfft_1.1_dbd98aa70c962419_.log 2025-07-17T09:11:40.6967992Z Running 79 items in this shard: test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFTShift::test_fft_n, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_all_1d_norm_preserving, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_axes_op0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_axes_op1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_axes_op2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_axes_op3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_dtypes_dtype0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_dtypes_dtype1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_dtypes_dtype2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fftn, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_hfft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_identity, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifft_norm0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifft_norm_backward, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifft_norm_forward, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifft_norm_ortho, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifftn, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ihfft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_irfft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_irfft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_irfftn, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_rfft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_rfft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_rfftn, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFTThreadSafe::test_fft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFTThreadSafe::test_ifft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFTThreadSafe::test_irfft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFTThreadSafe::test_rfft 2025-07-17T09:11:40.7027421Z 2025-07-17T09:11:43.9675857Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:11:43.9678979Z import pkg_resources 2025-07-17T09:11:44.1288957Z Running nn/test_dropout 1/1 ... [2025-07-17 09:11:44.128413] 2025-07-17T09:11:44.1290155Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:11:44.1292440Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_dropout.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:11:44.128821] 2025-07-17T09:12:06.3780710Z 2025-07-17T09:12:06.3782088Z nn/test_dropout 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_dropout_1.1_1b95b13e9274cf8b_.log 2025-07-17T09:12:06.3787943Z Running 9 items in this shard: test/nn/test_dropout.py::TestDropoutNN::test_AlphaDropout, test/nn/test_dropout.py::TestDropoutNN::test_FeatureAlphaDropout, test/nn/test_dropout.py::TestDropoutNN::test_invalid_dropout_p, test/nn/test_dropout.py::TestDropoutNN::test_native_dropout_corner_case, test/nn/test_dropout.py::TestDropoutNNDeviceTypeCPU::test_Dropout1d_cpu_float64, test/nn/test_dropout.py::TestDropoutNNDeviceTypeCPU::test_Dropout2d_cpu, test/nn/test_dropout.py::TestDropoutNNDeviceTypeCPU::test_Dropout3d_cpu, test/nn/test_dropout.py::TestDropoutNNDeviceTypeCPU::test_Dropout_cpu, test/nn/test_dropout.py::TestDropoutNNDeviceTypeCPU::test_empty_dropout_cpu 2025-07-17T09:12:06.3791978Z 2025-07-17T09:12:09.7314223Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:12:09.7317109Z import pkg_resources 2025-07-17T09:12:09.8563527Z Running test_dynamic_shapes 1/1 ... [2025-07-17 09:12:09.855886] 2025-07-17T09:12:09.8564626Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:12:09.8566703Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_dynamic_shapes.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:12:09.856274] 2025-07-17T09:12:36.4626711Z 2025-07-17T09:12:36.4628099Z test_dynamic_shapes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_dynamic_shapes_1.1_5727f4b6436df7a7_.log 2025-07-17T09:12:36.4762913Z Running 330 items in this shard: test/test_dynamic_shapes.py::TestPySymInt::test_arith_ops, test/test_dynamic_shapes.py::TestPySymInt::test_aten_ops, test/test_dynamic_shapes.py::TestPySymInt::test_avoid_unbacked_substitution, test/test_dynamic_shapes.py::TestPySymInt::test_backed_size_oblivious_01_spec, test/test_dynamic_shapes.py::TestPySymInt::test_baddbmm_symint, test/test_dynamic_shapes.py::TestPySymInt::test_binary, test/test_dynamic_shapes.py::TestPySymInt::test_data_dependent_guard, test/test_dynamic_shapes.py::TestPySymInt::test_data_dependent_guard_propagate_real_tensors, test/test_dynamic_shapes.py::TestPySymInt::test_debug_has_internal_overlap_unbacked, test/test_dynamic_shapes.py::TestPySymInt::test_deepcopy, test/test_dynamic_shapes.py::TestPySymInt::test_duck_shape, test/test_dynamic_shapes.py::TestPySymInt::test_ephemeral_source_simplification, test/test_dynamic_shapes.py::TestPySymInt::test_ephemeral_source_unified_with_non_ephemeral_source, test/test_dynamic_shapes.py::TestPySymInt::test_expect_true_basic, test/test_dynamic_shapes.py::TestPySymInt::test_expect_true_double_digits, test/test_dynamic_shapes.py::TestPySymInt::test_expect_true_prefer_later, test/test_dynamic_shapes.py::TestPySymInt::test_expect_true_refine_range, test/test_dynamic_shapes.py::TestPySymInt::test_expect_true_with_s0, test/test_dynamic_shapes.py::TestPySymInt::test_floor_clean_div_axioms, test/test_dynamic_shapes.py::TestPySymInt::test_floordiv_static, test/test_dynamic_shapes.py::TestPySymInt::test_fx_trace_intlist, test/test_dynamic_shapes.py::TestPySymInt::test_guard_int, test/test_dynamic_shapes.py::TestPySymInt::test_guard_refine_range, test/test_dynamic_shapes.py::TestPySymInt::test_int_bool, test/test_dynamic_shapes.py::TestPySymInt::test_int_conversion, test/test_dynamic_shapes.py::TestPySymInt::test_int_to_float, test/test_dynamic_shapes.py::TestPySymInt::test_max_of_unique_summation_opt, test/test_dynamic_shapes.py::TestPySymInt::test_meta_symint, test/test_dynamic_shapes.py::TestPySymInt::test_mul_int_oo_nan, test/test_dynamic_shapes.py::TestPySymInt::test_non_overlapping_and_dense, test/test_dynamic_shapes.py::TestPySymInt::test_non_overlapping_and_dense_unbacked, test/test_dynamic_shapes.py::TestPySymInt::test_numel, test/test_dynamic_shapes.py::TestPySymInt::test_numpy_sym_max, test/test_dynamic_shapes.py::TestPySymInt::test_numpy_sym_min, test/test_dynamic_shapes.py::TestPySymInt::test_prefer_deferred_runtime_assertions_over_guards, test/test_dynamic_shapes.py::TestPySymInt::test_print_readable_with_symints, test/test_dynamic_shapes.py::TestPySymInt::test_reverse_arith_ops, test/test_dynamic_shapes.py::TestPySymInt::test_roundtrip, test/test_dynamic_shapes.py::TestPySymInt::test_size_expressions, test/test_dynamic_shapes.py::TestPySymInt::test_specialize_zero_one, test/test_dynamic_shapes.py::TestPySymInt::test_statically_known_false, test/test_dynamic_shapes.py::TestPySymInt::test_statically_known_true, test/test_dynamic_shapes.py::TestPySymInt::test_stride, test/test_dynamic_shapes.py::TestPySymInt::test_sym_ceil, test/test_dynamic_shapes.py::TestPySymInt::test_sym_floor, test/test_dynamic_shapes.py::TestPySymInt::test_sym_int, test/test_dynamic_shapes.py::TestPySymInt::test_sym_ite, test/test_dynamic_shapes.py::TestPySymInt::test_sym_log2, test/test_dynamic_shapes.py::TestPySymInt::test_sym_max_multi_max_simplify, test/test_dynamic_shapes.py::TestPySymInt::test_sym_sqrt, test/test_dynamic_shapes.py::TestPySymInt::test_sym_sum, test/test_dynamic_shapes.py::TestPySymInt::test_sym_trunc, test/test_dynamic_shapes.py::TestPySymInt::test_symint_args, test/test_dynamic_shapes.py::TestPySymInt::test_symint_as_scalar, test/test_dynamic_shapes.py::TestPySymInt::test_symint_bitwise_and, test/test_dynamic_shapes.py::TestPySymInt::test_symint_bitwise_or, test/test_dynamic_shapes.py::TestPySymInt::test_symint_vargs, test/test_dynamic_shapes.py::TestPySymInt::test_sympify_symint, test/test_dynamic_shapes.py::TestPySymInt::test_sympy_optimized_add, test/test_dynamic_shapes.py::TestPySymInt::test_sympy_optimized_add_binary_search, test/test_dynamic_shapes.py::TestPySymInt::test_tensor_factory_with_symint, test/test_dynamic_shapes.py::TestPySymInt::test_tracing_sym_ite, test/test_dynamic_shapes.py::TestPySymInt::test_unbacked_substitution, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_abs, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_add, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_and, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_bitwise_and, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_bitwise_or, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_ceil, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_eq, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_float_pow, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_float_truediv, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_floor, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_ge, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_gt, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_int_floordiv, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_int_truediv, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_is_integer, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_le, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_lshift, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_lt, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_mod, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_mul, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_ne, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_neg, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_or, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_pos, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_pow_by_natural, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_round, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_rshift, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sub, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_acos, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_asin, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_atan, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_cos, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_cosh, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_ite, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_log2, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_max, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_min, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_not, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_sin, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_sinh, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_sqrt, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_tan, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_sym_tanh, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_bool_method_fn_trunc, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_abs_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_abs_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_abs_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_abs_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_add_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_add_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_add_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_add_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_and_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_and_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_and_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_and_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_bitwise_and_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_bitwise_and_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_bitwise_and_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_bitwise_and_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_bitwise_or_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_bitwise_or_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_bitwise_or_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_bitwise_or_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ceil_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ceil_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ceil_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ceil_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_eq_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_eq_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_eq_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_eq_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_float_pow_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_float_pow_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_float_pow_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_float_pow_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_float_truediv_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_float_truediv_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_float_truediv_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_float_truediv_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_floor_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_floor_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_floor_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_floor_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ge_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ge_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ge_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ge_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_gt_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_gt_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_gt_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_gt_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_int_floordiv_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_int_floordiv_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_int_floordiv_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_int_floordiv_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_int_truediv_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_int_truediv_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_int_truediv_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_int_truediv_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_is_integer_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_is_integer_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_is_integer_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_is_integer_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_le_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_le_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_le_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_le_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_lshift_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_lshift_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_lshift_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_lshift_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_lt_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_lt_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_lt_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_lt_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_mod_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_mod_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_mod_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_mod_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_mul_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_mul_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_mul_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_mul_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ne_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ne_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ne_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_ne_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_neg_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_neg_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_neg_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_neg_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_or_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_or_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_or_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_or_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_pos_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_pos_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_pos_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_pos_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_pow_by_natural_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_pow_by_natural_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_pow_by_natural_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_pow_by_natural_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_round_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_round_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_round_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_round_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_rshift_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_rshift_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_rshift_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_rshift_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sub_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sub_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sub_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sub_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_acos_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_acos_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_acos_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_acos_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_asin_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_asin_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_asin_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_asin_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_atan_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_atan_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_atan_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_atan_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_cos_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_cos_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_cos_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_cos_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_cosh_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_cosh_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_cosh_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_cosh_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_float_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_float_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_float_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_float_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_ite_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_ite_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_ite_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_ite_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_log2_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_log2_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_log2_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_log2_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_max_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_max_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_max_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_max_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_min_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_min_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_min_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_min_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_not_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_not_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_not_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_not_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sin_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sin_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sin_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sin_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sinh_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sinh_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sinh_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sinh_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sqrt_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sqrt_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sqrt_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_sqrt_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_tan_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_tan_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_tan_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_tan_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_tanh_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_tanh_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_tanh_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_sym_tanh_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_trunc_first_type_float_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_trunc_first_type_float_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_trunc_first_type_int_second_type_float, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_method_fn_trunc_first_type_int_second_type_int, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_non_symbolic_symnode, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_stride_symnode, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_symint_deepcopy, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_symint_hashing, test/test_dynamic_shapes.py::TestSymNumberMagicMethods::test_symnode_hashing, test/test_dynamic_shapes.py::TestFloorDiv::test_floordiv_assumptions, test/test_dynamic_shapes.py::TestFloorDiv::test_floordiv_div_by_one, test/test_dynamic_shapes.py::TestFloorDiv::test_floordiv_float_int, test/test_dynamic_shapes.py::TestFloorDiv::test_floordiv_simplify, test/test_dynamic_shapes.py::TestDimConstraints::test_dim_constraints_reduce_congruences_simple, test/test_dynamic_shapes.py::TestDimConstraints::test_dim_constraints_reduce_inequalities_error, test/test_dynamic_shapes.py::TestDimConstraints::test_dim_constraints_reduce_inequalities_simple, test/test_dynamic_shapes.py::TestDimConstraints::test_dim_constraints_solve_full, test/test_dynamic_shapes.py::TestDimConstraints::test_simplify_max_1_0, test/test_dynamic_shapes.py::TestGuardsExpressions::test_guard_or_false, test/test_dynamic_shapes.py::TestGuardsExpressions::test_guard_or_true, test/test_dynamic_shapes.py::TestGuardsExpressions::test_guards_float_div, test/test_dynamic_shapes.py::TestGuardsExpressions::test_guards_float_print, test/test_dynamic_shapes.py::TestGuardsExpressions::test_guards_gt_lt, test/test_dynamic_shapes.py::TestGuardsExpressions::test_remove_symbols_without_guarding, test/test_dynamic_shapes.py::TestUnbacked::test_deferred_neq_assert_backend_eager, test/test_dynamic_shapes.py::TestUnbacked::test_deferred_neq_assert_backend_inductor, test/test_dynamic_shapes.py::TestUnbacked::test_deferred_sym_eq_assert_backend_eager, test/test_dynamic_shapes.py::TestUnbacked::test_deferred_sym_eq_assert_backend_inductor, test/test_dynamic_shapes.py::TestUnbacked::test_deferred_sym_or_assert_backend_eager, test/test_dynamic_shapes.py::TestUnbacked::test_deferred_sym_or_assert_backend_inductor, test/test_dynamic_shapes.py::TestUnbacked::test_deferred_with_unbacked_input_backend_eager, test/test_dynamic_shapes.py::TestUnbacked::test_deferred_with_unbacked_input_backend_inductor, test/test_dynamic_shapes.py::TestUnbacked::test_has_free_symbols, test/test_dynamic_shapes.py::TestUnbacked::test_post_specialize_runtime_assert1_backend_eager, test/test_dynamic_shapes.py::TestUnbacked::test_post_specialize_runtime_assert1_backend_inductor, test/test_dynamic_shapes.py::TestUnbacked::test_post_specialize_runtime_assert2_backend_eager, test/test_dynamic_shapes.py::TestUnbacked::test_post_specialize_runtime_assert2_backend_inductor, test/test_dynamic_shapes.py::TestUbackedOps::test_invalid_view_unbacked_view, test/test_dynamic_shapes.py::TestUbackedOps::test_unbacked_contiguous, test/test_dynamic_shapes.py::TestUbackedOps::test_unbacked_non_contigious_reshape_failing, test/test_dynamic_shapes.py::TestUbackedOps::test_unbacked_reshape1, test/test_dynamic_shapes.py::TestUbackedOps::test_unbacked_reshape2, test/test_dynamic_shapes.py::TestUbackedOps::test_unbacked_select_index, test/test_dynamic_shapes.py::TestUbackedOps::test_unbacked_select_index_cpp_wrapper, test/test_dynamic_shapes.py::TestUbackedOps::test_unbacked_select_index_with_check, test/test_dynamic_shapes.py::TestUbackedOps::test_unbind_not_dynamic 2025-07-17T09:12:36.4894010Z 2025-07-17T09:12:39.7394679Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:12:39.7396529Z import pkg_resources 2025-07-17T09:12:39.8676706Z Running torch_np/numpy_tests/fft/test_helper 1/1 ... [2025-07-17 09:12:39.867267] 2025-07-17T09:12:39.8677241Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:12:39.8681319Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/fft/test_helper.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:12:39.867738] 2025-07-17T09:12:39.9853123Z 2025-07-17T09:12:39.9854422Z functorch/test_control_flow 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_control_flow_1.1_3048c118730a9e48_.log 2025-07-17T09:12:40.0685896Z Running 1315 items in this shard: test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_complex, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_different_pytree_output, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_gpu, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_grad_through_cond, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_inner_fn, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_inner_tensor, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_mixed_require_grad, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_nested, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_pytree_input, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_pytree_not_all_inputs_used, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_same_pytree_output, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_simple, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_torch_nn_module, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_user_nn_module, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_zeros_unused_branch_complex_compile_fail_compile_mode_compile_dynamic_shape_scalar_False, test/functorch/test_control_flow.py::TestControlFlow::test_cond_gpu, test/functorch/test_control_flow.py::TestControlFlow::test_cond_in_forloop, test/functorch/test_control_flow.py::TestControlFlow::test_cond_no_trace, test/functorch/test_control_flow.py::TestControlFlow::test_map_autograd_higher_order, test/functorch/test_control_flow.py::TestControlFlow::test_map_autograd_nested_list, test/functorch/test_control_flow.py::TestControlFlow::test_map_autograd_no_grad_output, test/functorch/test_control_flow.py::TestControlFlow::test_map_autograd_simple, test/functorch/test_control_flow.py::TestControlFlow::test_map_autograd_simple_partial_grad, test/functorch/test_control_flow.py::TestControlFlow::test_map_dict_in_out, test/functorch/test_control_flow.py::TestControlFlow::test_map_gpu, test/functorch/test_control_flow.py::TestControlFlow::test_map_illegal_inputs, test/functorch/test_control_flow.py::TestControlFlow::test_map_illegal_outputs, test/functorch/test_control_flow.py::TestControlFlow::test_map_list_in_out, test/functorch/test_control_flow.py::TestControlFlow::test_scan_associative_scan, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_carry_carry_alias, test/functorch/test_control_flow.py::TestControlFlow::test_scan_carry_output_alias, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_compile_mode_eager_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_compile_mode_eager_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_compile_mode_none_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_compile_mode_none_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_additional_inputs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_additional_inputs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_complex_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_complex_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_init_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_init_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_random_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_random_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_xs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_xs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_additional_inputs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_additional_inputs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_complex_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_complex_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_init_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_init_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_random_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_random_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_xs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_xs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_additional_inputs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_additional_inputs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_complex_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_complex_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_init_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_init_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_random_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_random_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_xs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_xs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_additional_inputs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_additional_inputs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_complex_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_complex_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_init_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_init_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_random_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_random_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_xs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_xs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_True_compile_mode_none_cuda_autograd_False, 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test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cuda_int32, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cuda_int64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_float_output, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_non_tensor, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_scanned_0, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_carry_shape, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_complex_reverse_False_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_complex_reverse_False_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_complex_reverse_True_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_complex_reverse_True_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_init_longer_carry, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_init_shorter_carry, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_shape, test/functorch/test_control_flow.py::TestControlFlow::test_scan_input_carry_alias, test/functorch/test_control_flow.py::TestControlFlow::test_scan_input_mutation, test/functorch/test_control_flow.py::TestControlFlow::test_scan_input_output_alias, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_one_return, test/functorch/test_control_flow.py::TestControlFlow::test_scan_pytree_output, test/functorch/test_control_flow.py::TestControlFlow::test_scan_simple_graph, test/functorch/test_control_flow.py::TestControlFlow::test_scan_simple_graph_wrong_dtype, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_wrong_pytree, test/functorch/test_control_flow.py::TestControlFlow::test_scan_y_less_ndim_then_dim, test/functorch/test_control_flow.py::TestControlFlow::test_while_loop_gpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_combine_fn_wrong_meta_in_combine_fn, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_dynamic_shape_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_dynamic_shape_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_dynamic_shape_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_dynamic_shape_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_eager_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_eager_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_eager_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_eager_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_none_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_none_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_none_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_none_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_compile_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_compile_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_compile_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_compile_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_compile_dynamic_shape_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_compile_dynamic_shape_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_compile_dynamic_shape_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_compile_dynamic_shape_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_eager_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_eager_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_eager_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_eager_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_none_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_none_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_none_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_none_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_eager_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_eager_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_eager_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_eager_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_eager_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_eager_combine_mode_pointwise_reverse_False_cuda, 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test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_none_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_none_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_none_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_none_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_none_reverse_True_cpu, 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test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_False_compile_mode_none_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_False_compile_mode_none_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_True_compile_mode_compile_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_True_compile_mode_compile_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_True_compile_mode_compile_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_True_compile_mode_compile_combine_mode_pointwise_cuda, 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test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_eager_reverse_True_cpu, 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test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_none_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_none_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_none_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_none_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_none_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_none_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_none_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_none_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_none_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_none_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_none_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_none_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_none_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_none_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_eager_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_fct_compile_mode_eager_combine_mode_generic_reverse_False_cuda, 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test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_input_mutation, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_input_output_alias, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_dynamic_shape_loop_type_for_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_dynamic_shape_loop_type_for_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_dynamic_shape_loop_type_for_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_dynamic_shape_loop_type_for_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_loop_type_for_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_loop_type_for_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_loop_type_for_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_loop_type_for_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_eager_loop_type_for_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_eager_loop_type_for_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_eager_loop_type_for_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_eager_loop_type_for_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_none_loop_type_for_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_none_loop_type_for_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_none_loop_type_for_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_none_loop_type_for_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_failure, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_map_in_combine_fn, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_nested, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_dynamic_shape_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_none_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_none_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_compile_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_compile_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_compile_dynamic_shape_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_compile_dynamic_shape_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_eager_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_eager_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_none_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_none_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_compile_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_compile_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_compile_dynamic_shape_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_compile_dynamic_shape_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_eager_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_eager_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_none_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_none_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_output_output_alias, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_pytree_output, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_sparse_tensor, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_none_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_none_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_wrong_pytree, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_accepts_torch_function_as_inputs, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_autograd_backward, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_eager_run_with_item, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_aot_func_check_functional, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_data_dependent_pred, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_input_aliasing_with_aot_func, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_input_mutation_on_false_branch, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_input_mutation_on_true_branch, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_nested_input_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_nested_input_mutation_with_aot_func, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_output_alias_input, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_make_fx_preserve_stack_trace_for_nodes_in_subgraph, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_merge_graph_preserves_ph_meta, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_output_dynamic_False_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_output_dynamic_False_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_output_dynamic_True_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_output_dynamic_True_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_strided_output_dynamic_False_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_strided_output_dynamic_False_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_strided_output_dynamic_True_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_strided_output_dynamic_True_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced_multi, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced_multi_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced_other_inputs, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced_other_inputs_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_with_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_with_closure_graph_module, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_no_dynamo_cache_limit, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_retrace_functionalized, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_simple_with_linear_compile_check_graph, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_subgraph_same_shape_env_as_parent, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_symint_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_symint_operands_requires_grad_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_symint_operands_requires_grad_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_trace_set__and_mutate_input, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_trace_set__and_mutate_intermediate, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_traced_not_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_traced_not_nested_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_module_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_module_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_module_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_module_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_unbacked_symint_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_multiple_args_with_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_multiple_inputs, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_multiple_outputs_nClosure_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_multiple_outputs_nClosure_1, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_function_nOperands_2_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_function_nOperands_2_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_module_nOperands_2_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_module_nOperands_2_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_object_nOperands_2_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_object_nOperands_2_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_single_input_with_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_consecutive_make_fx_symbolic, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_module_param_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_module_python_scalar_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_sym_pred, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_tensor_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_tensor_closure_graph_module, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_unbacked_sym_pred, test/functorch/test_control_flow.py::TestControlFlowTraced::test_hop_raises_if_not_overriding_call, test/functorch/test_control_flow.py::TestControlFlowTraced::test_input_input_alias, test/functorch/test_control_flow.py::TestControlFlowTraced::test_input_mutation_inference_mode_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_input_mutation_inference_mode_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_input_output_alias, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_functionalized, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_functionalized_aot_func, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_functionalized_arg_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_functionalized_elem_alias, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_functionalized_elem_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_unfunc_boolean_tensor_for_nested_map_cond, test/functorch/test_control_flow.py::TestControlFlowTraced::test_merge_output, test/functorch/test_control_flow.py::TestControlFlowTraced::test_nested_cond_map_cond_symbolic, test/functorch/test_control_flow.py::TestControlFlowTraced::test_nested_map_cond_real, test/functorch/test_control_flow.py::TestControlFlowTraced::test_nested_map_cond_symbolic, test/functorch/test_control_flow.py::TestControlFlowTraced::test_raise_error_on_mismatch_tensor_size, test/functorch/test_control_flow.py::TestControlFlowTraced::test_raise_error_on_mismatch_tensor_size_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_raise_error_on_mismatch_type_size, test/functorch/test_control_flow.py::TestControlFlowTraced::test_raise_error_on_mismatch_type_size_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_scan_functionalized, test/functorch/test_control_flow.py::TestControlFlowTraced::test_scan_functionalized_elem_alias, test/functorch/test_control_flow.py::TestControlFlowTraced::test_scan_functionalized_elem_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_scan_pytree_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_autograd_aot_functionalized, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_autograd_symbolic_dict, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_autograd_symbolic_list, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_autograd_symbolic_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_real, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_symbolic_dict, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_symbolic_list, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_symbolic_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_two_hops_not_sharing_code_obj, test/functorch/test_control_flow.py::TestControlFlowTraced::test_vmap_vmap_boolcond_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_vmap_vmap_boolcond_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_const_and_symint_output, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_int_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_nested_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_pytree_int_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_simple_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_const_and_symint_output, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_int_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_nested_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_pytree_int_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_simple_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_cpp_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_cpp_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_cpp_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_cpp_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_cpp_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_functorch_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_functorch_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_functorch_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_functorch_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_functorch_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_no_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_no_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_no_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_no_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_no_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_python_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_python_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_python_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_python_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_python_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_nested2_traced, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_nested_traced, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_compile_dynamic_False_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_compile_dynamic_False_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_compile_dynamic_True_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_compile_dynamic_True_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_export_strict_False_dynamic_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_export_strict_False_dynamic_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_export_strict_True_dynamic_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_export_strict_True_dynamic_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_compile_dynamic_False_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_compile_dynamic_False_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_compile_dynamic_True_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_compile_dynamic_True_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_export_strict_False_dynamic_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_export_strict_False_dynamic_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_mismatch_in_meta, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_compile_dynamic_False_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_compile_dynamic_False_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_compile_dynamic_True_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_compile_dynamic_True_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_export_strict_False_dynamic_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_export_strict_False_dynamic_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_export_strict_True_dynamic_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_export_strict_True_dynamic_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_simple_functionalize_check_graph_func_type_cpp, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_simple_functionalize_check_graph_func_type_functorch, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_simple_functionalize_check_graph_func_type_no, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_simple_functionalize_check_graph_func_type_python, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_simple_with_linear_compile_check_graph, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_nested_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_simple_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_unbacked_bindings, test/functorch/test_control_flow.py::TestHopSchema::test_function_schema_gen, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_GraphModule, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_ScriptObj, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_SymBool, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_SymInt, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_Tensor, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_bool, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_float, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_int, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_str, test/functorch/test_control_flow.py::TestHopSchema::test_schema_tree_spec, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_GraphModule, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_ScriptObj, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_SymBool, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_SymInt, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_Tensor, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_bool, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_float, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_int, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_str, test/functorch/test_control_flow.py::TestHopSchema::test_while_loop_schema_gen 2025-07-17T09:12:40.1493432Z 2025-07-17T09:12:43.2711563Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:12:43.2715239Z import pkg_resources 2025-07-17T09:12:43.3996411Z Running torch_np/test_ndarray_methods 1/1 ... [2025-07-17 09:12:43.399209] 2025-07-17T09:12:43.3997165Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:12:43.3999240Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_ndarray_methods.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:12:43.399631] 2025-07-17T09:12:51.3014010Z 2025-07-17T09:12:51.3015400Z torch_np/numpy_tests/fft/test_helper 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.fft.test_helper_1.1_c9973a722ce30097_.log 2025-07-17T09:12:51.3019638Z Running 8 items in this shard: test/torch_np/numpy_tests/fft/test_helper.py::TestFFTShift::test_axes_keyword, test/torch_np/numpy_tests/fft/test_helper.py::TestFFTShift::test_definition, test/torch_np/numpy_tests/fft/test_helper.py::TestFFTShift::test_equal_to_original, test/torch_np/numpy_tests/fft/test_helper.py::TestFFTShift::test_inverse, test/torch_np/numpy_tests/fft/test_helper.py::TestFFTShift::test_uneven_dims, test/torch_np/numpy_tests/fft/test_helper.py::TestFFTFreq::test_definition, test/torch_np/numpy_tests/fft/test_helper.py::TestRFFTFreq::test_definition, test/torch_np/numpy_tests/fft/test_helper.py::TestIRFFTN::test_not_last_axis_success 2025-07-17T09:12:51.3022430Z 2025-07-17T09:12:54.2302168Z 2025-07-17T09:12:54.2303562Z test_serialization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_serialization_1.1_26470bdda865c986_.log 2025-07-17T09:12:54.2446680Z Running 201 items in this shard: test/test_serialization.py::TestOldSerialization::test_debug_set_in_ci, test/test_serialization.py::TestOldSerialization::test_load_error_msg, test/test_serialization.py::TestOldSerialization::test_load_nonexistent_device, test/test_serialization.py::TestOldSerialization::test_load_python2_unicode_module, test/test_serialization.py::TestOldSerialization::test_load_unicode_error_msg, test/test_serialization.py::TestOldSerialization::test_pickle_module, test/test_serialization.py::TestOldSerialization::test_safe_load_basic_types, test/test_serialization.py::TestOldSerialization::test_save_different_dtype_error, test/test_serialization.py::TestOldSerialization::test_save_different_dtype_unallocated, test/test_serialization.py::TestOldSerialization::test_serialization, test/test_serialization.py::TestOldSerialization::test_serialization_backwards_compat, test/test_serialization.py::TestOldSerialization::test_serialization_backwards_compat_safe, test/test_serialization.py::TestOldSerialization::test_serialization_container, test/test_serialization.py::TestOldSerialization::test_serialization_container_filelike, test/test_serialization.py::TestOldSerialization::test_serialization_dill, test/test_serialization.py::TestOldSerialization::test_serialization_dill_version_not_supported, test/test_serialization.py::TestOldSerialization::test_serialization_fake_zip, test/test_serialization.py::TestOldSerialization::test_serialization_filelike, test/test_serialization.py::TestOldSerialization::test_serialization_filelike_api_requirements, test/test_serialization.py::TestOldSerialization::test_serialization_filelike_exceptions, test/test_serialization.py::TestOldSerialization::test_serialization_filelike_missing_attrs, test/test_serialization.py::TestOldSerialization::test_serialization_filelike_stress, test/test_serialization.py::TestOldSerialization::test_serialization_filelike_uses_readinto, test/test_serialization.py::TestOldSerialization::test_serialization_gzip, test/test_serialization.py::TestOldSerialization::test_serialization_map_location, test/test_serialization.py::TestOldSerialization::test_serialization_offset, test/test_serialization.py::TestOldSerialization::test_serialization_offset_filelike_weights_only_False, test/test_serialization.py::TestOldSerialization::test_serialization_offset_filelike_weights_only_True, test/test_serialization.py::TestOldSerialization::test_serialization_offset_gzip, test/test_serialization.py::TestOldSerialization::test_serialization_safe, test/test_serialization.py::TestOldSerialization::test_serialization_save_warnings, test/test_serialization.py::TestOldSerialization::test_serialization_sparse, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_bsc_invalid, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_bsr_invalid, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_csc_invalid, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_csr_invalid, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_invalid, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_invalid_legacy_ctor, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_safe, test/test_serialization.py::TestOldSerialization::test_serialization_storage_slice, test/test_serialization.py::TestOldSerialization::test_serialization_zipfile_utils, test/test_serialization.py::TestOldSerialization::test_serialize_device, test/test_serialization.py::TestOldSerialization::test_skip_data_load, test/test_serialization.py::TestSerialization::test_crc32_options_compute_crc32_False_filename_False, test/test_serialization.py::TestSerialization::test_crc32_options_compute_crc32_False_filename_True, test/test_serialization.py::TestSerialization::test_crc32_options_compute_crc32_True_filename_False, test/test_serialization.py::TestSerialization::test_crc32_options_compute_crc32_True_filename_True, test/test_serialization.py::TestSerialization::test_debug_set_in_ci, test/test_serialization.py::TestSerialization::test_filewriter_metadata_writing_filename_False, test/test_serialization.py::TestSerialization::test_filewriter_metadata_writing_filename_True, test/test_serialization.py::TestSerialization::test_get_unsafe_globals_in_checkpoint, test/test_serialization.py::TestSerialization::test_has_format_version, test/test_serialization.py::TestSerialization::test_load_error_msg, test/test_serialization.py::TestSerialization::test_load_njt_weights_only_should_import_False, test/test_serialization.py::TestSerialization::test_load_njt_weights_only_should_import_True, test/test_serialization.py::TestSerialization::test_load_nonexistent_device, test/test_serialization.py::TestSerialization::test_load_python2_unicode_module, test/test_serialization.py::TestSerialization::test_load_unicode_error_msg, test/test_serialization.py::TestSerialization::test_lr_scheduler_serialization, test/test_serialization.py::TestSerialization::test_meta_serialization_weights_only_False, test/test_serialization.py::TestSerialization::test_meta_serialization_weights_only_True, test/test_serialization.py::TestSerialization::test_mmap_load_offset_calculation_path_type0, test/test_serialization.py::TestSerialization::test_mmap_load_offset_calculation_path_type1, test/test_serialization.py::TestSerialization::test_pathlike_serialization_weights_only_False, test/test_serialization.py::TestSerialization::test_pathlike_serialization_weights_only_True, test/test_serialization.py::TestSerialization::test_pickle_module, test/test_serialization.py::TestSerialization::test_safe_load_basic_types, test/test_serialization.py::TestSerialization::test_save_different_dtype_error, test/test_serialization.py::TestSerialization::test_save_different_dtype_unallocated, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_bfloat16_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_bfloat16_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_bool_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_bool_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_complex128_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_complex128_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_complex64_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_complex64_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float16_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float16_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float32_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float32_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float64_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float64_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int16_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int16_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int32_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int32_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int64_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int64_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int8_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int8_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_uint8_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_uint8_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization, test/test_serialization.py::TestSerialization::test_serialization_backwards_compat, test/test_serialization.py::TestSerialization::test_serialization_backwards_compat_safe, test/test_serialization.py::TestSerialization::test_serialization_byte_literal_byte_literals0_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_byte_literal_byte_literals0_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_byte_literal_byte_literals1_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_byte_literal_byte_literals1_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_byteorder_mark, test/test_serialization.py::TestSerialization::test_serialization_dill, test/test_serialization.py::TestSerialization::test_serialization_dill_version_not_supported, test/test_serialization.py::TestSerialization::test_serialization_dtype_complex32_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_complex32_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_dtype_float8_e4m3fn_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_float8_e4m3fn_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_dtype_float8_e5m2_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_float8_e5m2_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint16_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint16_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint32_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint32_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint64_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint64_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_efficient_zerotensor_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_efficient_zerotensor_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_fake_zip, test/test_serialization.py::TestSerialization::test_serialization_filelike, test/test_serialization.py::TestSerialization::test_serialization_filelike_api_requirements, test/test_serialization.py::TestSerialization::test_serialization_filelike_exceptions, test/test_serialization.py::TestSerialization::test_serialization_filelike_missing_attrs, test/test_serialization.py::TestSerialization::test_serialization_filelike_stress, test/test_serialization.py::TestSerialization::test_serialization_filelike_uses_readinto, test/test_serialization.py::TestSerialization::test_serialization_gzip, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_bfloat16, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_bool, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_cdouble, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_cfloat, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_double, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_float, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_half, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_int, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_int16, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_int8, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_long, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_uint8, test/test_serialization.py::TestSerialization::test_serialization_map_location, test/test_serialization.py::TestSerialization::test_serialization_math_bits_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_math_bits_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_ctx, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_options_path_type0_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_options_path_type0_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_options_path_type1_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_options_path_type1_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_with_map_location, test/test_serialization.py::TestSerialization::test_serialization_nested_class, test/test_serialization.py::TestSerialization::test_serialization_offset_gzip, test/test_serialization.py::TestSerialization::test_serialization_python_attr_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_python_attr_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_safe, test/test_serialization.py::TestSerialization::test_serialization_save_warnings, test/test_serialization.py::TestSerialization::test_serialization_sparse, test/test_serialization.py::TestSerialization::test_serialization_sparse_bsc_invalid, test/test_serialization.py::TestSerialization::test_serialization_sparse_bsr_invalid, test/test_serialization.py::TestSerialization::test_serialization_sparse_csc_invalid, test/test_serialization.py::TestSerialization::test_serialization_sparse_csr_invalid, test/test_serialization.py::TestSerialization::test_serialization_sparse_invalid, test/test_serialization.py::TestSerialization::test_serialization_sparse_invalid_legacy_ctor, test/test_serialization.py::TestSerialization::test_serialization_sparse_safe, test/test_serialization.py::TestSerialization::test_serialization_storage_slice, test/test_serialization.py::TestSerialization::test_serialization_uintx_intx, test/test_serialization.py::TestSerialization::test_serialization_warning_s390x, test/test_serialization.py::TestSerialization::test_serialization_with_header, test/test_serialization.py::TestSerialization::test_serialization_zipfile_actually_jit, test/test_serialization.py::TestSerialization::test_serialization_zipfile_utils, test/test_serialization.py::TestSerialization::test_serialization_zipfile_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_zipfile_weights_only_True, test/test_serialization.py::TestSerialization::test_serialize_device, test/test_serialization.py::TestSerialization::test_skip_data_load, test/test_serialization.py::TestSerialization::test_skip_data_serialization_error_cases, test/test_serialization.py::TestSerialization::test_skip_data_serialization_materialize_fake_False, test/test_serialization.py::TestSerialization::test_skip_data_serialization_materialize_fake_True, test/test_serialization.py::TestSerialization::test_skip_data_serialization_preserves_views_materialize_fake_False, test/test_serialization.py::TestSerialization::test_skip_data_serialization_preserves_views_materialize_fake_True, test/test_serialization.py::TestSerialization::test_storage_alignment, test/test_serialization.py::TestSerialization::test_use_pinned_memory_for_d2h, test/test_serialization.py::TestSerialization::test_weights_only_assert, test/test_serialization.py::TestSerialization::test_weights_only_env_variables_force_weights_only_False, test/test_serialization.py::TestSerialization::test_weights_only_env_variables_force_weights_only_True, test/test_serialization.py::TestSerialization::test_weights_only_error_unsafe_global_False, test/test_serialization.py::TestSerialization::test_weights_only_error_unsafe_global_True, test/test_serialization.py::TestSerialization::test_weights_only_safe_globals_blocklist, test/test_serialization.py::TestSerialization::test_weights_only_safe_globals_build, test/test_serialization.py::TestSerialization::test_weights_only_safe_globals_build_with_slots_slots_all, test/test_serialization.py::TestSerialization::test_weights_only_safe_globals_build_with_slots_slots_some, test/test_serialization.py::TestSerialization::test_weights_only_safe_globals_newobj, test/test_serialization.py::TestSubclassSerialization::test_cloned_deepcopy_requires_grad_False, test/test_serialization.py::TestSubclassSerialization::test_cloned_deepcopy_requires_grad_True, test/test_serialization.py::TestSubclassSerialization::test_empty_class_serialization, test/test_serialization.py::TestSubclassSerialization::test_safe_globals_context_manager_weights_only, test/test_serialization.py::TestSubclassSerialization::test_safe_globals_for_weights_only, test/test_serialization.py::TestSubclassSerialization::test_sets_are_loadable_with_weights_only, test/test_serialization.py::TestSubclassSerialization::test_tensor_subclass_deepcopy, test/test_serialization.py::TestSubclassSerialization::test_tensor_subclass_getstate_overwrite, test/test_serialization.py::TestSubclassSerialization::test_tensor_subclass_map_location, test/test_serialization.py::TestSubclassSerialization::test_tensor_subclass_wrapper_serialization, test/test_serialization.py::TestBothSerializationCPU::test_serialization_new_format_old_format_compat_weights_only_False_cpu, test/test_serialization.py::TestBothSerializationCPU::test_serialization_new_format_old_format_compat_weights_only_True_cpu 2025-07-17T09:12:54.2593289Z 2025-07-17T09:12:54.5760881Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:12:54.5763646Z import pkg_resources 2025-07-17T09:12:54.7035771Z Running torch_np/numpy_tests/lib/test_twodim_base 1/1 ... [2025-07-17 09:12:54.703174] 2025-07-17T09:12:54.7036763Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:12:54.7038838Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_twodim_base.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:12:54.703559] 2025-07-17T09:12:57.4972589Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:12:57.4975303Z import pkg_resources 2025-07-17T09:12:57.6236376Z Running test_vulkan 1/1 ... [2025-07-17 09:12:57.623268] 2025-07-17T09:12:57.6237060Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:12:57.6240044Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_vulkan.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:12:57.623681] 2025-07-17T09:13:01.0432841Z 2025-07-17T09:13:01.0434120Z test_vulkan 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_vulkan_1.1_840a981545c3e043_.log 2025-07-17T09:13:01.0435678Z Running 1 items in this shard: test/test_vulkan.py::TestVulkanRewritePass::test_conv 2025-07-17T09:13:01.0436688Z 2025-07-17T09:13:04.2889533Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:13:04.2891103Z import pkg_resources 2025-07-17T09:13:04.4159077Z Running torch_np/numpy_tests/lib/test_shape_base_ 1/1 ... [2025-07-17 09:13:04.415465] 2025-07-17T09:13:04.4159902Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:13:04.4161582Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_shape_base_.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:13:04.415866] 2025-07-17T09:13:05.7347335Z 2025-07-17T09:13:05.7349601Z torch_np/numpy_tests/lib/test_twodim_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_twodim_base_1.1_d78db92eb5cb5b9c_.log 2025-07-17T09:13:05.7371350Z Running 34 items in this shard: test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_2d, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_basic, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_bool, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_diag, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_diag2d, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_eye_bounds, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_order, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestDiag::test_diag_bounds, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestDiag::test_failure, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestDiag::test_fortran_order, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestDiag::test_matrix, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestDiag::test_vector, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestFliplr::test_basic, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestFlipud::test_basic, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_all_outliers, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_asym, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_bad_length_x_len_10_y_len_11, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_bad_length_x_len_20_y_len_19, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_binparameter_combination, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_density, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_empty, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_simple, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_dtype, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_mask_indices, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_tril_indices, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_tril_triu_dtype, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_tril_triu_ndim2, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_tril_triu_ndim3, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_tril_triu_with_inf, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTriuIndices::test_triu_indices, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTrilIndicesFrom::test_exceptions, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTriuIndicesFrom::test_exceptions, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestVander::test_basic, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestVander::test_dtypes 2025-07-17T09:13:05.7392236Z 2025-07-17T09:13:09.1487025Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:13:09.1490259Z import pkg_resources 2025-07-17T09:13:09.2753611Z Running test_mkldnn_fusion 1/1 ... [2025-07-17 09:13:09.274962] 2025-07-17T09:13:09.2754388Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:13:09.2757409Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn_fusion.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:13:09.275433] 2025-07-17T09:13:12.7449536Z 2025-07-17T09:13:12.7450759Z test_mkldnn_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_fusion_1.1_ea2118171a0471f1_.log 2025-07-17T09:13:12.7455873Z Running 8 items in this shard: test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_binary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_transpose_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_nnc, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_linear_binary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_linear_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_single_conv, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_unsupported_conv 2025-07-17T09:13:12.7460156Z 2025-07-17T09:13:15.9718917Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:13:15.9722063Z import pkg_resources 2025-07-17T09:13:16.0988947Z Running dynamo/test_guard_manager 1/1 ... [2025-07-17 09:13:16.098463] 2025-07-17T09:13:16.0989727Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:13:16.0992586Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_guard_manager.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:13:16.098909] 2025-07-17T09:13:19.3253733Z 2025-07-17T09:13:19.3255073Z dynamo/test_guard_manager 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_guard_manager_1.1_0035462bb523b483_.log 2025-07-17T09:13:19.3256317Z 2025-07-17T09:13:22.5990838Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:13:22.5993574Z import pkg_resources 2025-07-17T09:13:22.7294220Z Running test_shape_ops 1/1 ... [2025-07-17 09:13:22.728805] 2025-07-17T09:13:22.7295058Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:13:22.7296543Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_shape_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:13:22.729219] 2025-07-17T09:13:24.5158202Z 2025-07-17T09:13:24.5159875Z torch_np/numpy_tests/lib/test_shape_base_ 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_shape_base__1.1_1db3c91c541588ef_.log 2025-07-17T09:13:24.5189598Z Running 73 items in this shard: test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTakeAlongAxis::test_argequivalent, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTakeAlongAxis::test_broadcast, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTakeAlongAxis::test_empty, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTakeAlongAxis::test_invalid, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestPutAlongAxis::test_broadcast, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestPutAlongAxis::test_replace_max, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_0d_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_3d, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_axis_insertion, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_axis_insertion_ma, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_empty, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_scalar_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_simple, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_simple101, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_tuple_func1d, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_with_iterable_object, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyOverAxes::test_simple, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestExpandDims::test_axis_out_of_range, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestExpandDims::test_axis_tuple, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestExpandDims::test_functionality, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestExpandDims::test_repeated_axis, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_index_split_high_bound, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_index_split_low_bound, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_index_split_simple, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_0_split, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_split, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_split_2D_cols, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_split_2D_default, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_split_2D_rows, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_split_2D_rows_greater_max_int32, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSplit::test_equal_split, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSplit::test_unequal_split, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestColumnStack::test_1D_arrays, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestColumnStack::test_2D_arrays, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestColumnStack::test_generator, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestColumnStack::test_non_iterable, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_0D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_1D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_2D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_2D_array2, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_generator, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_non_iterable, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestHsplit::test_0D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestHsplit::test_1D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestHsplit::test_2D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestHsplit::test_non_iterable, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestVsplit::test_0D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestVsplit::test_1D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestVsplit::test_2D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestVsplit::test_non_iterable, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDsplit::test_0D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDsplit::test_1D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDsplit::test_2D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDsplit::test_3D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDsplit::test_non_iterable, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_basic, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_basic_2, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_squeeze_axis, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_squeeze_axis_handling, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_squeeze_contiguous, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_squeeze_type, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_basic, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a0_shape_b0, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a1_shape_b1, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a2_shape_b2, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a3_shape_b3, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a4_shape_b4, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a5_shape_b5, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTile::test_basic, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTile::test_empty, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTile::test_kroncompare, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTile::test_tile_one_repetition_on_array_gh4679, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestMayShareMemory::test_basic 2025-07-17T09:13:24.5238524Z 2025-07-17T09:13:27.8174375Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:13:27.8177233Z import pkg_resources 2025-07-17T09:13:27.9443984Z Running torch_np/test_scalars_0D_arrays 1/1 ... [2025-07-17 09:13:27.943928] 2025-07-17T09:13:27.9444862Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:13:27.9446974Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_scalars_0D_arrays.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:13:27.944321] 2025-07-17T09:13:39.6285598Z 2025-07-17T09:13:39.6286993Z torch_np/test_scalars_0D_arrays 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_scalars_0D_arrays_1.1_32fde00137e15e4a_.log 2025-07-17T09:13:39.6299889Z Running 33 items in this shard: test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_array_scalar_basic_array, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_array_scalar_basic_asarray, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_array_scalar_basic_asarray_int, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_array_scalar_basic_int64, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_conversion_to_int_array, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_conversion_to_int_asarray, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_conversion_to_int_asarray_int, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_conversion_to_int_int64, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_decay_to_py_scalar_array, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_decay_to_py_scalar_asarray, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_decay_to_py_scalar_asarray_int, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_decay_to_py_scalar_int64, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_scalar_comparisons, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value0, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value1, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value10, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value11, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value4, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value5, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value6, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value7, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value8, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value9, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value_s, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value_string, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_array_0D, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_array_1D, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_array_2D, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_float32, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_int, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_list, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_list-list, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_literal 2025-07-17T09:13:39.6311550Z 2025-07-17T09:13:42.9251679Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:13:42.9254706Z import pkg_resources 2025-07-17T09:13:43.0525085Z Running nn/test_load_state_dict 1/1 ... [2025-07-17 09:13:43.052090] 2025-07-17T09:13:43.0525999Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:13:43.0528424Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_load_state_dict.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:13:43.052512] 2025-07-17T09:13:55.0877422Z 2025-07-17T09:13:55.0879075Z nn/test_load_state_dict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_load_state_dict_1.1_6de22f48507285cb_.log 2025-07-17T09:13:55.0891455Z Running 27 items in this shard: test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_BC_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_BC_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_False_keep_vars_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_False_keep_vars_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_True_keep_vars_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_True_keep_vars_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_shape_stride_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_shape_stride_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_with_optimizer_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_with_optimizer_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_child_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_child_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_custom_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_custom_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_invalid_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_invalid_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_ref_cycle_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_type_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_type_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_warn_assign_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_warn_assign_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_with_unexpected_key_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_with_unexpected_key_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDictSwap::test_swap_subclass_swap_True_assign_False, test/nn/test_load_state_dict.py::TestLoadStateDictSwap::test_swap_subclass_swap_True_assign_True 2025-07-17T09:13:55.0902338Z 2025-07-17T09:13:58.3159976Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:13:58.3161745Z import pkg_resources 2025-07-17T09:13:58.4428807Z Running test_indexing 1/1 ... [2025-07-17 09:13:58.442472] 2025-07-17T09:13:58.4429484Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:13:58.4432792Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_indexing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:13:58.442920] 2025-07-17T09:14:07.7034136Z 2025-07-17T09:14:07.7035751Z torch_np/test_ndarray_methods 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_ndarray_methods_1.1_8001bc037f13b305_.log 2025-07-17T09:14:07.7182515Z Running 342 items in this shard: test/torch_np/test_ndarray_methods.py::TestIndexing::test_indexing_simple, test/torch_np/test_ndarray_methods.py::TestIndexing::test_setitem, test/torch_np/test_ndarray_methods.py::TestReshape::test_reshape_function, test/torch_np/test_ndarray_methods.py::TestReshape::test_reshape_method, test/torch_np/test_ndarray_methods.py::TestTranspose::test_transpose_function, test/torch_np/test_ndarray_methods.py::TestTranspose::test_transpose_method, test/torch_np/test_ndarray_methods.py::TestRavel::test_ravel_function, test/torch_np/test_ndarray_methods.py::TestRavel::test_ravel_method, test/torch_np/test_ndarray_methods.py::TestNonzero::test_array_method, test/torch_np/test_ndarray_methods.py::TestNonzero::test_nonzero_onedim, test/torch_np/test_ndarray_methods.py::TestNonzero::test_nonzero_trivial, test/torch_np/test_ndarray_methods.py::TestNonzero::test_nonzero_twodim, test/torch_np/test_ndarray_methods.py::TestNonzero::test_sparse, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_all_method_max, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_all_method_min, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size0_axis0_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size0_axis0_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size10_axis_-1_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size10_axis_-1_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size11_axis_0_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size11_axis_0_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size12_axis_1_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size12_axis_1_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size13_axis13_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size13_axis13_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size14_axis_-2_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size14_axis_-2_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size15_axis_-1_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size15_axis_-1_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size16_axis_0_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size16_axis_0_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size17_axis_1_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size17_axis_1_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size18_axis18_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size18_axis18_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size19_axis_-3_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size19_axis_-3_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size1_axis_-1_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size1_axis_-1_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size20_axis_-2_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size20_axis_-2_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size21_axis_-1_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size21_axis_-1_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size22_axis_0_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size22_axis_0_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size23_axis_1_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size23_axis_1_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size24_axis_2_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size24_axis_2_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size25_axis25_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size25_axis25_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size26_axis_-3_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size26_axis_-3_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size27_axis_-2_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size27_axis_-2_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size28_axis_-1_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size28_axis_-1_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size29_axis_0_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size29_axis_0_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size2_axis_0_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size2_axis_0_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size30_axis_1_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size30_axis_1_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size31_axis_2_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size31_axis_2_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size32_axis32_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size32_axis32_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size33_axis_-4_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size33_axis_-4_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size34_axis_-3_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size34_axis_-3_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size35_axis_-2_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size35_axis_-2_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size36_axis_-1_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size36_axis_-1_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size37_axis_0_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size37_axis_0_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size38_axis_1_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size38_axis_1_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size39_axis_2_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size39_axis_2_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size3_axis3_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size3_axis3_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size40_axis_3_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size40_axis_3_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size41_axis41_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size41_axis41_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size42_axis_-4_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size42_axis_-4_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size43_axis_-3_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_argmin_argmax_keepdims_size43_axis_-3_method1, 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test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data45, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data46, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data47, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data48, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data49, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data5, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data50, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data51, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data52, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data53, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data54, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data55, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data56, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data57, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data58, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data59, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data6, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data60, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data61, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data62, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data63, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data64, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data65, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data66, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data67, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data68, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data69, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data7, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data70, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data71, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data72, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data73, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data8, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data9, test/torch_np/test_ndarray_methods.py::TestArgmin::test_minimum_signed_integers, test/torch_np/test_ndarray_methods.py::TestAmax::test_basic, test/torch_np/test_ndarray_methods.py::TestAmin::test_basic, test/torch_np/test_ndarray_methods.py::TestContains::test_contains, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_fn, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_ivar, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_method, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_name, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_plain, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_rvar, test/torch_np/test_ndarray_methods.py::TestIter::test_iter_1d, test/torch_np/test_ndarray_methods.py::TestIter::test_iter_2d 2025-07-17T09:14:07.7320058Z 2025-07-17T09:14:11.0224695Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:14:11.0227545Z import pkg_resources 2025-07-17T09:14:11.1509635Z Running torch_np/numpy_tests/lib/test_index_tricks 1/1 ... [2025-07-17 09:14:11.150455] 2025-07-17T09:14:11.1510631Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:14:11.1512829Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_index_tricks.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:14:11.150890] 2025-07-17T09:14:23.1864648Z 2025-07-17T09:14:23.1866530Z torch_np/numpy_tests/lib/test_index_tricks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_index_tricks_1.1_59cf7bb8fc2c54e3_.log 2025-07-17T09:14:23.1889431Z Running 47 items in this shard: test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_0d, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_basic, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_big_indices, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_clipmodes, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_dtypes, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_empty_array_ravel_mode_clip, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_empty_array_ravel_mode_raise, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_empty_array_ravel_mode_wrap, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_empty_array_unravel, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_empty_indices, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_writeability, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_accepts_longdouble, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_accepts_npcomplexfloating, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_accepts_npfloating, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_basic, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_linspace_equivalence, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_mgrid_size_none_handling_start0_stop_10_step0_expected0, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_mgrid_size_none_handling_start_-10_stop_20_step1_expected1, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_nd, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_sparse, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_0d, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_1d, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_2d, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_complex_step, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_mixed_type, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_more_mixed_type, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestNdenumerate::test_basic, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIndexExpression::test_regression_1, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIndexExpression::test_simple_1, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIx_::test_1d_only, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIx_::test_bool, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIx_::test_regression_1, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIx_::test_repeated_input, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIx_::test_shape_and_dtype, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestC::test_c_, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_basic, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_hetero_shape_handling, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_low_dim_handling, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_operate_4d_array, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_tall_matrix, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_tall_matrix_wrap, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_wide_matrix, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestDiagIndices::test_diag_indices, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestDiagIndicesFrom::test_diag_indices_from, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestDiagIndicesFrom::test_error_shape_mismatch, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestDiagIndicesFrom::test_error_small_input, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestNdIndex::test_ndindex 2025-07-17T09:14:23.1907237Z 2025-07-17T09:14:23.9962974Z 2025-07-17T09:14:23.9964192Z test_shape_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_shape_ops_1.1_039eb52f5a4f848a_.log 2025-07-17T09:14:23.9994819Z Running 97 items in this shard: test/test_shape_ops.py::TestShapeOpsCPU::test_clamp_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_clamp_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_clamp_propagates_nans_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_clamp_raises_arg_errors_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_complex_rot90_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_complex_rot90_cpu_complex64, test/test_shape_ops.py::TestShapeOpsCPU::test_diag_cpu_bool, test/test_shape_ops.py::TestShapeOpsCPU::test_diag_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_diagonal_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_diagonal_multidim_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_bfloat16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_bool, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_complex64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_float16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_int16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_int32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_int8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_uint8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_bfloat16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_bool, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_complex64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_float16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_int16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_int32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_int8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_uint8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_large_tensor_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_bfloat16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_bool, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_complex64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_float16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_int16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_int32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_int8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_uint8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_unsupported_dtype_cpu_quint2x4, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_unsupported_dtype_cpu_quint4x2, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_invalid_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_invalid_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_invalid_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_invalid_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_invalid_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_invalid_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_invalid_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_invalid_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_invalid_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_astuple_out_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_bfloat16, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_bool, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_float16, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_int16, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_int32, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_int8, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_uint8, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_discontiguous_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_no_warning_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_non_diff_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_rot90_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_sparse_dense_dim_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_sparse_dense_dim_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_sparse_dense_dim_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_tolist_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_int16, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_int32, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_int8, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_uint8, test/test_shape_ops.py::TestShapeOpsCPU::test_unbind_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_unfold_all_devices_and_dtypes_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_unfold_errors_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_unfold_scalars_cpu 2025-07-17T09:14:24.0022488Z 2025-07-17T09:14:26.4465067Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:14:26.4466831Z import pkg_resources 2025-07-17T09:14:26.5794135Z Running torch_np/numpy_tests/core/test_dlpack 1/1 ... [2025-07-17 09:14:26.578941] 2025-07-17T09:14:26.5794985Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:14:26.5796771Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_dlpack.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:14:26.579373] 2025-07-17T09:14:27.2241054Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:14:27.2244024Z import pkg_resources 2025-07-17T09:14:27.3493327Z Running torch_np/numpy_tests/lib/test_arraypad 1/1 ... [2025-07-17 09:14:27.348927] 2025-07-17T09:14:27.3494187Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:14:27.3496855Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_arraypad.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:14:27.349333] 2025-07-17T09:14:32.8729165Z 2025-07-17T09:14:32.8730629Z torch_np/numpy_tests/lib/test_arraypad 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_arraypad_1.1_f29745124e4010b0_.log 2025-07-17T09:14:32.8735114Z Running 9 items in this shard: test/torch_np/numpy_tests/lib/test_arraypad.py::TestConstant::test_check_constant, test/torch_np/numpy_tests/lib/test_arraypad.py::TestConstant::test_check_constant_float, test/torch_np/numpy_tests/lib/test_arraypad.py::TestConstant::test_check_constant_float2, test/torch_np/numpy_tests/lib/test_arraypad.py::TestConstant::test_check_constant_float3, test/torch_np/numpy_tests/lib/test_arraypad.py::TestConstant::test_check_constant_odd_pad_amount, test/torch_np/numpy_tests/lib/test_arraypad.py::TestConstant::test_check_constant_pad_2d, test/torch_np/numpy_tests/lib/test_arraypad.py::TestConstant::test_check_constant_zeros, test/torch_np/numpy_tests/lib/test_arraypad.py::TestConstant::test_check_large_integers, test/torch_np/numpy_tests/lib/test_arraypad.py::TestConstant::test_pad_empty_dimension 2025-07-17T09:14:32.8738737Z 2025-07-17T09:14:34.0605742Z 2025-07-17T09:14:34.0607771Z torch_np/numpy_tests/core/test_dlpack 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_dlpack_1.1_cca0b3af4eff666a_.log 2025-07-17T09:14:34.0644255Z Running 53 items in this shard: test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dlpack_destructor_exception, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dlpack_device, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype0, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype1, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype2, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype3, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype4, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype5, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype6, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype7, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype8, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype9, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dunder_dlpack_refcount, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dunder_dlpack_stream, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_from_dlpack_refcount, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_from_torch, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_0, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_1, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_10, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_11, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_12, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_13, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_14, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_15, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_16, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_17, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_18, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_19, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_2, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_20, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_21, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_22, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_23, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_24, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_25, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_26, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_27, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_28, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_29, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_3, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_30, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_31, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_32, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_4, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_5, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_6, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_7, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_8, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_9, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_ndim0, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_non_contiguous, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_readonly, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_to_torch 2025-07-17T09:14:34.0678953Z 2025-07-17T09:14:36.1804471Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:14:36.1806203Z import pkg_resources 2025-07-17T09:14:36.3054231Z Running lazy/test_debug_util 1/1 ... [2025-07-17 09:14:36.305034] 2025-07-17T09:14:36.3054845Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:14:36.3056839Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_debug_util.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:14:36.305413] 2025-07-17T09:14:37.2848956Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:14:37.2851970Z import pkg_resources 2025-07-17T09:14:37.4114618Z Running test_xnnpack_integration 1/1 ... [2025-07-17 09:14:37.411046] 2025-07-17T09:14:37.4115388Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:14:37.4117799Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_xnnpack_integration.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:14:37.411432] 2025-07-17T09:14:41.2274972Z 2025-07-17T09:14:41.2276391Z lazy/test_debug_util 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_debug_util_1.1_3f10f9c9407da1d2_.log 2025-07-17T09:14:41.2278194Z Running 1 items in this shard: test/lazy/test_debug_util.py::DebugUtilTest::test_get_python_frames 2025-07-17T09:14:41.2278979Z 2025-07-17T09:14:44.4604705Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:14:44.4607787Z import pkg_resources 2025-07-17T09:14:44.5880356Z Running test_sparse_csr 1/2 ... [2025-07-17 09:14:44.587607] 2025-07-17T09:14:44.5881201Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:14:44.5883317Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sparse_csr.py', '-m', 'not serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:14:44.587983] 2025-07-17T09:15:39.8040721Z 2025-07-17T09:15:39.8042134Z test_xnnpack_integration 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_xnnpack_integration_1.1_0a0ae91ec3556660_.log 2025-07-17T09:15:39.8048606Z Running 12 items in this shard: test/test_xnnpack_integration.py::TestXNNPACKOps::test_conv2d, test/test_xnnpack_integration.py::TestXNNPACKOps::test_conv2d_transpose, test/test_xnnpack_integration.py::TestXNNPACKOps::test_linear, test/test_xnnpack_integration.py::TestXNNPACKOps::test_linear_1d_input, test/test_xnnpack_integration.py::TestXNNPACKSerDes::test_combined_model, test/test_xnnpack_integration.py::TestXNNPACKSerDes::test_conv2d, test/test_xnnpack_integration.py::TestXNNPACKSerDes::test_conv2d_transpose, test/test_xnnpack_integration.py::TestXNNPACKSerDes::test_linear, test/test_xnnpack_integration.py::TestXNNPACKRewritePass::test_decomposed_linear, test/test_xnnpack_integration.py::TestXNNPACKRewritePass::test_linear, test/test_xnnpack_integration.py::TestXNNPACKConv1dTransformPass::test_conv1d_basic, test/test_xnnpack_integration.py::TestXNNPACKConv1dTransformPass::test_conv1d_with_relu_fc 2025-07-17T09:15:39.8052814Z 2025-07-17T09:15:43.0245468Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:15:43.0248465Z import pkg_resources 2025-07-17T09:15:43.1519849Z Running test_unary_ufuncs 3/3 ... [2025-07-17 09:15:43.151555] 2025-07-17T09:15:43.1520661Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:15:43.1523060Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_unary_ufuncs.py', '-m', 'not serial', '--shard-id=3', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:15:43.151979] 2025-07-17T09:16:30.5685415Z 2025-07-17T09:16:30.5686690Z test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_indexing_1.1_2c3cf2b710a0e119_.log 2025-07-17T09:16:30.5740766Z Running 92 items in this shard: test/test_indexing.py::TestIndexingCPU::test_advancedindex_big_cpu, test/test_indexing.py::TestIndexingCPU::test_advancedindex_cpu_float16, test/test_indexing.py::TestIndexingCPU::test_advancedindex_cpu_float64, test/test_indexing.py::TestIndexingCPU::test_basic_advanced_combined_cpu, test/test_indexing.py::TestIndexingCPU::test_bool_indices_accumulate_cpu, test/test_indexing.py::TestIndexingCPU::test_bool_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_bool_mask_assignment_cpu, test/test_indexing.py::TestIndexingCPU::test_byte_mask2d_cpu, test/test_indexing.py::TestIndexingCPU::test_byte_mask_accumulate_cpu, test/test_indexing.py::TestIndexingCPU::test_byte_mask_cpu, test/test_indexing.py::TestIndexingCPU::test_byte_tensor_assignment_cpu, test/test_indexing.py::TestIndexingCPU::test_cpu_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_cuda_broadcast_index_use_deterministic_algorithms_cpu, test/test_indexing.py::TestIndexingCPU::test_ellipsis_tensor_cpu, test/test_indexing.py::TestIndexingCPU::test_empty_index_cpu, test/test_indexing.py::TestIndexingCPU::test_empty_ndim_index_bool_cpu, test/test_indexing.py::TestIndexingCPU::test_empty_ndim_index_cpu, test/test_indexing.py::TestIndexingCPU::test_empty_slice_cpu, test/test_indexing.py::TestIndexingCPU::test_gather_take_along_dim_cross_device_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_getitem_scalars_cpu, test/test_indexing.py::TestIndexingCPU::test_index_cpu, test/test_indexing.py::TestIndexingCPU::test_index_getitem_copy_bools_slices_cpu, test/test_indexing.py::TestIndexingCPU::test_index_ind_dtype_cpu, test/test_indexing.py::TestIndexingCPU::test_index_limits_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_accumulate_duplicate_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_accumulate_empty_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_accumulate_expanded_values_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_accumulate_large_tensor_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_accumulate_non_contiguous_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_deterministic_with_optional_tensors_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_large_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_bool, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_complex128, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_complex64, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_index_scalar_with_bool_mask_cpu, test/test_indexing.py::TestIndexingCPU::test_index_setitem_bools_slices_cpu, test/test_indexing.py::TestIndexingCPU::test_index_src_datatype_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_src_datatype_cpu_bool, test/test_indexing.py::TestIndexingCPU::test_index_src_datatype_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_src_datatype_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_int_assignment_cpu, test/test_indexing.py::TestIndexingCPU::test_int_indices2d_cpu, test/test_indexing.py::TestIndexingCPU::test_int_indices_broadcast_cpu, test/test_indexing.py::TestIndexingCPU::test_int_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_invalid_device_cpu, test/test_indexing.py::TestIndexingCPU::test_invalid_index_cpu, test/test_indexing.py::TestIndexingCPU::test_jit_indexing_cpu, test/test_indexing.py::TestIndexingCPU::test_list_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_multi_dimensional_bool_mask_assignment_cpu, test/test_indexing.py::TestIndexingCPU::test_multi_dimensional_bool_mask_cpu, test/test_indexing.py::TestIndexingCPU::test_multiple_bool_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_multiple_byte_mask_cpu, test/test_indexing.py::TestIndexingCPU::test_multiple_int_cpu, test/test_indexing.py::TestIndexingCPU::test_none_cpu, test/test_indexing.py::TestIndexingCPU::test_out_of_bound_index_cpu, test/test_indexing.py::TestIndexingCPU::test_set_item_to_scalar_tensor_cpu, test/test_indexing.py::TestIndexingCPU::test_setitem_expansion_error_cpu, test/test_indexing.py::TestIndexingCPU::test_setitem_scalars_cpu, test/test_indexing.py::TestIndexingCPU::test_single_int_cpu, test/test_indexing.py::TestIndexingCPU::test_step_assignment_cpu, test/test_indexing.py::TestIndexingCPU::test_step_cpu, test/test_indexing.py::TestIndexingCPU::test_take_along_dim_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_take_along_dim_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_take_along_dim_invalid_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_take_along_dim_invalid_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_unravel_index_errors_cpu, test/test_indexing.py::TestIndexingCPU::test_variable_slicing_cpu, test/test_indexing.py::TestIndexingCPU::test_zero_dim_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_assignment_value_mismatch_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_indexing_alldims_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_indexing_onedim_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_indexing_twodim_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_indexing_weirdness_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_indexing_weirdness_tensors_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_list_indexing_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_shape_mismatch_cpu, test/test_indexing.py::NumpyTestsCPU::test_broadcast_subspace_cpu, test/test_indexing.py::NumpyTestsCPU::test_broaderrors_indexing_cpu, test/test_indexing.py::NumpyTestsCPU::test_ellipsis_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_empty_fancy_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_empty_tuple_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_everything_returns_views_cpu, test/test_indexing.py::NumpyTestsCPU::test_index_is_larger_cpu, test/test_indexing.py::NumpyTestsCPU::test_index_no_floats_cpu, test/test_indexing.py::NumpyTestsCPU::test_none_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_single_bool_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_single_int_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_trivial_fancy_out_of_bounds_cpu, test/test_indexing.py::NumpyTestsCPU::test_truncate_leading_1s_cpu 2025-07-17T09:16:30.5796658Z 2025-07-17T09:16:33.8757615Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:16:33.8760388Z import pkg_resources 2025-07-17T09:16:34.0028738Z Running nn/test_init 1/1 ... [2025-07-17 09:16:34.002447] 2025-07-17T09:16:34.0029467Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:16:34.0032026Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_init.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:16:34.002865] 2025-07-17T09:16:49.9430138Z 2025-07-17T09:16:49.9431339Z nn/test_init 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_init_1.1_f16f3ef8f6cc5d26_.log 2025-07-17T09:16:49.9444885Z Running 30 items in this shard: test/nn/test_init.py::TestNNInit::test_calculate_gain_leaky_relu, test/nn/test_init.py::TestNNInit::test_calculate_gain_leaky_relu_only_accepts_numbers, test/nn/test_init.py::TestNNInit::test_calculate_gain_linear, test/nn/test_init.py::TestNNInit::test_calculate_gain_nonlinear, test/nn/test_init.py::TestNNInit::test_calculate_gain_only_accepts_valid_nonlinearities, test/nn/test_init.py::TestNNInit::test_constant, test/nn/test_init.py::TestNNInit::test_deprecation, test/nn/test_init.py::TestNNInit::test_dirac_identity, test/nn/test_init.py::TestNNInit::test_dirac_only_works_on_3_4_5d_inputs, test/nn/test_init.py::TestNNInit::test_dirac_properties, test/nn/test_init.py::TestNNInit::test_eye, test/nn/test_init.py::TestNNInit::test_eye_only_works_on_2d_inputs, test/nn/test_init.py::TestNNInit::test_kaiming_normal, test/nn/test_init.py::TestNNInit::test_kaiming_normal_errors_on_inputs_smaller_than_2d, test/nn/test_init.py::TestNNInit::test_kaiming_normal_warning_on_0element_tensor, test/nn/test_init.py::TestNNInit::test_kaiming_uniform, test/nn/test_init.py::TestNNInit::test_kaiming_uniform_errors_on_inputs_smaller_than_2d, test/nn/test_init.py::TestNNInit::test_kaiming_uniform_warning_on_0element_tensor, test/nn/test_init.py::TestNNInit::test_normal, test/nn/test_init.py::TestNNInit::test_ones_and_zeros, test/nn/test_init.py::TestNNInit::test_orthogonal, test/nn/test_init.py::TestNNInit::test_sparse_default_std, test/nn/test_init.py::TestNNInit::test_sparse_only_works_on_2d_inputs, test/nn/test_init.py::TestNNInit::test_trunc_normal, test/nn/test_init.py::TestNNInit::test_trunc_normal_generator, test/nn/test_init.py::TestNNInit::test_uniform, test/nn/test_init.py::TestNNInit::test_xavier_normal, test/nn/test_init.py::TestNNInit::test_xavier_normal_errors_on_inputs_smaller_than_2d, test/nn/test_init.py::TestNNInit::test_xavier_uniform, test/nn/test_init.py::TestNNInit::test_xavier_uniform_errors_on_inputs_smaller_than_2d 2025-07-17T09:16:49.9459018Z 2025-07-17T09:16:53.1999397Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:16:53.2000955Z import pkg_resources 2025-07-17T09:16:53.3300678Z Running test_function_schema 1/1 ... [2025-07-17 09:16:53.329645] 2025-07-17T09:16:53.3301620Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:16:53.3305429Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_function_schema.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:16:53.330155] 2025-07-17T09:16:59.0041018Z 2025-07-17T09:16:59.0042150Z test_function_schema 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_function_schema_1.1_11635b8e8748fdaa_.log 2025-07-17T09:16:59.0048583Z Running 15 items in this shard: test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_arguments, test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_outputs, test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_structure, test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_with_smart_serialization, test/test_function_schema.py::TestFunctionSchema::test_forward_compatible_arguments_real_use_case, test/test_function_schema.py::TestFunctionSchema::test_forward_compatible_arguments_with_out, test/test_function_schema.py::TestFunctionSchema::test_forward_compatible_arguments_without_out, test/test_function_schema.py::TestFunctionSchema::test_hash_schema, test/test_function_schema.py::TestFunctionSchema::test_out_schema, test/test_function_schema.py::TestFunctionSchema::test_schema_error, test/test_function_schema.py::TestFunctionSchema::test_serialize_and_deserialize, test/test_function_schema.py::TestFunctionSchema::test_string_optional_parameter_default_value, test/test_function_schema.py::TestFunctionSchema::test_sym_int_argument_properly_parsed, test/test_function_schema.py::TestFunctionSchema::test_tensor_list_alias_annotation_properly_parsed, test/test_function_schema.py::TestFunctionSchema::test_tensor_option_arguments_properly_parsed 2025-07-17T09:16:59.0054772Z 2025-07-17T09:17:02.2072551Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:17:02.2074119Z import pkg_resources 2025-07-17T09:17:02.3341119Z Running torch_np/numpy_tests/core/test_scalar_ctors 1/1 ... [2025-07-17 09:17:02.333650] 2025-07-17T09:17:02.3342049Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:17:02.3344313Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalar_ctors.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:17:02.334067] 2025-07-17T09:17:12.4147663Z 2025-07-17T09:17:12.4149319Z torch_np/numpy_tests/core/test_scalar_ctors 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalar_ctors_1.1_3031a9cc17955d37_.log 2025-07-17T09:17:12.4179427Z Running 65 items in this shard: test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestFromString::test_bool, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestFromString::test_floating, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestFromString::test_floating_overflow, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestFromInt::test_intp, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestFromInt::test_uint64_from_negative, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t10_t20, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t10_t21, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t10_t22, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t11_t20, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t11_t21, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t11_t22, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t10_t20, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t10_t21, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t10_t22, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t10_t23, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t11_t20, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t11_t21, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t11_t22, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t11_t23, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t12_t20, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t12_t21, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t12_t22, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t12_t23 2025-07-17T09:17:12.4207189Z 2025-07-17T09:17:15.6139231Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:17:15.6142221Z import pkg_resources 2025-07-17T09:17:15.7417242Z Running test_sparse 1/2 ... [2025-07-17 09:17:15.741267] 2025-07-17T09:17:15.7417995Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:17:15.7420206Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sparse.py', '-m', 'not serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:17:15.741674] 2025-07-17T09:21:33.1602051Z 2025-07-17T09:21:33.1603430Z test_sparse_csr 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_csr_1.2_87411c2e43625c78_.log 2025-07-17T09:21:33.2759245Z Running 2352 items in this shard: test/test_sparse_csr.py::TestSparseCSRSampler::test_make_crow_indices, test/test_sparse_csr.py::TestSparseCSRCPU::test_add_SparseCSR_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_all_sparse_csr_SparseCSC_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_all_sparse_csr_SparseCSC_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_all_sparse_csr_SparseCSR_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSC_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSC_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSR_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSR_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_errors_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_0_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_1_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_1_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_1_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_25_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_0_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_0_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_1_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_1_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_25_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_25_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_1_m_0_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_1_m_1_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_1_m_1_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_1_m_1_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_1_m_25_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_1_m_25_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_0_m_0_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_0_m_0_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_0_m_0_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_0_m_1_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_0_m_1_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_0_m_1_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_10_m_0_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_10_m_0_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_10_m_1_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_10_m_1_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_10_m_25_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_1_m_0_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_1_m_0_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_1_m_0_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_1_m_1_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_1_m_25_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_1_m_25_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_1_n_1_m_25_cpu_float32, 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test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_amax_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_amax_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_amax_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_amin_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_amin_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_amin_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_amin_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_mean_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_mean_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_mean_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_prod_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_prod_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_prod_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_sum_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_sum_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_sum_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_sum_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_masked_sum_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_mul_cpu_bfloat16, 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test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tan_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tan_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tan_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tan_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tan_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tan_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tanh_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tanh_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tanh_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tanh_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tanh_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tanh_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_tanh_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_to_sparse_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_to_sparse_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_to_sparse_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_to_sparse_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_to_sparse_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_to_sparse_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_consistency_SparseCSR_to_sparse_cpu_int64, 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test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_constructor_shape_and_device_inference_factory_from_list_SparseCSR_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_constructor_shape_and_device_inference_factory_from_list_SparseCSR_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_constructor_shape_and_device_inference_factory_from_list_SparseCSR_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_constructor_shape_and_device_inference_factory_from_list_SparseCSR_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_constructor_shape_and_device_inference_factory_from_list_SparseCSR_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_constructor_shape_and_device_inference_factory_from_list_SparseCSR_cpu_int32, 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test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseBSR_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseBSR_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseBSR_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseBSR_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseBSR_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseBSR_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSR_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSR_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSR_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSR_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSC_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSC_cpu_float64, 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test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_bsr_dense_bmm_error_messages, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_bsr_scatter_mm, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_bsr_softmax, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_kernel 2025-07-17T09:21:33.3964259Z 2025-07-17T09:21:35.7229984Z Uploading artifacts took 2.56 seconds 2025-07-17T09:21:37.6149873Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:21:37.6153274Z import pkg_resources 2025-07-17T09:21:37.8056929Z Running torch_np/test_reductions 1/1 ... [2025-07-17 09:21:37.805144] 2025-07-17T09:21:37.8057814Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:21:37.8064206Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_reductions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:21:37.805599] 2025-07-17T09:22:59.0742831Z 2025-07-17T09:22:59.0744210Z test_unary_ufuncs 3/3 was successful, full logs can be found in artifacts with path test/test-reports/test_unary_ufuncs_3.3_670567f0ed231511_.log 2025-07-17T09:22:59.4097611Z Running 8092 items in this shard: test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_abs_angle_complex_to_float_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_byte_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_byte_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cdouble_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cdouble_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cdouble_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cdouble_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cdouble_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cdouble_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cdouble_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cfloat_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cfloat_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cfloat_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cfloat_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cfloat_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cfloat_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_cfloat_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_chalf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_chalf_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_chalf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_chalf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_chalf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_char_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_char_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_char_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_char_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_char_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_char_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_char_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_double_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_double_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_double_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_double_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_double_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_double_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_float_cpu_bfloat16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_reciprocal_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_reciprocal_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_round_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_round_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_round_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_round_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_rsqrt_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_rsqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_rsqrt_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_rsqrt_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sgn_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sgn_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sigmoid_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sign_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sign_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sign_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sign_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sign_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sign_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sign_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_signbit_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_signbit_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_signbit_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_signbit_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sin_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sin_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sin_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sin_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sin_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_sinc_cpu_float32, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_entr_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_entr_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_entr_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_erfcx_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_erfcx_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_i1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_i1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_i1e_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_i1e_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_log_ndtr_cpu_bool, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_multigammaln_mvlgamma_p_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_ndtr_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_ndtr_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_ndtr_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_ndtr_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_ndtri_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_ndtri_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_ndtri_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs_special_spherical_bessel_j0_cpu_bool, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_acos_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_acos_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_acos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_acos_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_acos_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_acos_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_acosh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_acosh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_acosh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_acosh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_angle_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_angle_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_angle_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_asin_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_asin_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_asin_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_asinh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_asinh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_asinh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_asinh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_asinh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_asinh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_atan_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_atan_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_atan_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_atan_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_atan_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_atan_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_atan_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_atanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_atanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_atanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_atanh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_bfloat16_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_bfloat16_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_bfloat16_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_bfloat16_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_bitwise_not_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_bitwise_not_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_bool_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_bool_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_bool_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_bool_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_bool_cpu_int32, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_ceil_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_ceil_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_ceil_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cfloat_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cfloat_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cfloat_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cfloat_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cfloat_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cfloat_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cfloat_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_chalf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_chalf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_chalf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_char_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_char_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_char_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_char_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_char_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_char_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_conj_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_conj_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_conj_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_conj_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_conj_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_conj_physical_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_conj_physical_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_conj_physical_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_conj_physical_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cos_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cos_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cos_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cos_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cosh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cosh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cosh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_cosh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_deg2rad_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_deg2rad_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_digamma_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_digamma_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_digamma_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_double_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_double_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_double_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_double_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_double_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_double_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erfc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erfc_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erfc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erfc_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erfc_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erfinv_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erfinv_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erfinv_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erfinv_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_erfinv_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_exp2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_exp2_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_exp2_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_exp2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_exp2_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_exp_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_exp_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_exp_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_exp_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_expm1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_expm1_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_expm1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_expm1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_fill_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_fill_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_float_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_float_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_floor_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_floor_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_floor_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_floor_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_floor_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_frac_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_frac_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_frexp_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_frexp_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_frexp_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_half_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_half_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_half_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_half_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_half_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_i0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_imag_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_int_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_int_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_int_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_int_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isfinite_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isfinite_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isfinite_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isfinite_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isfinite_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isinf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isinf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isinf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isnan_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isnan_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isnan_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isneginf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isneginf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isneginf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isposinf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isposinf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isposinf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isposinf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isreal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isreal_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_isreal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_jiterator_unary_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_jiterator_unary_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_jiterator_unary_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_jiterator_unary_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_jiterator_unary_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_lgamma_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_lgamma_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log10_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log10_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log10_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log10_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log1p_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log1p_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log1p_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log1p_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log2_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log2_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_log_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_logical_not_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_logical_not_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_logical_not_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_logical_not_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_logical_not_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_logit_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_logit_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_logit_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_logit_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_long_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_long_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_long_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_long_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_long_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_long_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_mvlgamma_mvlgamma_p_1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nan_to_num_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nan_to_num_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nan_to_num_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nan_to_num_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nan_to_num_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_neg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_neg_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_neg_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_neg_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_celu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_celu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_elu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_elu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardtanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_logsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_mish_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_mish_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_mish_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_relu6_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_relu6_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_relu6_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_relu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_relu_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_rrelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_silu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softplus_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softsign_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softsign_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softsign_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_tanhshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_tanhshrink_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_threshold_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_threshold_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_threshold_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_2_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_2_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_3_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_4_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_polygamma_polygamma_n_4_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_positive_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_positive_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_positive_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_positive_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_positive_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_rad2deg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_rad2deg_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_rad2deg_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_real_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_real_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_real_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_real_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_real_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_real_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_reciprocal_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_reciprocal_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_reciprocal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_reciprocal_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_reciprocal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_round_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_round_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_round_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_round_decimals_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_round_decimals_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_rsqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_rsqrt_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_rsqrt_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_rsqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_rsqrt_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_rsqrt_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sgn_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sgn_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sgn_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sgn_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sgn_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sgn_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sgn_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_short_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_short_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_short_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sigmoid_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sigmoid_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sigmoid_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sign_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sign_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sign_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_signbit_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_signbit_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sin_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sin_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sin_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sin_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sin_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sinc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sinc_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sinc_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sinc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sinc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sinh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_sinh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_airy_ai_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_airy_ai_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_airy_ai_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_bessel_j0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_bessel_j0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_bessel_j0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_bessel_j1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_bessel_j1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_bessel_j1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_bessel_j1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_bessel_y0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_bessel_y0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_bessel_y1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_entr_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_entr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_entr_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_entr_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_entr_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_erfcx_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_erfcx_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_erfcx_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_erfcx_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_erfcx_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i0e_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i0e_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i0e_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i0e_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i0e_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i0e_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i1e_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i1e_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i1e_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i1e_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_i1e_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_log_ndtr_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_log_ndtr_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_log_ndtr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_log_ndtr_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_log_ndtr_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_i0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_i0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_i0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_i0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_i1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_i1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_k0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_k0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_k0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_k0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_k0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_k1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_modified_bessel_k1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_ndtr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_ndtr_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_ndtr_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_ndtri_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_ndtri_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_ndtri_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_ndtri_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_ndtri_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_polygamma_special_polygamma_n_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_polygamma_special_polygamma_n_0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_scaled_modified_bessel_k0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_scaled_modified_bessel_k0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_scaled_modified_bessel_k1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_scaled_modified_bessel_k1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_special_scaled_modified_bessel_k1_cpu_int8, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_neg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_neg_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_neg_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_neg_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_neg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_neg_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_elu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_hardshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_hardtanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_hardtanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_prelu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_prelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_selu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_softshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_threshold_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_threshold_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_threshold_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_positive_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_positive_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_rad2deg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_rad2deg_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_rad2deg_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_real_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_real_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_real_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_real_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_real_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_reciprocal_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_reciprocal_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_reciprocal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_reciprocal_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_reciprocal_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_round_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_round_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_rsqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_rsqrt_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sgn_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sgn_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sgn_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sgn_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sgn_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sigmoid_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sigmoid_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sigmoid_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sign_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sign_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sign_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_signbit_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_signbit_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_signbit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_signbit_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_signbit_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sin_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sin_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sin_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sin_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sin_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sin_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sinc_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sinc_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sinc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sinh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sinh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sinh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_bessel_j0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_bessel_j0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_bessel_j1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_entr_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_entr_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_entr_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_entr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_entr_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_entr_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_erfcx_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_erfcx_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_erfcx_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_i0e_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_i0e_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_i1e_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_i1e_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_i1e_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_i1e_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_log_ndtr_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_log_ndtr_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_logit_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_logit_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_logit_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_logit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_logit_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_logit_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_logit_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_multigammaln_mvlgamma_p_1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_multigammaln_mvlgamma_p_1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_multigammaln_mvlgamma_p_1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_multigammaln_mvlgamma_p_1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_multigammaln_mvlgamma_p_3_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_multigammaln_mvlgamma_p_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_multigammaln_mvlgamma_p_3_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_multigammaln_mvlgamma_p_5_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_multigammaln_mvlgamma_p_5_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_multigammaln_mvlgamma_p_5_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_multigammaln_mvlgamma_p_5_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_ndtr_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_ndtr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_ndtr_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_ndtr_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_ndtr_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_special_ndtri_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sqrt_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_sqrt_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_square_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_square_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_square_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_square_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_square_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_square_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_tan_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_tan_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_tan_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_tan_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_tanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_tanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_tanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_tanh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_trunc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_trunc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_trunc_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_trunc_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asin_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asin_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asin_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asin_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asin_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asinh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asinh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asinh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asinh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bitwise_not_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bitwise_not_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bool_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bool_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bool_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bool_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_byte_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_byte_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cdouble_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cdouble_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cdouble_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cdouble_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cdouble_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cdouble_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_ceil_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_ceil_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_ceil_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cfloat_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cfloat_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cfloat_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cfloat_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfinv_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_fill_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_fill_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_fill_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_frac_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_frac_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_frac_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_imag_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logit_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_celu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_celu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_elu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_logsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_logsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_mish_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_prelu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_prelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu6_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu6_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_rrelu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_selu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_selu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_selu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_silu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_silu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_decimals_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_decimals_0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rsqrt_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rsqrt_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rsqrt_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sgn_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sgn_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sgn_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_short_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_short_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_short_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_short_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sigmoid_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sigmoid_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sign_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sign_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sign_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sign_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sign_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sign_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_signbit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_signbit_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sin_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sin_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sin_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sin_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sin_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sinc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sinc_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sinc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sinc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sinh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sinh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sinh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sinh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sinh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_airy_ai_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_airy_ai_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_bessel_j0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_bessel_j0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_bessel_j1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_bessel_j1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_bessel_y0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_bessel_y0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_bessel_y1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_bessel_y1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_entr_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_entr_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_entr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_entr_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_erfcx_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_erfcx_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_i0e_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_i0e_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_i0e_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_i0e_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_i1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_i1e_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_i1e_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_i1e_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_log_ndtr_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_log_ndtr_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_i0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_i0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_i1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_i1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_i1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_i1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_k0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_k0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_k0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_k0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_k1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_k1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_k1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_modified_bessel_k1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_ndtr_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_ndtr_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_ndtr_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_ndtri_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_ndtri_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_ndtri_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_polygamma_special_polygamma_n_0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_scaled_modified_bessel_k1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_scaled_modified_bessel_k1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_scaled_modified_bessel_k1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_spherical_bessel_j0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_special_spherical_bessel_j0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sqrt_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_sqrt_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_square_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_square_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_square_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_tan_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_tan_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_tan_cpu_int16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_atanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_bitwise_not_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_bitwise_not_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_bitwise_not_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_ceil_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_ceil_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_ceil_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_ceil_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_ceil_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_conj_cpu_int16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_reciprocal_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_reciprocal_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_reciprocal_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_reciprocal_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_round_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_round_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_rsqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_rsqrt_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_rsqrt_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_rsqrt_cpu_float16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_entr_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_entr_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_entr_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_erfcx_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_erfcx_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_erfcx_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_i0e_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_i0e_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_i1_cpu_bool, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_multigammaln_mvlgamma_p_1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_multigammaln_mvlgamma_p_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_multigammaln_mvlgamma_p_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_multigammaln_mvlgamma_p_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_multigammaln_mvlgamma_p_3_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_multigammaln_mvlgamma_p_3_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_multigammaln_mvlgamma_p_5_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_multigammaln_mvlgamma_p_5_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_ndtr_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_ndtr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_ndtr_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_ndtri_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_spherical_bessel_j0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_special_spherical_bessel_j0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_sqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_sqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_square_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_tan_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_tan_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_tan_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_tan_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_tanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_tanh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_tanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_tanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_tanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_tanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_tanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed__refs_trunc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_abs_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_abs_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acosh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acosh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acosh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_asin_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_asin_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_asin_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_asinh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_asinh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_atan_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_atan_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_atan_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_atan_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_atanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_atanh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_atanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_atanh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cdouble_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cdouble_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cdouble_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cdouble_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_ceil_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_ceil_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_ceil_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_ceil_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_ceil_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_ceil_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_floor_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frac_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frac_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frexp_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frexp_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_imag_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_imag_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_long_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_long_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_long_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nan_to_num_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_celu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_elu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_elu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_elu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardsigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardtanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardtanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardtanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_prelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_rrelu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_selu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softplus_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_4_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_4_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_neg_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_airy_ai_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_airy_ai_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_erfcx_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_erfcx_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_erfcx_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_i0e_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_i0e_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_i0e_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_i1_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_i1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_i1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_i1e_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_log_ndtr_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_log_ndtr_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_log_ndtr_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_log_ndtr_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_modified_bessel_i0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_modified_bessel_i0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_modified_bessel_i0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_modified_bessel_i1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_modified_bessel_i1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_modified_bessel_k0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_modified_bessel_k0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_modified_bessel_k0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_modified_bessel_k1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_ndtr_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_ndtr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_ndtri_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_ndtri_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_ndtri_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_polygamma_special_polygamma_n_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_polygamma_special_polygamma_n_0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_polygamma_special_polygamma_n_0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_scaled_modified_bessel_k0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_scaled_modified_bessel_k0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_scaled_modified_bessel_k0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_scaled_modified_bessel_k1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_scaled_modified_bessel_k1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_spherical_bessel_j0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sqrt_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sqrt_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sqrt_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_square_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_square_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_square_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_square_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_square_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_square_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tan_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tan_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tan_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_trunc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_trunc_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_digamma_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_exp_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_exp_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_exp_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_acosh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_acosh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_asin_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_asin_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_erfinv_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log10_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log10_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log10_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log1p_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log1p_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_rsqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_logit_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_logit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_3_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_5_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_5_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_ndtri_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_ndtri_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_sqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_sqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_sqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acos_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acosh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acosh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_asin_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_atanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_atanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_erfinv_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_erfinv_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log10_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log1p_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_logit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_1_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_sqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_frexp_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardshrink_edge_cases_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_range1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_range2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_range2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_special_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igamma_common_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igammac_common_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igammac_edge_cases_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igammac_edge_cases_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igammac_edge_cases_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_isposinf_isneginf_non_boolean_output_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_isposinf_isneginf_non_boolean_output_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_isposinf_isneginf_non_boolean_output_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_isposinf_isneginf_non_boolean_output_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_isposinf_isneginf_non_boolean_output_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_log1p_complex_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_mish_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_nan_to_num_bfloat16_cpu, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_nan_to_num_complex_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_nan_to_num_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_nan_to_num_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_nan_to_num_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_nan_to_num_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_bfloat16_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_bfloat16_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_bfloat16_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_bool_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_bool_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_bool_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_byte_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_byte_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_byte_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_byte_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_byte_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_byte_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_cdouble_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_cdouble_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_cdouble_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_cfloat_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_cfloat_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_cfloat_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_cfloat_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_cfloat_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_chalf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_chalf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_chalf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_char_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_char_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_char_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_double_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_double_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_double_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_double_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_double_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_float_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_float_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_float_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_float_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_half_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_half_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_half_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_half_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_int_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_int_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_long_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_long_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig__refs__conversions_long_cpu_int8, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_angle_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_angle_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_asin_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_asin_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_asin_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_asin_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_asinh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_asinh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_asinh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_atan_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_atan_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_atan_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_atan_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_atan_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_atanh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_atanh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_atanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_atanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_atanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bfloat16_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bfloat16_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bfloat16_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bfloat16_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bitwise_not_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfc_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfc_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfinv_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfinv_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfinv_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfinv_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_exp2_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_exp2_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_exp2_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_exp2_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_exp_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_exp_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_exp_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_expm1_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_expm1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_fill_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_fill_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_fill_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_fill_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_float_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_float_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_floor_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_floor_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_floor_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_floor_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_floor_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_floor_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_frac_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_frexp_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_half_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_half_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_half_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_half_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_i0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_i0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_i0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_i0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_i0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_imag_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_imag_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_int_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_int_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isfinite_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isfinite_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isfinite_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isfinite_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isfinite_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isfinite_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isfinite_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isinf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isinf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isinf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isnan_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isnan_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isnan_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isnan_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isnan_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isnan_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isnan_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isneginf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isneginf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isposinf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isposinf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isposinf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_lgamma_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_lgamma_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_lgamma_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_lgamma_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log10_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log10_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log10_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log10_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log1p_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log1p_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log1p_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log1p_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log2_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log2_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log2_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log2_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_log_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_logical_not_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_logical_not_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_logical_not_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_logical_not_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_logical_not_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_logit_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_logit_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_logit_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_logit_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_logit_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_long_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_long_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_long_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_long_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_long_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_long_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_long_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_long_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_3_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_5_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nan_to_num_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nan_to_num_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nan_to_num_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nan_to_num_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_celu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_celu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_celu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_logsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_logsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_logsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_selu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_silu_complex_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_silu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softplus_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softplus_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_2_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_positive_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_positive_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_real_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_real_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_real_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_real_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_real_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_real_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_reciprocal_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rsqrt_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rsqrt_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rsqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rsqrt_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rsqrt_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sgn_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sgn_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_short_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sigmoid_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sigmoid_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sigmoid_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sign_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sign_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sign_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_signbit_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_signbit_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_signbit_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_signbit_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_signbit_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_signbit_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sin_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sin_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sin_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sin_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sin_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sin_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinc_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinc_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinc_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinc_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_y0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_y0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_y0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_y0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_y1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_y1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_y1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_y1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_y1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_entr_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_entr_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_entr_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_entr_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_erfcx_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_erfcx_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_erfcx_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_i0e_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_i0e_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_i1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_i1_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_i1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_i1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_i1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_i1e_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_i1e_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_i1e_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_log_ndtr_cpu_float32, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_prelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_relu6_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_relu6_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_relu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_relu_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_relu_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_selu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_silu_complex_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_silu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_silu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_silu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_softplus_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_softshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_softsign_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_softsign_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_softsign_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_softsign_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_tanhshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_tanhshrink_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_nn_functional_tanhshrink_cpu_float16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_polygamma_polygamma_n_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_polygamma_polygamma_n_3_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_polygamma_polygamma_n_3_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_polygamma_polygamma_n_4_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_polygamma_polygamma_n_4_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_positive_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_positive_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rad2deg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rad2deg_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rad2deg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rad2deg_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_real_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_real_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_real_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_real_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_round_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_round_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_round_decimals_0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_round_decimals_0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_round_decimals_0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_round_decimals_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_round_decimals_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_round_decimals_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_round_decimals_neg_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rsqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rsqrt_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rsqrt_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rsqrt_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rsqrt_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rsqrt_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rsqrt_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_rsqrt_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_sgn_cpu_bool, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_entr_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_entr_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_entr_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_entr_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_erfcx_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_erfcx_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_i0e_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_i1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_i1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_i1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_i1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_i1e_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_i1e_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_i1e_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_i1e_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_log_ndtr_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_log_ndtr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_log_ndtr_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_log_ndtr_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_log_ndtr_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_modified_bessel_i0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_modified_bessel_i0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_modified_bessel_i1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_modified_bessel_i1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_modified_bessel_k0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_modified_bessel_k1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_modified_bessel_k1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_ndtr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_ndtr_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_ndtri_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_special_ndtri_cpu_int16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_logit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nan_to_num_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nan_to_num_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_neg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_neg_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_celu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_hardsigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_logsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_logsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_mish_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_selu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_silu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_softsign_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_tanhshrink_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_tanhshrink_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_threshold_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_nn_functional_threshold_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_polygamma_polygamma_n_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_polygamma_polygamma_n_0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_polygamma_polygamma_n_0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_polygamma_polygamma_n_1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_polygamma_polygamma_n_1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_polygamma_polygamma_n_2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_polygamma_polygamma_n_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_polygamma_polygamma_n_4_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_positive_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_positive_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_real_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_real_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_real_cpu_float16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_special_spherical_bessel_j0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_sqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_square_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_square_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_tan_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_tan_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_tan_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_tanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_extremal_trunc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_abs_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_abs_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_abs_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_acos_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_acos_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_acos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_acos_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_acosh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_acosh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_acosh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_acosh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_acosh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_asin_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_asin_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_asin_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_asin_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_asinh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_asinh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_asinh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_asinh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_atan_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_atan_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_atan_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_atanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_atanh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_atanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_atanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_atanh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_atanh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_bitwise_not_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_bitwise_not_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_ceil_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_ceil_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_ceil_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_ceil_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_ceil_cpu_uint8, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_cos_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_cos_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_cosh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_cosh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_cosh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_deg2rad_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_deg2rad_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_deg2rad_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_deg2rad_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_digamma_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_digamma_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_digamma_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_erf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_erf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_erf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_erf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_erfc_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_erfc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_large__refs_erfc_cpu_int16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_nn_functional_tanhshrink_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_nn_functional_tanhshrink_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_nn_functional_threshold_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_nn_functional_threshold_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_2_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_3_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_3_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_3_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_4_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_4_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_4_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_polygamma_polygamma_n_4_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_positive_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_positive_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_positive_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_positive_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_positive_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_rad2deg_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_real_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_real_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_real_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_real_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_real_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_real_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_reciprocal_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_reciprocal_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_reciprocal_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_reciprocal_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_reciprocal_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_reciprocal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_round_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_round_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_round_decimals_0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_round_decimals_0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_round_decimals_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_round_decimals_neg_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_round_decimals_neg_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_rsqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_rsqrt_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_rsqrt_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_rsqrt_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_rsqrt_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sgn_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sgn_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sgn_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sigmoid_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sigmoid_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sign_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sign_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sign_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sign_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sign_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_signbit_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_signbit_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_signbit_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sin_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sin_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sin_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sin_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sin_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sinc_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sinc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sinc_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sinh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sinh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sinh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sinh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_airy_ai_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_airy_ai_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_airy_ai_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_bessel_j0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_bessel_j1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_bessel_y0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_bessel_y0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_bessel_y1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_bessel_y1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_bessel_y1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_bessel_y1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_bessel_y1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_entr_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_entr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_entr_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_entr_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_erfcx_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_i0e_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_i0e_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_i1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_i1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_i1e_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_i1e_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_i1e_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_i1e_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_i1e_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_i1e_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_log_ndtr_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_log_ndtr_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_log_ndtr_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_log_ndtr_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_i0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_i0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_i0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_i1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_i1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_i1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_i1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_k0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_k0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_k0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_k1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_k1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_modified_bessel_k1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_ndtr_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_ndtr_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_ndtr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_ndtr_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_ndtri_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_polygamma_special_polygamma_n_0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_polygamma_special_polygamma_n_0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_scaled_modified_bessel_k0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_scaled_modified_bessel_k1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_special_spherical_bessel_j0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sqrt_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sqrt_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sqrt_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_sqrt_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_square_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_square_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_square_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_square_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_square_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_square_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_tan_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_tan_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_tanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_tanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_tanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_tanh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_silu_complex_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_silu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_special_i0_i1_vs_scipy_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_threshold_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_threshold_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_unary_out_op_mem_overlap_cpu_float64 2025-07-17T09:22:59.7338221Z 2025-07-17T09:23:02.5073804Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:23:02.5076857Z import pkg_resources 2025-07-17T09:23:02.6346899Z Running profiler/test_profiler_tree 1/1 ... [2025-07-17 09:23:02.633611] 2025-07-17T09:23:02.6348079Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:23:02.6350282Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_profiler_tree.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:23:02.634004] 2025-07-17T09:23:09.3102787Z 2025-07-17T09:23:09.3104385Z profiler/test_profiler_tree 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_profiler_tree_1.1_dae692086fcb3b6e_.log 2025-07-17T09:23:09.3113872Z Running 10 items in this shard: test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_cuda, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_cuda_detailed, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_cuda_with_stream, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_memory, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_memory_and_stack, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_record_function, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_stack_and_modules, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_stack_and_torch_dispatch, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_stack_and_torch_function 2025-07-17T09:23:09.3126621Z 2025-07-17T09:23:12.8070999Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:23:12.9334486Z import pkg_resources 2025-07-17T09:23:12.9335135Z Running test_type_promotion 1/1 ... [2025-07-17 09:23:12.933084] 2025-07-17T09:23:12.9335818Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:23:12.9338086Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_type_promotion.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:23:12.933486] 2025-07-17T09:23:37.7304819Z 2025-07-17T09:23:37.7306358Z torch_np/test_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_reductions_1.1_0b3902b0302681aa_.log 2025-07-17T09:23:37.8175116Z Running 966 items in this shard: test/torch_np/test_reductions.py::TestFlatnonzero::test_basic, test/torch_np/test_reductions.py::TestAny::test_basic, test/torch_np/test_reductions.py::TestAny::test_method_vs_function, test/torch_np/test_reductions.py::TestAny::test_nd, test/torch_np/test_reductions.py::TestAll::test_basic, test/torch_np/test_reductions.py::TestAll::test_method_vs_function, test/torch_np/test_reductions.py::TestAll::test_nd, test/torch_np/test_reductions.py::TestMean::test_mean, test/torch_np/test_reductions.py::TestMean::test_mean_float16, test/torch_np/test_reductions.py::TestMean::test_mean_values, test/torch_np/test_reductions.py::TestMean::test_mean_where, 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test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func2_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func2_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func2_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func3_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func3_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func3_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func3_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func3_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func3_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func3_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func3_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func3_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func10, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func11, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func3, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func4, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func9, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_array_axis_func0, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_array_axis_func1, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_axis_bad_tuple_func0, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_axis_bad_tuple_func1, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_axis_empty_generic_func0, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_axis_empty_generic_func1, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_bad_axis_func0, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_bad_axis_func1 2025-07-17T09:23:37.9010978Z 2025-07-17T09:23:41.1623684Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:23:41.1627212Z import pkg_resources 2025-07-17T09:23:41.2879705Z Running dynamo/test_python_autograd 1/1 ... [2025-07-17 09:23:41.287538] 2025-07-17T09:23:41.2880973Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-07-17T09:23:41.2887023Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_python_autograd.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 09:23:41.287971] 2025-07-17T09:23:45.2220031Z 2025-07-17T09:23:45.2221594Z dynamo/test_python_autograd 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_python_autograd_1.1_f43aedeba2e81208_.log 2025-07-17T09:23:45.2222919Z 2025-07-17T09:23:48.5996757Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:23:48.5999587Z import pkg_resources 2025-07-17T09:24:51.2206415Z 2025-07-17T09:24:51.2207558Z test_sparse 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_1.2_335d63c454fd2db5_.log 2025-07-17T09:24:51.2898030Z Running 1572 items in this shard: test/test_sparse.py::TestSparseOneOff::test_cuda_from_cpu, test/test_sparse.py::TestSparseMeta::test_add_meta_SparseBSC_float64, test/test_sparse.py::TestSparseMeta::test_add_meta_SparseBSR_float64, test/test_sparse.py::TestSparseMeta::test_add_meta_SparseCOO_float64, test/test_sparse.py::TestSparseMeta::test_add_meta_SparseCSC_float64, test/test_sparse.py::TestSparseMeta::test_fake_SparseCOO_float64, test/test_sparse.py::TestSparseMeta::test_meta_SparseBSC_float64, test/test_sparse.py::TestSparseMeta::test_meta_SparseCSR_float64, test/test_sparse.py::TestSparseMeta::test_print_meta_SparseBSC_float64, test/test_sparse.py::TestSparseMeta::test_print_meta_SparseCOO_float64, test/test_sparse.py::TestSparseMeta::test_sum_meta_SparseBSC_float64, test/test_sparse.py::TestSparseMeta::test_sum_meta_SparseBSR_float64, test/test_sparse.py::TestSparseMeta::test_sum_meta_SparseCOO_float64, test/test_sparse.py::TestSparseMeta::test_sum_meta_SparseCSC_float64, test/test_sparse.py::TestSparseMeta::test_to_meta_SparseCOO_float64, test/test_sparse.py::TestSparseMeta::test_zeros_like_fake_SparseBSR_float64, test/test_sparse.py::TestSparseMeta::test_zeros_like_fake_SparseCSC_float64, test/test_sparse.py::TestSparseMeta::test_zeros_like_meta_SparseCOO_float64, test/test_sparse.py::TestSparseMeta::test_zeros_like_meta_SparseCSC_float64, test/test_sparse.py::TestSparseMeta::test_zeros_like_meta_SparseCSR_float64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_abs_cpu_int16, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_abs_cpu_int8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_abs_cpu_uint8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_asin_cpu_complex64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_asin_cpu_float32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_asin_cpu_int32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_asin_cpu_int8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_asinh_cpu_complex128, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_asinh_cpu_float64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_asinh_cpu_int64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_asinh_cpu_uint8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_atan_cpu_float32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_atan_cpu_int64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_atan_cpu_int8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_atanh_cpu_float32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_atanh_cpu_int64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_atanh_cpu_int8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_ceil_cpu_float64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_ceil_cpu_int32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_ceil_cpu_int64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_ceil_cpu_uint8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_conj_cpu_complex128, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_conj_cpu_complex64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_conj_cpu_float64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_conj_cpu_int32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_conj_cpu_int64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_conj_physical_cpu_complex128, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_conj_physical_cpu_complex64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_conj_physical_cpu_float64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_conj_physical_cpu_int64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_conj_physical_cpu_int8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_conj_physical_cpu_uint8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_deg2rad_cpu_float64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_deg2rad_cpu_int16, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_deg2rad_cpu_uint8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_erf_cpu_float64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_erf_cpu_int64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_erf_cpu_int8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_erf_cpu_uint8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_expm1_cpu_float64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_expm1_cpu_int32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_floor_cpu_float64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_floor_cpu_int64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_floor_cpu_uint8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_frac_cpu_float32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isinf_cpu_complex128, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isinf_cpu_float32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isinf_cpu_int16, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isinf_cpu_int64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isnan_cpu_complex64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isnan_cpu_float32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isnan_cpu_int64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isneginf_cpu_float32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isneginf_cpu_int16, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isneginf_cpu_int64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isneginf_cpu_int8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isposinf_cpu_int32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_isposinf_cpu_int8, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_log1p_cpu_float32, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_log1p_cpu_float64, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_log1p_cpu_int16, test/test_sparse.py::TestSparseUnaryUfuncsCPU::test_inplace_log1p_cpu_int8, 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test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseBSR_int64_cpu_float16, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseBSR_int64_cpu_int16, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseBSR_int64_cpu_int32, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseBSR_int64_cpu_int64, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int32_cpu_bool, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int32_cpu_complex128, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int32_cpu_float64, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int32_cpu_int64, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int32_cpu_int8, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int32_cpu_uint8, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int64_cpu_bool, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int64_cpu_float32, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int64_cpu_float64, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int64_cpu_int16, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int64_cpu_int32, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int64_cpu_int64, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCOO_int64_cpu_int8, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int32_cpu_bfloat16, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int32_cpu_bool, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int32_cpu_complex64, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int32_cpu_float16, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int32_cpu_float64, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int32_cpu_int32, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int32_cpu_uint8, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int64_cpu_bfloat16, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int64_cpu_complex128, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int64_cpu_complex64, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int64_cpu_float16, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int64_cpu_int16, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int64_cpu_int32, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int64_cpu_int64, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int64_cpu_int8, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSC_int64_cpu_uint8, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSR_int32_cpu_bfloat16, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSR_int32_cpu_bool, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSR_int64_cpu_bool, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSR_int64_cpu_complex64, test/test_sparse.py::TestSparseAnyCPU::test_to_sparse_Strided_SparseCSR_int64_cpu_int64, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_ccol_indices_SparseBSC_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_ccol_indices_SparseBSR_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_ccol_indices_Strided_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_coalesce_SparseBSR_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_coalesce_SparseCOO_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_col_indices_SparseBSC_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_col_indices_SparseCOO_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_col_indices_Strided_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_indices_SparseBSR_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_indices_SparseCOO_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_indices_SparseCSC_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_indices_SparseCSR_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_indices_Strided_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_is_coalesced_SparseBSC_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_is_coalesced_SparseBSR_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_is_coalesced_SparseCOO_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_is_coalesced_SparseCSC_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_is_coalesced_Strided_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_row_indices_SparseCOO_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_row_indices_SparseCSC_cpu, test/test_sparse.py::TestSparseAnyCPU::test_unsupported_backend_error_message_values_Strided_cpu 2025-07-17T09:24:51.3456881Z 2025-07-17T09:24:54.3627539Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-07-17T09:24:54.3630640Z import pkg_resources 2025-07-17T09:25:42.2383277Z 2025-07-17T09:25:42.2384434Z test_type_promotion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_type_promotion_1.1_cd55063b07292fe3_.log 2025-07-17T09:25:42.2564299Z Running 423 items in this shard: test/test_type_promotion.py::TestTypePromotionCPU::test_add_wrapped_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_alpha_mismatch_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_alternate_result_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_bfloat16_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_booleans_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_can_cast_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_cat_different_dtypes_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_cat_out_different_dtypes_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_bool_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_bool_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_bool_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_bool_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float64_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_int32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_int32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_int32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_int32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_bool_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_bool_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_bool_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_bool_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_float32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_float32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_float32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_float32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_float64_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_float64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_float64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_float64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_int32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_int32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_int32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_int32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_bool_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_bool_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_bool_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_bool_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_float32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_float32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_float32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_float32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_float64_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_float64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_float64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_float64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_int32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_int32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_int32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_int32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_bool_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_bool_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_bool_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_bool_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_float32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_float32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_float32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_float32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_float64_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_float64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_float64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_float64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_int32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_int32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_int32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_int32_int32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_comparison_ops_with_type_promotion_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_complex_assertraises_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_complex_half_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_complex_promotion_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_complex_scalar_mult_tensor_promotion_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_computation_ignores_out_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_create_bool_tensors_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_cpu_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_cpu_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_cpu_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_cpu_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_cpu_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_cpu_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_inplace_cpu_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_inplace_cpu_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_inplace_cpu_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_inplace_cpu_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_inplace_cpu_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_inplace_cpu_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_inplace_cpu_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_inplace_cpu_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_out_cpu_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_out_cpu_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_out_cpu_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_out_cpu_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_out_cpu_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_out_cpu_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_out_cpu_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_div_promotion_out_cpu_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_float_promotion_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_from_issue_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_half_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_indexing_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_indexing_fail_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_inplace_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_int_promotion_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_int_to_float_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_integer_addcdiv_deprecated_cpu_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_integer_addcdiv_deprecated_cpu_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_integer_addcdiv_deprecated_cpu_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_integer_addcdiv_deprecated_cpu_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_integer_addcdiv_deprecated_cpu_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_lt_with_type_promotion_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_many_promotions_cpu, 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test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_tensor_vs_scalar_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_add_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_promotion_cpu_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_promotion_cpu_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_promotion_cpu_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_promotion_cpu_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_promotion_cpu_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_mul_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_sub_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_ternary_out_promotion_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_transpose_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex128_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex128_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex128_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex128_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex128_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float32_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float32_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float32_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_int64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_int64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_int64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_int64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_int64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_unsigned_cpu 2025-07-17T09:25:42.2735676Z 2025-07-17T09:25:43.0263109Z Running test batch 'tests to run' cost 8280.02 seconds 2025-07-17T09:25:45.3084464Z 2025-07-17T09:25:45.3085056Z real 138m6.668s 2025-07-17T09:25:45.3085483Z user 297m10.303s 2025-07-17T09:25:45.3085713Z sys 45m31.826s 2025-07-17T09:25:45.3109875Z + assert_git_not_dirty 2025-07-17T09:25:45.3132490Z + [[ linux-jammy-py3.13-clang12 != *rocm* ]] 2025-07-17T09:25:45.3139185Z + [[ linux-jammy-py3.13-clang12 != *xla* ]] 2025-07-17T09:25:45.3170357Z ++ git status --porcelain 2025-07-17T09:25:45.3171101Z ++ grep -v '?? third_party' 2025-07-17T09:26:27.6409449Z ++ true 2025-07-17T09:26:27.6442012Z + git_status= 2025-07-17T09:26:27.6442293Z + [[ -n '' ]] 2025-07-17T09:26:27.6448061Z + [[ 2 == 1 ]] 2025-07-17T09:26:27.6473285Z + sccache_epilogue 2025-07-17T09:26:27.6473866Z + echo '::group::Sccache Compilation Log' 2025-07-17T09:26:27.6474680Z ##[group]Sccache Compilation Log 2025-07-17T09:26:27.6475065Z + echo '=================== sccache compilation log ===================' 2025-07-17T09:26:27.6475498Z =================== sccache compilation log =================== 2025-07-17T09:26:27.6476140Z + python /var/lib/jenkins/workspace/.ci/pytorch/print_sccache_log.py /var/lib/jenkins/sccache_error.log 2025-07-17T09:26:27.6618933Z + echo '=========== If your build fails, please take a look at the log above for possible reasons ===========' 2025-07-17T09:26:27.6619728Z =========== If your build fails, please take a look at the log above for possible reasons =========== 2025-07-17T09:26:27.6620249Z + sccache --show-stats 2025-07-17T09:26:27.6657832Z Compile requests 2689 2025-07-17T09:26:27.6658343Z Compile requests executed 98 2025-07-17T09:26:27.6658736Z Cache hits 60 2025-07-17T09:26:27.6659115Z Cache hits (C/C++) 60 2025-07-17T09:26:27.6659738Z Cache misses 38 2025-07-17T09:26:27.6660240Z Cache misses (C/C++) 38 2025-07-17T09:26:27.6661241Z Cache hits rate 61.22 % 2025-07-17T09:26:27.6661604Z Cache hits rate (C/C++) 61.22 % 2025-07-17T09:26:27.6662096Z Cache timeouts 0 2025-07-17T09:26:27.6662633Z Cache read errors 0 2025-07-17T09:26:27.6662955Z Forced recaches 0 2025-07-17T09:26:27.6663260Z Cache write errors 0 2025-07-17T09:26:27.6663573Z Cache errors 0 2025-07-17T09:26:27.6663894Z Compilations 38 2025-07-17T09:26:27.6664209Z Compilation failures 0 2025-07-17T09:26:27.6664545Z Non-cacheable compilations 0 2025-07-17T09:26:27.6664880Z Non-cacheable calls 6 2025-07-17T09:26:27.6665206Z Non-compilation calls 2585 2025-07-17T09:26:27.6665528Z Unsupported compiler calls 0 2025-07-17T09:26:27.6665883Z Average cache write 0.052 s 2025-07-17T09:26:27.6666217Z Average compiler 12.119 s 2025-07-17T09:26:27.6666539Z Average cache read hit 0.039 s 2025-07-17T09:26:27.6666883Z Failed distributed compilations 0 2025-07-17T09:26:27.6667106Z 2025-07-17T09:26:27.6667216Z Non-cacheable reasons: 2025-07-17T09:26:27.6667468Z -E 6 2025-07-17T09:26:27.6667688Z 2025-07-17T09:26:27.6667925Z Cache location s3, name: ossci-compiler-cache-circleci-v2, prefix: / 2025-07-17T09:26:27.6668395Z Version (client) 0.10.0 2025-07-17T09:26:27.6668710Z + sccache --stop-server 2025-07-17T09:26:27.6681984Z Stopping sccache server... 2025-07-17T09:26:27.6684879Z Compile requests 2689 2025-07-17T09:26:27.6685426Z Compile requests executed 98 2025-07-17T09:26:27.6685744Z Cache hits 60 2025-07-17T09:26:27.6686058Z Cache hits (C/C++) 60 2025-07-17T09:26:27.6686376Z Cache misses 38 2025-07-17T09:26:27.6686702Z Cache misses (C/C++) 38 2025-07-17T09:26:27.6687375Z Cache hits rate 61.22 % 2025-07-17T09:26:27.6687918Z Cache hits rate (C/C++) 61.22 % 2025-07-17T09:26:27.6688518Z Cache timeouts 0 2025-07-17T09:26:27.6689067Z Cache read errors 0 2025-07-17T09:26:27.6689639Z Forced recaches 0 2025-07-17T09:26:27.6690153Z Cache write errors 0 2025-07-17T09:26:27.6690625Z Cache errors 0 2025-07-17T09:26:27.6691372Z Compilations 38 2025-07-17T09:26:27.6692013Z Compilation failures 0 2025-07-17T09:26:27.6692568Z Non-cacheable compilations 0 2025-07-17T09:26:27.6693145Z Non-cacheable calls 6 2025-07-17T09:26:27.6693556Z Non-compilation calls 2585 2025-07-17T09:26:27.6693892Z Unsupported compiler calls 0 2025-07-17T09:26:27.6694222Z Average cache write 0.052 s 2025-07-17T09:26:27.6694557Z Average compiler 12.119 s 2025-07-17T09:26:27.6694893Z Average cache read hit 0.039 s 2025-07-17T09:26:27.6695220Z Failed distributed compilations 0 2025-07-17T09:26:27.6695456Z 2025-07-17T09:26:27.6695553Z Non-cacheable reasons: 2025-07-17T09:26:27.6695811Z -E 6 2025-07-17T09:26:27.6696018Z 2025-07-17T09:26:27.6696265Z Cache location s3, name: ossci-compiler-cache-circleci-v2, prefix: / 2025-07-17T09:26:27.6696721Z Version (client) 0.10.0 2025-07-17T09:26:27.6697057Z + echo ::endgroup:: 2025-07-17T09:26:27.6697532Z ##[endgroup] 2025-07-17T09:26:27.6697755Z + cleanup_workspace 2025-07-17T09:26:27.6698247Z + echo 'sudo may print the following warning message that can be ignored. The chown command will still run.' 2025-07-17T09:26:27.6699048Z sudo may print the following warning message that can be ignored. The chown command will still run. 2025-07-17T09:26:27.6699777Z + echo ' sudo: setrlimit(RLIMIT_STACK): Operation not permitted' 2025-07-17T09:26:27.6700254Z sudo: setrlimit(RLIMIT_STACK): Operation not permitted 2025-07-17T09:26:27.6700791Z + echo 'For more details refer to https://github.com/sudo-project/sudo/issues/42' 2025-07-17T09:26:27.6701402Z For more details refer to https://github.com/sudo-project/sudo/issues/42 2025-07-17T09:26:27.6701884Z + sudo chown -R 1000 /var/lib/jenkins/workspace 2025-07-17T09:26:30.6171272Z ##[group]Run pytorch/test-infra/.github/actions/upload-benchmark-results@main 2025-07-17T09:26:30.6171809Z with: 2025-07-17T09:26:30.6172049Z benchmark-results-dir: test/test-reports 2025-07-17T09:26:30.6172374Z dry-run: false 2025-07-17T09:26:30.6172613Z schema-version: v3 2025-07-17T09:26:30.6173104Z github-token: *** 2025-07-17T09:26:30.6173323Z env: 2025-07-17T09:26:30.6173538Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:30.6174010Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:30.6174513Z ##[endgroup] 2025-07-17T09:26:30.6201153Z ##[group]Run set -eux 2025-07-17T09:26:30.6201443Z set -eux 2025-07-17T09:26:30.6201816Z python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-07-17T09:26:30.6202257Z  2025-07-17T09:26:30.6202478Z DEVICE_NAME="" 2025-07-17T09:26:30.6202734Z DEVICE_TYPE="" 2025-07-17T09:26:30.6202983Z  2025-07-17T09:26:30.6203258Z if command -v nvidia-smi; then 2025-07-17T09:26:30.6203719Z  # NB: I'm using PyTorch here to get the device name, however, it needs to 2025-07-17T09:26:30.6204312Z  # install the correct version of PyTorch manually for now. Any PyTorch 2025-07-17T09:26:30.6204870Z  # version is fine, I just use 2.7.1 to satify PYPIDEP linter 2025-07-17T09:26:30.6205309Z  python3 -mpip install torch==2.7.1 2025-07-17T09:26:30.6205745Z elif command -v rocminfo; then 2025-07-17T09:26:30.6206184Z  # NB: Installing torch on ROCm runner with pip here causes CI to fail 2025-07-17T09:26:30.6206851Z  # with a memoryview is too large error only on MI300 runners. Is pip 2025-07-17T09:26:30.6207430Z  # version on ROCm runner there too old? As a workaround, let's use the 2025-07-17T09:26:30.6207927Z  # GPU device name coming from rocminfo instead 2025-07-17T09:26:30.6208303Z  DEVICE_NAME=rocm 2025-07-17T09:26:30.6208802Z  DEVICE_TYPE=$(rocminfo | grep "Marketing Name" | tail -n1 | awk -F':' '{print $2}' | xargs) 2025-07-17T09:26:30.6209370Z fi 2025-07-17T09:26:30.6209575Z  2025-07-17T09:26:30.6209853Z echo "DEVICE_NAME=$DEVICE_NAME" >> $GITHUB_ENV 2025-07-17T09:26:30.6210275Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV 2025-07-17T09:26:30.6414162Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:30.6414558Z env: 2025-07-17T09:26:30.6414779Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:30.6415235Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:30.6415751Z ##[endgroup] 2025-07-17T09:26:30.6460995Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-07-17T09:26:31.4353522Z Defaulting to user installation because normal site-packages is not writeable 2025-07-17T09:26:32.5059938Z Collecting boto3==1.35.33 2025-07-17T09:26:32.5229960Z Downloading boto3-1.35.33-py3-none-any.whl (139 kB) 2025-07-17T09:26:32.8327801Z Collecting psutil==7.0.0 2025-07-17T09:26:32.8364770Z Downloading psutil-7.0.0-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (277 kB) 2025-07-17T09:26:32.8635904Z Collecting pynvml==12.0.0 2025-07-17T09:26:32.8674477Z Downloading pynvml-12.0.0-py3-none-any.whl (26 kB) 2025-07-17T09:26:32.9116440Z Collecting s3transfer<0.11.0,>=0.10.0 2025-07-17T09:26:32.9157671Z Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB) 2025-07-17T09:26:34.0469761Z Collecting botocore<1.36.0,>=1.35.33 2025-07-17T09:26:34.0505374Z Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB) 2025-07-17T09:26:34.1961616Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /usr/lib/python3.9/site-packages (from boto3==1.35.33) (0.10.0) 2025-07-17T09:26:34.2381785Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0 2025-07-17T09:26:34.2415662Z Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB) 2025-07-17T09:26:34.2502124Z Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (2.8.1) 2025-07-17T09:26:34.2512164Z Requirement already satisfied: urllib3<1.27,>=1.25.4 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.25.10) 2025-07-17T09:26:34.4454887Z Requirement already satisfied: six>=1.5 in /usr/lib/python3.9/site-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.15.0) 2025-07-17T09:26:34.6110921Z Installing collected packages: botocore, s3transfer, nvidia-ml-py, pynvml, psutil, boto3 2025-07-17T09:26:35.1192850Z Attempting uninstall: nvidia-ml-py 2025-07-17T09:26:35.1193866Z Found existing installation: nvidia-ml-py 11.525.84 2025-07-17T09:26:35.1213987Z Uninstalling nvidia-ml-py-11.525.84: 2025-07-17T09:26:35.1578666Z Successfully uninstalled nvidia-ml-py-11.525.84 2025-07-17T09:26:35.2195943Z Attempting uninstall: psutil 2025-07-17T09:26:35.2196884Z Found existing installation: psutil 5.9.1 2025-07-17T09:26:35.2271904Z Uninstalling psutil-5.9.1: 2025-07-17T09:26:35.2278343Z Successfully uninstalled psutil-5.9.1 2025-07-17T09:26:35.3957087Z Successfully installed boto3-1.35.33 botocore-1.35.99 nvidia-ml-py-12.575.51 psutil-7.0.0 pynvml-12.0.0 s3transfer-0.10.4 2025-07-17T09:26:35.5041558Z + DEVICE_NAME= 2025-07-17T09:26:35.5041975Z + DEVICE_TYPE= 2025-07-17T09:26:35.5042334Z + command -v nvidia-smi 2025-07-17T09:26:35.5042806Z + command -v rocminfo 2025-07-17T09:26:35.5043175Z + echo DEVICE_NAME= 2025-07-17T09:26:35.5043747Z + echo DEVICE_TYPE= 2025-07-17T09:26:35.5074163Z ##[group]Run set -eux 2025-07-17T09:26:35.5074447Z set -eux 2025-07-17T09:26:35.5074665Z  2025-07-17T09:26:35.5074909Z if [[ -z "${GITHUB_TOKEN}" ]]; then 2025-07-17T09:26:35.5075272Z  echo "Missing github-token input" 2025-07-17T09:26:35.5075591Z  exit 1 2025-07-17T09:26:35.5075840Z fi 2025-07-17T09:26:35.5081408Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:35.5081785Z env: 2025-07-17T09:26:35.5082121Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:35.5082597Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:35.5083113Z DEVICE_NAME: 2025-07-17T09:26:35.5083328Z DEVICE_TYPE: 2025-07-17T09:26:35.5083788Z GITHUB_TOKEN: *** 2025-07-17T09:26:35.5084025Z ##[endgroup] 2025-07-17T09:26:35.5112312Z + [[ -z *** ]] 2025-07-17T09:26:35.5171540Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main 2025-07-17T09:26:35.5172007Z with: 2025-07-17T09:26:35.5172473Z github-token: *** 2025-07-17T09:26:35.5172712Z env: 2025-07-17T09:26:35.5172920Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:35.5173392Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:35.5173902Z DEVICE_NAME: 2025-07-17T09:26:35.5174118Z DEVICE_TYPE: 2025-07-17T09:26:35.5174357Z ##[endgroup] 2025-07-17T09:26:35.5198718Z ##[group]Run set -eux 2025-07-17T09:26:35.5199014Z set -eux 2025-07-17T09:26:35.5199257Z  2025-07-17T09:26:35.5199792Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-07-17T09:26:35.5206378Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:35.5206797Z env: 2025-07-17T09:26:35.5207028Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:35.5207492Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:35.5208017Z DEVICE_NAME: 2025-07-17T09:26:35.5208245Z DEVICE_TYPE: 2025-07-17T09:26:35.5208629Z GITHUB_TOKEN: *** 2025-07-17T09:26:35.5208850Z ##[endgroup] 2025-07-17T09:26:35.5233722Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 16337959907 i-00d4fcac0f1d6282f 2025-07-17T09:26:38.5311076Z setting job-id=46154839619 2025-07-17T09:26:38.5311657Z setting job-name=linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T09:26:38.5448709Z ##[group]Run set -eux 2025-07-17T09:26:38.5448996Z set -eux 2025-07-17T09:26:38.5449227Z  2025-07-17T09:26:38.5449615Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \ 2025-07-17T09:26:38.5450153Z  --schema-version "${SCHEMA_VERSION}" \ 2025-07-17T09:26:38.5450511Z  --repo "${REPO}" \ 2025-07-17T09:26:38.5450822Z  --head-branch "${HEAD_BRANCH}" \ 2025-07-17T09:26:38.5451161Z  --head-sha "${HEAD_SHA}" \ 2025-07-17T09:26:38.5451504Z  --workflow-id "${WORKFLOW_RUN_ID}" \ 2025-07-17T09:26:38.5451872Z  --run-attempt "${RUN_ATTEMPT}" \ 2025-07-17T09:26:38.5452194Z  --job-id "${JOB_ID}" \ 2025-07-17T09:26:38.5452506Z  --job-name "${JOB_NAME}" 2025-07-17T09:26:38.5458334Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:38.5458724Z env: 2025-07-17T09:26:38.5458967Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:38.5459436Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:38.5459992Z DEVICE_NAME: 2025-07-17T09:26:38.5460219Z DEVICE_TYPE: 2025-07-17T09:26:38.5460448Z SCHEMA_VERSION: v3 2025-07-17T09:26:38.5460689Z REPO: pytorch/pytorch 2025-07-17T09:26:38.5460955Z HEAD_BRANCH: refs/heads/main 2025-07-17T09:26:38.5461277Z HEAD_SHA: a38f433be2e94a64b095a44ba39879d02d0c2316 2025-07-17T09:26:38.5461713Z WORKFLOW_RUN_ID: 16337959907 2025-07-17T09:26:38.5461988Z RUN_ATTEMPT: 1 2025-07-17T09:26:38.5462218Z JOB_ID: 46154839619 2025-07-17T09:26:38.5462616Z JOB_NAME: linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T09:26:38.5463085Z ##[endgroup] 2025-07-17T09:26:38.5493674Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_metadata.py --schema-version v3 --repo pytorch/pytorch --head-branch refs/heads/main --head-sha a38f433be2e94a64b095a44ba39879d02d0c2316 --workflow-id 16337959907 --run-attempt 1 --job-id 46154839619 --job-name 'linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge)' 2025-07-17T09:26:38.5824229Z ##[group]Run set -eux 2025-07-17T09:26:38.5824509Z set -eux 2025-07-17T09:26:38.5824739Z  2025-07-17T09:26:38.5825136Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py" 2025-07-17T09:26:38.5830871Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:38.5831257Z env: 2025-07-17T09:26:38.5831481Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:38.5831943Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:38.5832453Z DEVICE_NAME: 2025-07-17T09:26:38.5832686Z DEVICE_TYPE: 2025-07-17T09:26:38.5832918Z ##[endgroup] 2025-07-17T09:26:38.5858217Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py 2025-07-17T09:26:38.6268199Z INFO:root:Fail to import torch to get the device name 2025-07-17T09:26:38.6378593Z ##[group]Run set -eux 2025-07-17T09:26:38.6378876Z set -eux 2025-07-17T09:26:38.6379110Z  2025-07-17T09:26:38.6379352Z # TODO (huydhn): Implement this part 2025-07-17T09:26:38.6379797Z echo "dependencies={}" >> "${GITHUB_OUTPUT}" 2025-07-17T09:26:38.6385436Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:38.6385823Z env: 2025-07-17T09:26:38.6386061Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:38.6386517Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:38.6387028Z DEVICE_NAME: 2025-07-17T09:26:38.6387257Z DEVICE_TYPE: 2025-07-17T09:26:38.6387484Z ##[endgroup] 2025-07-17T09:26:38.6410831Z + echo 'dependencies={}' 2025-07-17T09:26:38.6450198Z ##[group]Run set -eux 2025-07-17T09:26:38.6450709Z set -eux 2025-07-17T09:26:38.6451110Z  2025-07-17T09:26:38.6451572Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then 2025-07-17T09:26:38.6452385Z  echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping" 2025-07-17T09:26:38.6453261Z  # We don't want the job to fail if the directory doesn't exist 2025-07-17T09:26:38.6453993Z  exit 0 2025-07-17T09:26:38.6454416Z fi 2025-07-17T09:26:38.6454777Z  2025-07-17T09:26:38.6455207Z if [[ "${DRY_RUN}" == "true" ]]; then 2025-07-17T09:26:38.6456098Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-07-17T09:26:38.6457112Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-07-17T09:26:38.6457904Z  --metadata "${BENCHMARK_METADATA}" \ 2025-07-17T09:26:38.6458553Z  --runners "${RUNNER_INFO}" \ 2025-07-17T09:26:38.6459156Z  --dependencies "${DEPENDENCIES}" \ 2025-07-17T09:26:38.6459783Z  --dry-run 2025-07-17T09:26:38.6460241Z else 2025-07-17T09:26:38.6461006Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-07-17T09:26:38.6462065Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-07-17T09:26:38.6462869Z  --metadata "${BENCHMARK_METADATA}" \ 2025-07-17T09:26:38.6463513Z  --runners "${RUNNER_INFO}" \ 2025-07-17T09:26:38.6464145Z  --dependencies "${DEPENDENCIES}" 2025-07-17T09:26:38.6464827Z fi 2025-07-17T09:26:38.6473313Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:38.6473983Z env: 2025-07-17T09:26:38.6474246Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:38.6474726Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:38.6475260Z DEVICE_NAME: 2025-07-17T09:26:38.6475479Z DEVICE_TYPE: 2025-07-17T09:26:38.6475738Z BENCHMARK_RESULTS_DIR: test/test-reports 2025-07-17T09:26:38.6476151Z DRY_RUN: false 2025-07-17T09:26:38.6477493Z BENCHMARK_METADATA: {"timestamp": 1752744398, "schema_version": "v3", "name": "linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "a38f433be2e94a64b095a44ba39879d02d0c2316", "workflow_id": 16337959907, "run_attempt": 1, "job_id": 46154839619} 2025-07-17T09:26:38.6479246Z RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 8, "avail_mem_in_gb": 15, "extra_info": {"hostname": "ip-10-0-42-148.ec2.internal"}, "name": "", "type": ""}] 2025-07-17T09:26:38.6479889Z DEPENDENCIES: {} 2025-07-17T09:26:38.6480129Z ##[endgroup] 2025-07-17T09:26:38.6503283Z + [[ ! -d test/test-reports ]] 2025-07-17T09:26:38.6503593Z + [[ false == \t\r\u\e ]] 2025-07-17T09:26:38.6506434Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1752744398, "schema_version": "v3", "name": "linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "a38f433be2e94a64b095a44ba39879d02d0c2316", "workflow_id": 16337959907, "run_attempt": 1, "job_id": 46154839619}' --runners '[{"cpu_info": "x86_64", "cpu_count": 8, "avail_mem_in_gb": 15, "extra_info": {"hostname": "ip-10-0-42-148.ec2.internal"}, "name": "", "type": ""}]' --dependencies '{}' 2025-07-17T09:26:38.8671037Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'functorch/test_eager_transforms'}, {'test_file': 'functorch/test_ops'}, {'test_file': 'test_transformers'}, {'test_file': 'dynamo/cpython/3_13/test_generators'}, {'test_file': 'dynamo/cpython/3_13/test_contextlib'}, {'test_file': 'dynamo/cpython/3_13/test_raise'}, {'test_file': 'dynamo/cpython/3_13/test_exceptions'}, {'test_file': 'dynamo/cpython/3_13/test_sys'}, {'test_file': 'test_jit_fuser_te'}, {'test_file': 'test_ci_sanity_check_fail'}, {'test_file': 'higher_order_ops/test_invoke_subgraph'}, {'test_file': 'test_numba_integration'}, {'test_file': 'dynamo/test_logging'}, {'test_file': 'dynamo/test_activation_checkpointing'}, {'test_file': 'dynamo/test_reorder_logs'}, {'test_file': 'dynamo/test_exc'}, {'test_file': 'test_autograd'}, {'test_file': 'dynamo/test_precompile_context'}, {'test_file': 'test_testing'}, {'test_file': 'test_overrides'}, {'test_file': 'test_reductions'}, {'test_file': 'test_quantization'}, {'test_file': 'doctests'}, {'test_file': 'dynamo/test_inline_and_install'}, {'test_file': 'dynamo/test_install_free_tensors'}, {'test_file': 'test_linalg'}, {'test_file': 'test_namedtuple_return_api'}, {'test_file': 'dynamo/cpython/3_13/test_list'}, {'test_file': 'functorch/test_vmap'}, {'test_file': 'test_nestedtensor'}, {'test_file': 'test_nn'}, {'test_file': 'test_binary_ufuncs'}, {'test_file': 'test_foreach'}, {'test_file': 'dynamo/cpython/3_13/test_generator_stop'}, {'test_file': 'dynamo/cpython/3_13/test_exception_variations'}, {'test_file': 'dynamo/cpython/3_13/test_int_literal'}, {'test_file': 'dynamo/cpython/3_13/test_with'}, {'test_file': 'dynamo/cpython/3_13/test_numeric_tower'}, {'test_file': 'dynamo/cpython/3_13/test_ordered_dict'}, {'test_file': 'dynamo/cpython/3_13/test_baseexception'}, {'test_file': 'dynamo/cpython/3_13/test_int'}, {'test_file': 'dynamo/cpython/3_13/test_itertools'}, {'test_file': 'dynamo/cpython/3_13/test_userlist'}, {'test_file': 'dynamo/cpython/3_13/test_cmath'}, {'test_file': 'dynamo/cpython/3_13/test_math'}, {'test_file': 'dynamo/cpython/3_13/test_operator'}, {'test_file': 'dynamo/cpython/3_13/test_userdict'}, {'test_file': 'dynamo/cpython/3_13/test_set'}, {'test_file': 'dynamo/cpython/3_13/test_iter'}, {'test_file': 'dynamo/cpython/3_13/test_bool'}, {'test_file': 'dynamo/cpython/3_13/test_sort'}, {'test_file': 'dynamo/cpython/3_13/test_float'}, {'test_file': 'dynamo/cpython/3_13/test_dict'}, {'test_file': 'dynamo/cpython/3_13/test_complex'}, {'test_file': 'dynamo/cpython/3_13/test_tuple'}, {'test_file': 'test_package'}, {'test_file': 'test_decomp'}, {'test_file': 'test_autoload'}, {'test_file': 'test_utils_config_module'}, {'test_file': 'test_mkl_verbose'}, {'test_file': 'test_spectral_ops'}, {'test_file': 'distributions/test_distributions'}, {'test_file': 'dynamo/test_deque_reconstruct'}, {'test_file': 'test_license'}, {'test_file': 'test_mkldnn_verbose'}, {'test_file': 'dynamo/test_recompiles'}, {'test_file': 'dynamo/cpython/3_13/test_unittest/test_assertions'}, {'test_file': 'test_comparison_utils'}, {'test_file': 'test_ops'}, {'test_file': 'dynamo/test_base_output'}, {'test_file': 'typing/test_python_operators'}, {'test_file': 'torch_np/test_nep50_examples'}, {'test_file': 'test_extension_utils'}, {'test_file': 'test_cpp_api_parity'}, {'test_file': 'test_ops_jit'}, {'test_file': 'dynamo/test_skip_guard_eval_unsafe'}, {'test_file': 'functorch/test_ac_logging'}, {'test_file': 'test_custom_ops'}, {'test_file': 'test_ao_sparsity'}, {'test_file': 'torch_np/test_binary_ufuncs'}, {'test_file': 'test_hop_infra'}, {'test_file': 'torch_np/test_unary_ufuncs'}, {'test_file': 'dynamo/test_nops'}, {'test_file': 'backends/xeon/test_launch'}, {'test_file': 'torch_np/numpy_tests/linalg/test_linalg'}, {'test_file': 'test_cpp_extensions_open_device_registration'}, {'test_file': 'dynamo/test_skip_non_tensor'}, {'test_file': 'dynamo/test_interop'}, {'test_file': 'test_file_check'}, {'test_file': 'dynamo/test_buffers_override'}, {'test_file': 'test_appending_byte_serializer'}, {'test_file': 'dynamo/test_resume'}, {'test_file': 'torch_np/test_dtype'}, {'test_file': 'test_proxy_tensor'}, {'test_file': 'test_transformers_privateuse1'}, {'test_file': 'dynamo/test_modules'}, {'test_file': 'xpu/test_fusion'}, {'test_file': 'test_openreg'}, {'test_file': 'dynamo/test_sdpa'}, {'test_file': 'dynamo/test_fx_passes_pre_grad'}, {'test_file': 'dynamo/test_global'}, {'test_file': 'dynamo/test_utils'}, {'test_file': 'dynamo/test_frame_init'}, {'test_file': 'dynamo/test_graph_region_tracker'}, {'test_file': 'profiler/test_kineto'}, {'test_file': 'test_fx_experimental'}, {'test_file': 'test_flop_counter'}, {'test_file': 'test_typing'}, {'test_file': 'test_meta'}, {'test_file': 'test_functionalization'}, {'test_file': 'test_utils_filelock'}, {'test_file': 'dynamo/test_pre_dispatch'}, {'test_file': 'dynamo/test_metrics_context'}, {'test_file': 'test_fx'}, {'test_file': 'dynamo/test_subgraphs'}, {'test_file': 'cpp_extensions/python_agnostic_extension/test/test_python_agnostic'}, {'test_file': 'dynamo/test_reconstruct'}, {'test_file': 'test_show_pickle'}, {'test_file': 'dynamo/test_dicts'}, {'test_file': 'dynamo/test_dynamic_shapes'}, {'test_file': 'test_pytree'}, 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'dynamo/test_higher_order_ops'}, {'test_file': 'test_cuda_sanitizer'}, {'test_file': 'test_model_exports_to_core_aten'}, {'test_file': 'test_mkldnn'}, {'test_file': 'torch_np/numpy_tests/lib/test_function_base'}, {'test_file': 'lazy/test_functionalization'}, {'test_file': 'test_jit'}, {'test_file': 'dynamo/test_aot_autograd_cache'}, {'test_file': 'dynamo/test_einops'}, {'test_file': 'dynamo/test_compiler_bisector'}, {'test_file': 'test_python_dispatch'}, {'test_file': 'test_modules'}, {'test_file': 'nn/test_lazy_modules'}, {'test_file': 'optim/test_lrscheduler'}, {'test_file': 'dynamo/test_trace_rules'}, {'test_file': 'torch_np/numpy_tests/lib/test_type_check'}, {'test_file': 'test_itt'}, {'test_file': 'dynamo/test_aot_autograd'}, {'test_file': 'test_autograd_fallback'}, {'test_file': 'test_bundled_inputs'}, {'test_file': 'dynamo/test_error_messages'}, {'test_file': 'test_cuda'}, {'test_file': 'nn/test_pruning'}, {'test_file': 'test_fx_reinplace_pass'}, {'test_file': 'test_cuda_nvml_based_avail'}, {'test_file': 'torch_np/test_function_base'}, {'test_file': 'test_tensor_creation_ops'}, {'test_file': 'test_accelerator'}, {'test_file': 'dynamo/test_callback'}, {'test_file': 'test_functionalization_of_rng_ops'}, {'test_file': 'test_public_bindings'}, {'test_file': 'torch_np/numpy_tests/core/test_indexing'}, {'test_file': 'dynamo/test_unspec'}, {'test_file': 'test_schema_check'}, {'test_file': 'dynamo/test_exceptions'}, {'test_file': 'test_cuda_trace'}, {'test_file': 'torch_np/numpy_tests/lib/test_histograms'}, {'test_file': 'benchmark_utils/test_benchmark_utils'}, {'test_file': 'test_masked'}, {'test_file': 'test_type_info'}, {'test_file': 'dynamo/test_torchrec'}, {'test_file': 'test_jit_llga_fuser'}, {'test_file': 'test_subclass'}, {'test_file': 'dynamo/test_hooks'}, {'test_file': 'dynamo/test_input_attr_tracking'}, {'test_file': 'nn/test_parametrization'}, {'test_file': 'test_matmul_cuda'}, {'test_file': 'dynamo/test_minifier'}, {'test_file': 'dynamo/test_bytecode_utils'}, {'test_file': 'test_dlpack'}, {'test_file': 'optim/test_swa_utils'}, {'test_file': 'test_sympy_utils'}, {'test_file': 'test_sparse_semi_structured'}, {'test_file': 'functorch/test_control_flow'}, {'test_file': 'lazy/test_ts_opinfo'}, {'test_file': 'test_maskedtensor'}, {'test_file': 'torch_np/numpy_tests/core/test_scalarmath'}, {'test_file': 'torch_np/numpy_tests/core/test_getlimits'}, {'test_file': 'dynamo/test_recompile_ux'}, {'test_file': 'dynamo/test_ctx_manager'}, {'test_file': 'test_autocast'}, {'test_file': 'torch_np/numpy_tests/core/test_dtype'}, {'test_file': 'functorch/test_vmap_registrations'}, {'test_file': 'dynamo/test_fake_distributed'}, {'test_file': 'dynamo/test_comptime'}, {'test_file': 'torch_np/numpy_tests/core/test_shape_base'}, {'test_file': 'nn/test_packed_sequence'}, {'test_file': 'test_futures'}, {'test_file': 'test_cpp_extensions_jit'}, {'test_file': 'optim/test_optim'}, {'test_file': 'torch_np/numpy_tests/fft/test_pocketfft'}, {'test_file': 'test_serialization'}, {'test_file': 'dynamo/test_generator'}, {'test_file': 'test_functional_optim'}, {'test_file': 'test_cuda_primary_ctx'}, {'test_file': 'nn/test_embedding'}, {'test_file': 'nn/test_dropout'}, {'test_file': 'test_dynamic_shapes'}, {'test_file': 'torch_np/numpy_tests/fft/test_helper'}, {'test_file': 'torch_np/test_ndarray_methods'}, {'test_file': 'test_torch'}, {'test_file': 'torch_np/numpy_tests/lib/test_twodim_base'}, {'test_file': 'test_vulkan'}, {'test_file': 'torch_np/numpy_tests/lib/test_shape_base_'}, {'test_file': 'test_mkldnn_fusion'}, {'test_file': 'dynamo/test_guard_manager'}, {'test_file': 'test_shape_ops'}, {'test_file': 'torch_np/test_scalars_0D_arrays'}, {'test_file': 'dynamo/test_subclasses'}, {'test_file': 'nn/test_load_state_dict'}, {'test_file': 'test_indexing'}, {'test_file': 'torch_np/numpy_tests/lib/test_index_tricks'}, {'test_file': 'torch_np/numpy_tests/core/test_dlpack'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraypad'}, {'test_file': 'lazy/test_debug_util'}, {'test_file': 'test_native_mha'}, {'test_file': 'test_sort_and_select'}, {'test_file': 'test_xnnpack_integration'}, {'test_file': 'test_sparse_csr'}, {'test_file': 'lazy/test_generator'}, {'test_file': 'test_functional_autograd_benchmark'}, {'test_file': 'torch_np/numpy_tests/core/test_scalar_methods'}, {'test_file': 'test_multiprocessing_spawn'}, {'test_file': 'nn/test_module_hooks'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraysetops'}, {'test_file': 'torch_np/numpy_tests/core/test_numerictypes'}, {'test_file': 'test_view_ops'}, {'test_file': 'test_scatter_gather_ops'}, {'test_file': 'nn/test_pooling'}, {'test_file': 'profiler/test_memory_profiler'}, {'test_file': 'test_unary_ufuncs'}, {'test_file': 'nn/test_init'}, {'test_file': 'test_function_schema'}, {'test_file': 'test_cuda_multigpu'}, {'test_file': 'test_mobile_optimizer'}, {'test_file': 'torch_np/numpy_tests/core/test_scalar_ctors'}, {'test_file': 'test_sparse'}, {'test_file': 'torch_np/test_reductions'}, {'test_file': 'profiler/test_profiler_tree'}, {'test_file': 'nn/test_convolution'}, {'test_file': 'test_type_promotion'}, {'test_file': 'dynamo/test_python_autograd'}, {'test_file': 'test_jit_autocast'}, {'test_file': 'profiler/test_record_function'}, {'test_file': 'test_prims'}, {'test_file': 'lazy/test_reuse_ir'}, {'test_file': 'profiler/test_execution_trace'}, {'test_file': 'profiler/test_torch_tidy'}, {'test_file': 'test_autoload_disable'}, {'test_file': 'test_autoload_enable'}, {'test_file': 'test_cpp_extensions_aot_ninja'}, {'test_file': 'test_cpp_extensions_aot_no_ninja'}, {'test_file': 'test_rename_privateuse1_to_existing_device'}], 'excluded': []} from test/test-reports/td_exclusions-e0856826b8297dd916ef.json is not a benchmark record, skipping 2025-07-17T09:26:38.8722623Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-07-17T09:26:38.8875097Z ##[group]Run cat test/**/*_toprint.log || true 2025-07-17T09:26:38.8875534Z cat test/**/*_toprint.log || true 2025-07-17T09:26:38.8881118Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:38.8881505Z env: 2025-07-17T09:26:38.8881725Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:38.8882181Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:38.8882691Z DEVICE_NAME: 2025-07-17T09:26:38.8882918Z DEVICE_TYPE: 2025-07-17T09:26:38.8883143Z ##[endgroup] 2025-07-17T09:26:38.8970144Z cat: 'test/**/*_toprint.log': No such file or directory 2025-07-17T09:26:38.9006021Z ##[group]Run kill "$MONITOR_SCRIPT_PID" 2025-07-17T09:26:38.9006401Z kill "$MONITOR_SCRIPT_PID" 2025-07-17T09:26:38.9011651Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:38.9012037Z env: 2025-07-17T09:26:38.9012256Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:38.9012718Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:38.9013237Z DEVICE_NAME: 2025-07-17T09:26:38.9013465Z DEVICE_TYPE: 2025-07-17T09:26:38.9013702Z MONITOR_SCRIPT_PID: 42688 2025-07-17T09:26:38.9013956Z ##[endgroup] 2025-07-17T09:26:38.9162261Z Prepare all required actions 2025-07-17T09:26:38.9162789Z Getting action download info 2025-07-17T09:26:39.0796501Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-07-17T09:26:39.3021417Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02) 2025-07-17T09:26:39.7263631Z ##[group]Run ./.github/actions/upload-test-artifacts 2025-07-17T09:26:39.7263998Z with: 2025-07-17T09:26:39.7264326Z file-suffix: test-dynamo_wrapped-2-3-linux.2xlarge_46154839619 2025-07-17T09:26:39.7264748Z s3-bucket: gha-artifacts 2025-07-17T09:26:39.7264996Z env: 2025-07-17T09:26:39.7265209Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:39.7265677Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:39.7266184Z DEVICE_NAME: 2025-07-17T09:26:39.7266409Z DEVICE_TYPE: 2025-07-17T09:26:39.7266636Z ##[endgroup] 2025-07-17T09:26:39.7293973Z ##[group]Run # Remove any previous test jsons if they exist 2025-07-17T09:26:39.7294445Z # Remove any previous test jsons if they exist 2025-07-17T09:26:39.7294817Z rm -f test-jsons-*.zip 2025-07-17T09:26:39.7295250Z zip -r "test-jsons-${FILE_SUFFIX}.zip" test/test-reports -i '*.json' 2025-07-17T09:26:39.7301105Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:39.7301496Z env: 2025-07-17T09:26:39.7301731Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:39.7302195Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:39.7302690Z DEVICE_NAME: 2025-07-17T09:26:39.7302919Z DEVICE_TYPE: 2025-07-17T09:26:39.7303250Z FILE_SUFFIX: test-dynamo_wrapped-2-3-linux.2xlarge_46154839619 2025-07-17T09:26:39.7303647Z ##[endgroup] 2025-07-17T09:26:39.7487568Z adding: test/test-reports/td_exclusions-e0856826b8297dd916ef.json (deflated 82%) 2025-07-17T09:26:39.7515653Z ##[group]Run # Remove any previous test reports if they exist 2025-07-17T09:26:39.7516140Z # Remove any previous test reports if they exist 2025-07-17T09:26:39.7516534Z rm -f test-reports-*.zip 2025-07-17T09:26:39.7517023Z zip -r "test-reports-${FILE_SUFFIX}.zip" test/test-reports -i '*.xml' -i '*.csv' 2025-07-17T09:26:39.7522441Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:39.7522925Z env: 2025-07-17T09:26:39.7523148Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:39.7523606Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:39.7524111Z DEVICE_NAME: 2025-07-17T09:26:39.7524338Z DEVICE_TYPE: 2025-07-17T09:26:39.7524659Z FILE_SUFFIX: test-dynamo_wrapped-2-3-linux.2xlarge_46154839619 2025-07-17T09:26:39.7525057Z ##[endgroup] 2025-07-17T09:26:39.7678438Z adding: test/test-reports/python-pytest/test_reductions/test_reductions-cc0c18058cb67eca.xml (deflated 97%) 2025-07-17T09:26:39.7695838Z adding: test/test-reports/python-pytest/test_reductions/test_reductions-416b17b8669aa65e.xml (deflated 97%) 2025-07-17T09:26:39.7714738Z adding: test/test-reports/python-pytest/test_reductions/test_reductions-fa312581c0cee086.xml (deflated 97%) 2025-07-17T09:26:39.7716091Z adding: test/test-reports/python-pytest/test_namedtuple_return_api/test_namedtuple_return_api-c48f146853e707df.xml (deflated 72%) 2025-07-17T09:26:39.7734295Z adding: test/test-reports/python-pytest/test_nn/test_nn-db232cc9394a2516.xml (deflated 94%) 2025-07-17T09:26:39.7751964Z adding: test/test-reports/python-pytest/test_nn/test_nn-0064ec828301b1aa.xml (deflated 94%) 2025-07-17T09:26:39.7760063Z adding: test/test-reports/python-pytest/test_spectral_ops/test_spectral_ops-bca9dc9c4b1856e9.xml (deflated 94%) 2025-07-17T09:26:39.7762406Z adding: test/test-reports/python-pytest/distributions.test_distributions/distributions.test_distributions-5bdda5acdeb813bb.xml (deflated 92%) 2025-07-17T09:26:39.7764813Z adding: test/test-reports/python-pytest/distributions.test_distributions/distributions.test_distributions-f36b1798e4c49e08.xml (deflated 93%) 2025-07-17T09:26:39.7766604Z adding: test/test-reports/python-pytest/test_cpp_extensions_open_device_registration/test_cpp_extensions_open_device_registration-2a830f9404d30275.xml (deflated 79%) 2025-07-17T09:26:39.7767978Z adding: test/test-reports/python-pytest/test_transformers_privateuse1/test_transformers_privateuse1-7a551533f5e832fb.xml (deflated 73%) 2025-07-17T09:26:39.7769362Z adding: test/test-reports/python-pytest/test_openreg/test_openreg-a7bef005db8ebaaa.xml (deflated 92%) 2025-07-17T09:26:39.7804856Z adding: test/test-reports/python-pytest/test_fx/test_fx-a575b094b1d41e62.xml (deflated 97%) 2025-07-17T09:26:39.7805985Z adding: 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test/test-reports/dynamo.test_aot_autograd_1.1_2578644f113bdf55_.log (deflated 35%) 2025-07-17T09:26:40.2541136Z adding: test/test-reports/dynamo.test_callback_1.1_9ef9cd99208b609a_.log (deflated 35%) 2025-07-17T09:26:40.2541874Z adding: test/test-reports/dynamo.test_torchrec_1.1_43457df9ae70b170_.log (deflated 36%) 2025-07-17T09:26:40.2542567Z adding: test/test-reports/optim.test_swa_utils_1.1_1817c9643f9fe111_.log (deflated 36%) 2025-07-17T09:26:40.2543291Z adding: test/test-reports/test_sparse_semi_structured_1.1_de124f3d1f3b879e_.log (deflated 85%) 2025-07-17T09:26:40.2551103Z adding: test/test-reports/torch_np.numpy_tests.core.test_scalarmath_1.1_d5080da43242bd69_.log (deflated 92%) 2025-07-17T09:26:40.2551998Z adding: test/test-reports/torch_np.numpy_tests.core.test_getlimits_1.1_bf6e3d6a7063d13f_.log (deflated 75%) 2025-07-17T09:26:40.2555670Z adding: test/test-reports/torch_np.numpy_tests.core.test_dtype_1.1_5c0a8fc63ed46cf0_.log (deflated 91%) 2025-07-17T09:26:40.2596065Z adding: test/test-reports/functorch.test_vmap_registrations_1.1_ceed8e5f10f26c28_.log (deflated 95%) 2025-07-17T09:26:40.2596841Z adding: test/test-reports/dynamo.test_comptime_1.1_a8567e036e97be4a_.log (deflated 35%) 2025-07-17T09:26:40.2601470Z adding: test/test-reports/torch_np.numpy_tests.core.test_shape_base_1.1_f9cd4eb70bf8ec82_.log (deflated 90%) 2025-07-17T09:26:40.2603319Z adding: test/test-reports/nn.test_packed_sequence_1.1_b3cf9aa67c2f5cea_.log (deflated 79%) 2025-07-17T09:26:40.2606200Z adding: test/test-reports/torch_np.numpy_tests.fft.test_pocketfft_1.1_dbd98aa70c962419_.log (deflated 87%) 2025-07-17T09:26:40.2615147Z adding: test/test-reports/test_dynamic_shapes_1.1_5727f4b6436df7a7_.log (deflated 94%) 2025-07-17T09:26:40.2652525Z adding: test/test-reports/functorch.test_control_flow_1.1_3048c118730a9e48_.log (deflated 95%) 2025-07-17T09:26:40.2653809Z adding: test/test-reports/torch_np.numpy_tests.fft.test_helper_1.1_c9973a722ce30097_.log (deflated 73%) 2025-07-17T09:26:40.2655102Z adding: test/test-reports/torch_np.numpy_tests.lib.test_twodim_base_1.1_d78db92eb5cb5b9c_.log (deflated 81%) 2025-07-17T09:26:40.2655990Z adding: test/test-reports/dynamo.test_guard_manager_1.1_0035462bb523b483_.log (deflated 35%) 2025-07-17T09:26:40.2659225Z adding: test/test-reports/torch_np.numpy_tests.lib.test_shape_base__1.1_1db3c91c541588ef_.log (deflated 88%) 2025-07-17T09:26:40.2660514Z adding: test/test-reports/torch_np.test_scalars_0D_arrays_1.1_32fde00137e15e4a_.log (deflated 80%) 2025-07-17T09:26:40.2662238Z adding: test/test-reports/nn.test_load_state_dict_1.1_6de22f48507285cb_.log (deflated 79%) 2025-07-17T09:26:40.2670348Z adding: test/test-reports/torch_np.test_ndarray_methods_1.1_8001bc037f13b305_.log (deflated 93%) 2025-07-17T09:26:40.2671980Z adding: test/test-reports/torch_np.numpy_tests.lib.test_index_tricks_1.1_59cf7bb8fc2c54e3_.log (deflated 84%) 2025-07-17T09:26:40.2672856Z adding: test/test-reports/torch_np.numpy_tests.lib.test_arraypad_1.1_f29745124e4010b0_.log (deflated 71%) 2025-07-17T09:26:40.2677501Z adding: test/test-reports/torch_np.numpy_tests.core.test_dlpack_1.1_cca0b3af4eff666a_.log (deflated 95%) 2025-07-17T09:26:40.2678278Z adding: test/test-reports/lazy.test_debug_util_1.1_3f10f9c9407da1d2_.log (deflated 50%) 2025-07-17T09:26:40.2679328Z adding: test/test-reports/test_xnnpack_integration_1.1_0a0ae91ec3556660_.log (deflated 80%) 2025-07-17T09:26:40.2680220Z adding: test/test-reports/test_function_schema_1.1_11635b8e8748fdaa_.log (deflated 74%) 2025-07-17T09:26:40.2682358Z adding: test/test-reports/torch_np.numpy_tests.core.test_scalar_ctors_1.1_3031a9cc17955d37_.log (deflated 88%) 2025-07-17T09:26:40.2689389Z adding: test/test-reports/profiler.test_profiler_tree_1.1_dae692086fcb3b6e_.log (deflated 96%) 2025-07-17T09:26:40.2710488Z adding: test/test-reports/torch_np.test_reductions_1.1_0b3902b0302681aa_.log (deflated 95%) 2025-07-17T09:26:40.2711250Z adding: test/test-reports/dynamo.test_python_autograd_1.1_f43aedeba2e81208_.log (deflated 35%) 2025-07-17T09:26:40.2724910Z adding: test/test-reports/test_type_promotion_1.1_cd55063b07292fe3_.log (deflated 92%) 2025-07-17T09:26:40.2757923Z ##[group]Run # Remove any previous debugging artifacts if they exist 2025-07-17T09:26:40.2758550Z # Remove any previous debugging artifacts if they exist 2025-07-17T09:26:40.2758968Z rm -f debug-*.zip 2025-07-17T09:26:40.2759256Z if [ -d 'test/debug' ]; then 2025-07-17T09:26:40.2759604Z  zip -r "debug-${FILE_SUFFIX}.zip" test/debug 2025-07-17T09:26:40.2759947Z fi 2025-07-17T09:26:40.2765605Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:40.2765984Z env: 2025-07-17T09:26:40.2766213Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:40.2766682Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:40.2767198Z DEVICE_NAME: 2025-07-17T09:26:40.2767414Z DEVICE_TYPE: 2025-07-17T09:26:40.2767748Z FILE_SUFFIX: test-dynamo_wrapped-2-3-linux.2xlarge_46154839619 2025-07-17T09:26:40.2768146Z ##[endgroup] 2025-07-17T09:26:40.2853556Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-07-17T09:26:40.2853904Z with: 2025-07-17T09:26:40.2854126Z s3-bucket: gha-artifacts 2025-07-17T09:26:40.2854458Z s3-prefix: pytorch/pytorch/16337959907/1/artifact 2025-07-17T09:26:40.2854822Z retention-days: 14 2025-07-17T09:26:40.2855072Z if-no-files-found: warn 2025-07-17T09:26:40.2855353Z path: test-jsons-*.zip 2025-07-17T09:26:40.2855618Z name: artifact 2025-07-17T09:26:40.2855841Z region: us-east-1 2025-07-17T09:26:40.2856073Z env: 2025-07-17T09:26:40.2856327Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:40.2856796Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:40.2857297Z DEVICE_NAME: 2025-07-17T09:26:40.2857524Z DEVICE_TYPE: 2025-07-17T09:26:40.2857862Z ##[endgroup] 2025-07-17T09:26:40.8361341Z NOTE: s3-prefix specified, ignoring name parameter 2025-07-17T09:26:40.8362124Z With the provided path, there will be 1 file uploaded 2025-07-17T09:26:40.8362730Z Uploading to s3 prefix: pytorch/pytorch/16337959907/1/artifact 2025-07-17T09:26:40.9862106Z Starting upload of test-jsons-test-dynamo_wrapped-2-3-linux.2xlarge_46154839619.zip 2025-07-17T09:26:41.1156339Z Finished upload of test-jsons-test-dynamo_wrapped-2-3-linux.2xlarge_46154839619.zip 2025-07-17T09:26:41.1369719Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-07-17T09:26:41.1370256Z with: 2025-07-17T09:26:41.1370475Z s3-bucket: gha-artifacts 2025-07-17T09:26:41.1370805Z s3-prefix: pytorch/pytorch/16337959907/1/artifact 2025-07-17T09:26:41.1371163Z retention-days: 14 2025-07-17T09:26:41.1371437Z if-no-files-found: error 2025-07-17T09:26:41.1371706Z path: test-reports-*.zip 2025-07-17T09:26:41.1371975Z name: artifact 2025-07-17T09:26:41.1372207Z region: us-east-1 2025-07-17T09:26:41.1372434Z env: 2025-07-17T09:26:41.1372648Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:41.1373122Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:41.1373621Z DEVICE_NAME: 2025-07-17T09:26:41.1373846Z DEVICE_TYPE: 2025-07-17T09:26:41.1374069Z ##[endgroup] 2025-07-17T09:26:41.4651020Z NOTE: s3-prefix specified, ignoring name parameter 2025-07-17T09:26:41.4651510Z With the provided path, there will be 1 file uploaded 2025-07-17T09:26:41.4651958Z Uploading to s3 prefix: pytorch/pytorch/16337959907/1/artifact 2025-07-17T09:26:41.4698442Z Starting upload of test-reports-test-dynamo_wrapped-2-3-linux.2xlarge_46154839619.zip 2025-07-17T09:26:41.6341153Z Finished upload of test-reports-test-dynamo_wrapped-2-3-linux.2xlarge_46154839619.zip 2025-07-17T09:26:41.6581773Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-07-17T09:26:41.6582119Z with: 2025-07-17T09:26:41.6582335Z s3-bucket: gha-artifacts 2025-07-17T09:26:41.6582678Z s3-prefix: pytorch/pytorch/16337959907/1/artifact 2025-07-17T09:26:41.6583040Z retention-days: 14 2025-07-17T09:26:41.6583298Z if-no-files-found: ignore 2025-07-17T09:26:41.6583562Z path: logs-*.zip 2025-07-17T09:26:41.6583800Z name: artifact 2025-07-17T09:26:41.6584033Z region: us-east-1 2025-07-17T09:26:41.6584255Z env: 2025-07-17T09:26:41.6584586Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:41.6585068Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:41.6585611Z DEVICE_NAME: 2025-07-17T09:26:41.6585857Z DEVICE_TYPE: 2025-07-17T09:26:41.6586081Z ##[endgroup] 2025-07-17T09:26:41.9850091Z NOTE: s3-prefix specified, ignoring name parameter 2025-07-17T09:26:41.9850574Z With the provided path, there will be 1 file uploaded 2025-07-17T09:26:41.9851024Z Uploading to s3 prefix: pytorch/pytorch/16337959907/1/artifact 2025-07-17T09:26:41.9897024Z Starting upload of logs-test-dynamo_wrapped-2-3-linux.2xlarge_46154839619.zip 2025-07-17T09:26:42.1898202Z Finished upload of logs-test-dynamo_wrapped-2-3-linux.2xlarge_46154839619.zip 2025-07-17T09:26:42.2086504Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-07-17T09:26:42.2086855Z with: 2025-07-17T09:26:42.2087072Z s3-bucket: gha-artifacts 2025-07-17T09:26:42.2087407Z s3-prefix: pytorch/pytorch/16337959907/1/artifact 2025-07-17T09:26:42.2087779Z retention-days: 14 2025-07-17T09:26:42.2088038Z if-no-files-found: ignore 2025-07-17T09:26:42.2088299Z path: debug-*.zip 2025-07-17T09:26:42.2088538Z name: artifact 2025-07-17T09:26:42.2088773Z region: us-east-1 2025-07-17T09:26:42.2088984Z env: 2025-07-17T09:26:42.2089197Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:42.2089669Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:42.2090167Z DEVICE_NAME: 2025-07-17T09:26:42.2090406Z DEVICE_TYPE: 2025-07-17T09:26:42.2090634Z ##[endgroup] 2025-07-17T09:26:42.5273697Z No files were found with the provided path: debug-*.zip. No artifacts will be uploaded. 2025-07-17T09:26:42.5478293Z ##[group]Run # shellcheck disable=SC2156 2025-07-17T09:26:42.5478694Z # shellcheck disable=SC2156 2025-07-17T09:26:42.5479280Z find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \; 2025-07-17T09:26:42.5485940Z shell: /usr/bin/bash -e {0} 2025-07-17T09:26:42.5486243Z env: 2025-07-17T09:26:42.5486450Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:42.5486926Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:42.5487440Z DEVICE_NAME: 2025-07-17T09:26:42.5487671Z DEVICE_TYPE: 2025-07-17T09:26:42.5487884Z ##[endgroup] 2025-07-17T09:26:42.8628209Z Prepare all required actions 2025-07-17T09:26:42.8628636Z Getting action download info 2025-07-17T09:26:43.0183271Z ##[group]Run ./.github/actions/upload-utilization-stats 2025-07-17T09:26:43.0183667Z with: 2025-07-17T09:26:43.0183875Z job_id: 46154839619 2025-07-17T09:26:43.0184290Z job_name: linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T09:26:43.0184774Z workflow_name: pull 2025-07-17T09:26:43.0185025Z workflow_run_id: 16337959907 2025-07-17T09:26:43.0185304Z workflow_attempt: 1 2025-07-17T09:26:43.0185543Z env: 2025-07-17T09:26:43.0185745Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:43.0186220Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:43.0186728Z DEVICE_NAME: 2025-07-17T09:26:43.0186943Z DEVICE_TYPE: 2025-07-17T09:26:43.0187166Z ##[endgroup] 2025-07-17T09:26:43.0212858Z ##[group]Run echo "workflow_id: 16337959907" 2025-07-17T09:26:43.0213315Z echo "workflow_id: 16337959907" 2025-07-17T09:26:43.0213655Z echo "workflow_attempt: 1" 2025-07-17T09:26:43.0213966Z echo "workflow_Name: pull" 2025-07-17T09:26:43.0214369Z echo "job_id: 46154839619" 2025-07-17T09:26:43.0214897Z echo "job_name: linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge)" 2025-07-17T09:26:43.0215437Z echo "artifact_prefix: " 2025-07-17T09:26:43.0215751Z python3 --version 2025-07-17T09:26:43.0221288Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:43.0221662Z env: 2025-07-17T09:26:43.0221880Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:43.0222436Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:43.0222947Z DEVICE_NAME: 2025-07-17T09:26:43.0223164Z DEVICE_TYPE: 2025-07-17T09:26:43.0223396Z ##[endgroup] 2025-07-17T09:26:43.0247439Z workflow_id: 16337959907 2025-07-17T09:26:43.0247967Z workflow_attempt: 1 2025-07-17T09:26:43.0248363Z workflow_Name: pull 2025-07-17T09:26:43.0248586Z job_id: 46154839619 2025-07-17T09:26:43.0248997Z job_name: linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge) 2025-07-17T09:26:43.0249477Z artifact_prefix: 2025-07-17T09:26:43.0260299Z Python 3.9.23 2025-07-17T09:26:43.0328858Z ##[group]Run nick-fields/retry@v3.0.0 2025-07-17T09:26:43.0329379Z with: 2025-07-17T09:26:43.0329731Z shell: bash 2025-07-17T09:26:43.0330115Z timeout_minutes: 5 2025-07-17T09:26:43.0330529Z max_attempts: 5 2025-07-17T09:26:43.0330983Z retry_wait_seconds: 30 2025-07-17T09:26:43.0332011Z command: set -eu python3 -m pip install python-dateutil==2.8.2 boto3==1.35.42 pandas==2.1.3 dataclasses_json==0.6.7 2025-07-17T09:26:43.0333166Z polling_interval_seconds: 1 2025-07-17T09:26:43.0333679Z warning_on_retry: true 2025-07-17T09:26:43.0334153Z continue_on_error: false 2025-07-17T09:26:43.0334611Z env: 2025-07-17T09:26:43.0334956Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:43.0335811Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:43.0336753Z DEVICE_NAME: 2025-07-17T09:26:43.0337132Z DEVICE_TYPE: 2025-07-17T09:26:43.0337524Z ##[endgroup] 2025-07-17T09:26:43.3983609Z Defaulting to user installation because normal site-packages is not writeable 2025-07-17T09:26:43.4740698Z Collecting python-dateutil==2.8.2 2025-07-17T09:26:43.4903253Z Downloading python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB) 2025-07-17T09:26:44.4592647Z Collecting boto3==1.35.42 2025-07-17T09:26:44.4630625Z Downloading boto3-1.35.42-py3-none-any.whl (139 kB) 2025-07-17T09:26:44.9736596Z Collecting pandas==2.1.3 2025-07-17T09:26:44.9775124Z Downloading pandas-2.1.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.3 MB) 2025-07-17T09:26:45.1212665Z Requirement already satisfied: dataclasses_json==0.6.7 in /home/ec2-user/.local/lib/python3.9/site-packages (0.6.7) 2025-07-17T09:26:45.1236705Z Requirement already satisfied: six>=1.5 in /usr/lib/python3.9/site-packages (from python-dateutil==2.8.2) (1.15.0) 2025-07-17T09:26:45.1283215Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /usr/lib/python3.9/site-packages (from boto3==1.35.42) (0.10.0) 2025-07-17T09:26:45.1289646Z Requirement already satisfied: botocore<1.36.0,>=1.35.42 in /home/ec2-user/.local/lib/python3.9/site-packages (from boto3==1.35.42) (1.35.99) 2025-07-17T09:26:45.1293796Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from boto3==1.35.42) (0.10.4) 2025-07-17T09:26:45.2207866Z Collecting tzdata>=2022.1 2025-07-17T09:26:45.2242831Z Downloading tzdata-2025.2-py2.py3-none-any.whl (347 kB) 2025-07-17T09:26:46.0728802Z Collecting numpy<2,>=1.22.4 2025-07-17T09:26:46.0766397Z Downloading numpy-1.26.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB) 2025-07-17T09:26:46.2713564Z Requirement already satisfied: pytz>=2020.1 in /usr/lib/python3.9/site-packages (from pandas==2.1.3) (2022.7.1) 2025-07-17T09:26:46.2746525Z Requirement already satisfied: typing-inspect<1,>=0.4.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from dataclasses_json==0.6.7) (0.9.0) 2025-07-17T09:26:46.2751038Z Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from dataclasses_json==0.6.7) (3.26.1) 2025-07-17T09:26:46.2808539Z Requirement already satisfied: urllib3<1.27,>=1.25.4 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.42->boto3==1.35.42) (1.25.10) 2025-07-17T09:26:46.2938554Z Requirement already satisfied: packaging>=17.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (25.0) 2025-07-17T09:26:46.3042579Z Requirement already satisfied: typing-extensions>=3.7.4 in /home/ec2-user/.local/lib/python3.9/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (4.14.1) 2025-07-17T09:26:46.3046916Z Requirement already satisfied: mypy-extensions>=0.3.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (1.1.0) 2025-07-17T09:26:46.4690766Z Installing collected packages: python-dateutil, tzdata, numpy, pandas, boto3 2025-07-17T09:26:51.4492073Z Attempting uninstall: boto3 2025-07-17T09:26:51.4492714Z Found existing installation: boto3 1.35.33 2025-07-17T09:26:51.4591990Z Uninstalling boto3-1.35.33: 2025-07-17T09:26:51.4605518Z Successfully uninstalled boto3-1.35.33 2025-07-17T09:26:51.5147171Z Successfully installed boto3-1.35.42 numpy-1.26.4 pandas-2.1.3 python-dateutil-2.8.2 tzdata-2025.2 2025-07-17T09:26:52.1280039Z Command completed after 1 attempt(s). 2025-07-17T09:26:52.1335209Z ##[group]Run python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-07-17T09:26:52.1335941Z python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-07-17T09:26:52.1336460Z  --workflow-run-id "16337959907" \ 2025-07-17T09:26:52.1336836Z  --workflow-name "pull" \ 2025-07-17T09:26:52.1337179Z  --workflow-run-attempt "1" \ 2025-07-17T09:26:52.1337497Z  --job-id "46154839619" \ 2025-07-17T09:26:52.1338020Z  --job-name "linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge)" \ 2025-07-17T09:26:52.1338561Z  --local-path "" \ 2025-07-17T09:26:52.1338864Z  --artifact-prefix "" 2025-07-17T09:26:52.1345099Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:52.1345491Z env: 2025-07-17T09:26:52.1345718Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:52.1346181Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:52.1346705Z DEVICE_NAME: 2025-07-17T09:26:52.1346940Z DEVICE_TYPE: 2025-07-17T09:26:52.1347158Z ##[endgroup] 2025-07-17T09:26:54.1407828Z repo: pytorch/pytorch 2025-07-17T09:26:54.1408522Z Search for test log in s3 bucket: ossci-utilization 2025-07-17T09:26:54.1410028Z Downloading logs-test-dynamo_wrapped-2-3-linux.2xlarge_46154839619.zip 2025-07-17T09:26:54.1411459Z extracting usage_log.txt from zip file logs-test-dynamo_wrapped-2-3-linux.2xlarge_46154839619.zip 2025-07-17T09:26:54.1412609Z Converted Log Model: UtilizationMetadata: 2025-07-17T09:26:54.1415398Z UtilizationMetadata(level='metadata', workflow_id='16337959907', job_id='46154839619', workflow_name='pull', job_name='linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge)', usage_collect_interval=1.0, data_model_version=1.0, start_at=1752735902, gpu_count=0, cpu_count=8, gpu_type=None, error=None) 2025-07-17T09:26:54.1418281Z [Db Segments] detected pytest cmd: 11, generated segments: 11 2025-07-17T09:26:54.1419111Z [db model] Peek db timeseries 2025-07-17T09:26:54.1419657Z :{ 2025-07-17T09:26:54.1420057Z "created_at": 1752744413, 2025-07-17T09:26:54.1420606Z "type": "utilization", 2025-07-17T09:26:54.1421117Z "tags": [ 2025-07-17T09:26:54.1421522Z "record" 2025-07-17T09:26:54.1421957Z ], 2025-07-17T09:26:54.1422393Z "time_stamp": 1752735902, 2025-07-17T09:26:54.1422938Z "repo": "pytorch/pytorch", 2025-07-17T09:26:54.1423507Z "workflow_id": 16337959907, 2025-07-17T09:26:54.1424313Z "run_attempt": 1, 2025-07-17T09:26:54.1424804Z "job_id": 46154839619, 2025-07-17T09:26:54.1425316Z "workflow_name": "pull", 2025-07-17T09:26:54.1426196Z "job_name": "linux-jammy-py3.13-clang12 / test (dynamo_wrapped, 2, 3, linux.2xlarge)", 2025-07-17T09:26:54.1427159Z "json_data": "{}" 2025-07-17T09:26:54.1427610Z } 2025-07-17T09:26:54.1428598Z Writing 1 documents to S3 ossci-utilization/util_metadata/v_1.0/pytorch/pytorch/16337959907/1/46154839619/metadata 2025-07-17T09:26:54.1430647Z Done! Finish writing document to S3 ossci-utilization/util_metadata/v_1.0/pytorch/pytorch/16337959907/1/46154839619/metadata 2025-07-17T09:26:54.1432604Z Writing 1686 documents to S3 ossci-utilization/util_timeseries/v_1.0/pytorch/pytorch/16337959907/1/46154839619/time_series 2025-07-17T09:26:54.1434645Z Done! Finish writing document to S3 ossci-utilization/util_timeseries/v_1.0/pytorch/pytorch/16337959907/1/46154839619/time_series 2025-07-17T09:26:54.2475720Z ##[group]Run pytorch/test-infra/.github/actions/teardown-linux@main 2025-07-17T09:26:54.2476181Z with: 2025-07-17T09:26:54.2476387Z env: 2025-07-17T09:26:54.2476594Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:54.2477063Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:54.2477572Z DEVICE_NAME: 2025-07-17T09:26:54.2477790Z DEVICE_TYPE: 2025-07-17T09:26:54.2478013Z ##[endgroup] 2025-07-17T09:26:54.2497161Z ##[group]Run set -eou pipefail 2025-07-17T09:26:54.2497519Z set -eou pipefail 2025-07-17T09:26:54.2497788Z  2025-07-17T09:26:54.2498163Z echo "Holding runner for 2 hours until all ssh sessions have logged out" 2025-07-17T09:26:54.2498680Z for _ in $(seq 1440); do 2025-07-17T09:26:54.2499021Z  # Break if no ssh session exists anymore 2025-07-17T09:26:54.2499382Z  if [ "$(who)" = "" ]; then 2025-07-17T09:26:54.2499670Z  break 2025-07-17T09:26:54.2499957Z  fi 2025-07-17T09:26:54.2500179Z  echo "." 2025-07-17T09:26:54.2500424Z  sleep 5 2025-07-17T09:26:54.2500663Z done 2025-07-17T09:26:54.2506222Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:54.2506612Z env: 2025-07-17T09:26:54.2506837Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:54.2507305Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:54.2507803Z DEVICE_NAME: 2025-07-17T09:26:54.2508039Z DEVICE_TYPE: 2025-07-17T09:26:54.2508264Z ##[endgroup] 2025-07-17T09:26:54.2532077Z Holding runner for 2 hours until all ssh sessions have logged out 2025-07-17T09:26:54.2618746Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty 2025-07-17T09:26:54.2619424Z # ignore expansion of "docker ps -q" since it could be empty 2025-07-17T09:26:54.2619869Z # shellcheck disable=SC2046 2025-07-17T09:26:54.2620222Z docker stop $(docker ps -q) || true 2025-07-17T09:26:54.2620568Z # Prune all of the docker images 2025-07-17T09:26:54.2620905Z docker system prune -af 2025-07-17T09:26:54.2626227Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:26:54.2626598Z env: 2025-07-17T09:26:54.2626825Z GIT_DEFAULT_BRANCH: main 2025-07-17T09:26:54.2627294Z DOCKER_CONTAINER_ID: 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:26:54.2627791Z DEVICE_NAME: 2025-07-17T09:26:54.2628018Z DEVICE_TYPE: 2025-07-17T09:26:54.2628256Z ##[endgroup] 2025-07-17T09:27:05.4398547Z 987bbea70184 2025-07-17T09:27:06.1242271Z Deleted Containers: 2025-07-17T09:27:06.1242790Z 987bbea701846bc035c44d64b910615c22f73cf5b3dc2f371f42bf6c5bfd22b6 2025-07-17T09:27:06.1243156Z 2025-07-17T09:27:12.8784920Z Deleted Images: 2025-07-17T09:27:12.8786042Z untagged: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-01345e7669bb7198df9fce7a02a4a12ce8c84f2d 2025-07-17T09:27:12.8787548Z untagged: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image@sha256:298ca350eaba018a1adf58a70fad4c1b682d6f0738c0f0b4a6d27f040d02eb09 2025-07-17T09:27:12.8788504Z deleted: sha256:fc552ac054088d2469fbdea029aa8fa6904bc0b5b71dbfece3084d62acbe009f 2025-07-17T09:27:12.8789184Z deleted: sha256:f1b6db397da3ffabbf63e8e10ed59357cbf4f10b0420ec5c5bef6fd2b0321e9e 2025-07-17T09:27:12.8789873Z deleted: sha256:a1105bf7addbd31697b4c26a97b7a76fbca5e8b2af15ac3b1e9210390ce14707 2025-07-17T09:27:12.8790545Z deleted: sha256:005885ade24802c8af561d71bfb2485fbef1c6f758622d8a4b7e54ecefa76d30 2025-07-17T09:27:12.8791270Z deleted: sha256:79f532eee2efc37200f328a31c15ef8f71954d2306b8e67706b72b4bfee3bd04 2025-07-17T09:27:12.8791940Z deleted: sha256:46cda1d680b2a246ae026ca79d5b7fe81fb69e553101f08f0b3b5fda3d72f264 2025-07-17T09:27:12.8792595Z deleted: sha256:648b73987a4975b4d2481b7585459ba7f364e888f5beb79f245448a83b772111 2025-07-17T09:27:12.8793388Z deleted: 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'/home/ec2-user/actions-runner/_work/_temp/98ba2ec7-94bd-4726-8b5a-417849e5ece7/.gitconfig' 2025-07-17T09:27:13.0465627Z Temporarily overriding HOME='/home/ec2-user/actions-runner/_work/_temp/98ba2ec7-94bd-4726-8b5a-417849e5ece7' before making global git config changes 2025-07-17T09:27:13.0466634Z Adding repository directory to the temporary git global config as a safe directory 2025-07-17T09:27:13.0470445Z [command]/usr/bin/git config --global --add safe.directory /home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-07-17T09:27:13.0518759Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-07-17T09:27:13.0549248Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'core\.sshCommand' && git config --local --unset-all 'core.sshCommand' || :" 2025-07-17T09:27:13.0960772Z Entering 'android/libs/fbjni' 2025-07-17T09:27:13.1025069Z Entering 'third_party/FP16' 2025-07-17T09:27:13.1089579Z Entering 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2025-07-17T09:27:13.3844363Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-07-17T09:27:13.3899112Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-07-17T09:27:13.3955374Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-07-17T09:27:13.4017173Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-07-17T09:27:13.4071428Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-07-17T09:27:13.4129118Z Entering 'third_party/kleidiai' 2025-07-17T09:27:13.4185872Z Entering 'third_party/mimalloc' 2025-07-17T09:27:13.4241655Z Entering 'third_party/nlohmann' 2025-07-17T09:27:13.4300504Z Entering 'third_party/onnx' 2025-07-17T09:27:13.4409754Z Entering 'third_party/onnx/third_party/pybind11' 2025-07-17T09:27:13.4479838Z Entering 'third_party/opentelemetry-cpp' 2025-07-17T09:27:13.4538202Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-07-17T09:27:13.4593170Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-07-17T09:27:13.4646589Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-07-17T09:27:13.4699774Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-07-17T09:27:13.4754995Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-07-17T09:27:13.4810390Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-07-17T09:27:13.4863324Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-07-17T09:27:13.4916663Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-07-17T09:27:13.4974559Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-07-17T09:27:13.5031252Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-07-17T09:27:13.5105858Z Entering 'third_party/pocketfft' 2025-07-17T09:27:13.5163175Z Entering 'third_party/protobuf' 2025-07-17T09:27:13.5269145Z Entering 'third_party/protobuf/third_party/benchmark' 2025-07-17T09:27:13.5329736Z Entering 'third_party/protobuf/third_party/googletest' 2025-07-17T09:27:13.5384803Z Entering 'third_party/psimd' 2025-07-17T09:27:13.5447028Z Entering 'third_party/pthreadpool' 2025-07-17T09:27:13.5511673Z Entering 'third_party/pybind11' 2025-07-17T09:27:13.5566543Z Entering 'third_party/python-peachpy' 2025-07-17T09:27:13.5628268Z Entering 'third_party/sleef' 2025-07-17T09:27:13.5684107Z Entering 'third_party/tensorpipe' 2025-07-17T09:27:13.5762142Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-07-17T09:27:13.5834023Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-07-17T09:27:13.5909933Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-07-17T09:27:13.5990633Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-07-17T09:27:13.6073059Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-07-17T09:27:13.6160280Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-07-17T09:27:13.6181782Z http.https://github.com/.extraheader 2025-07-17T09:27:13.6192746Z [command]/usr/bin/git config --local --unset-all http.https://github.com/.extraheader 2025-07-17T09:27:13.6223812Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'http\.https\:\/\/github\.com\/\.extraheader' && git config --local --unset-all 'http.https://github.com/.extraheader' || :" 2025-07-17T09:27:13.6520783Z Entering 'android/libs/fbjni' 2025-07-17T09:27:13.6558303Z http.https://github.com/.extraheader 2025-07-17T09:27:13.6592424Z Entering 'third_party/FP16' 2025-07-17T09:27:13.6635898Z http.https://github.com/.extraheader 2025-07-17T09:27:13.6672810Z Entering 'third_party/FXdiv' 2025-07-17T09:27:13.6710356Z http.https://github.com/.extraheader 2025-07-17T09:27:13.6744486Z Entering 'third_party/NNPACK' 2025-07-17T09:27:13.6782405Z http.https://github.com/.extraheader 2025-07-17T09:27:13.6816608Z Entering 'third_party/NVTX' 2025-07-17T09:27:13.6854292Z http.https://github.com/.extraheader 2025-07-17T09:27:13.6888202Z Entering 'third_party/VulkanMemoryAllocator' 2025-07-17T09:27:13.6928239Z http.https://github.com/.extraheader 2025-07-17T09:27:13.6961857Z Entering 'third_party/XNNPACK' 2025-07-17T09:27:13.6999899Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7050093Z Entering 'third_party/aiter' 2025-07-17T09:27:13.7087139Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7122549Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-07-17T09:27:13.7158909Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7205912Z Entering 'third_party/benchmark' 2025-07-17T09:27:13.7242740Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7276727Z Entering 'third_party/composable_kernel' 2025-07-17T09:27:13.7313425Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7354240Z Entering 'third_party/cpp-httplib' 2025-07-17T09:27:13.7391367Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7424676Z Entering 'third_party/cpuinfo' 2025-07-17T09:27:13.7465678Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7499839Z Entering 'third_party/cudnn_frontend' 2025-07-17T09:27:13.7537515Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7571493Z Entering 'third_party/cutlass' 2025-07-17T09:27:13.7608800Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7652440Z Entering 'third_party/fbgemm' 2025-07-17T09:27:13.7690516Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7727651Z Entering 'third_party/fbgemm/external/asmjit' 2025-07-17T09:27:13.7764305Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7798797Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-07-17T09:27:13.7835375Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7877641Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-07-17T09:27:13.7913964Z http.https://github.com/.extraheader 2025-07-17T09:27:13.7947455Z Entering 'third_party/fbgemm/external/cutlass' 2025-07-17T09:27:13.7985176Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8027017Z Entering 'third_party/fbgemm/external/googletest' 2025-07-17T09:27:13.8062868Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8096242Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-07-17T09:27:13.8139063Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8172942Z Entering 'third_party/fbgemm/external/json' 2025-07-17T09:27:13.8209368Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8247085Z Entering 'third_party/flash-attention' 2025-07-17T09:27:13.8286096Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8320980Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-07-17T09:27:13.8357454Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8397483Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-07-17T09:27:13.8433788Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8481093Z Entering 'third_party/flatbuffers' 2025-07-17T09:27:13.8517900Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8555325Z Entering 'third_party/fmt' 2025-07-17T09:27:13.8594307Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8627878Z Entering 'third_party/gemmlowp/gemmlowp' 2025-07-17T09:27:13.8664868Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8698837Z Entering 'third_party/gloo' 2025-07-17T09:27:13.8736388Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8769904Z Entering 'third_party/googletest' 2025-07-17T09:27:13.8806607Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8840108Z Entering 'third_party/ideep' 2025-07-17T09:27:13.8877764Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8910891Z Entering 'third_party/ideep/mkl-dnn' 2025-07-17T09:27:13.8947409Z http.https://github.com/.extraheader 2025-07-17T09:27:13.8992012Z Entering 'third_party/ittapi' 2025-07-17T09:27:13.9030106Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9063954Z Entering 'third_party/kineto' 2025-07-17T09:27:13.9101287Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9135085Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-07-17T09:27:13.9171509Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9205485Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-07-17T09:27:13.9242654Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9280910Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-07-17T09:27:13.9319000Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9352893Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-07-17T09:27:13.9390156Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9425410Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-07-17T09:27:13.9461686Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9495646Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-07-17T09:27:13.9532355Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9568063Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-07-17T09:27:13.9606498Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9640388Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-07-17T09:27:13.9678803Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9713668Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-07-17T09:27:13.9751082Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9787094Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-07-17T09:27:13.9823561Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9859678Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-07-17T09:27:13.9897046Z http.https://github.com/.extraheader 2025-07-17T09:27:13.9932058Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-07-17T09:27:13.9968102Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0004189Z Entering 'third_party/kleidiai' 2025-07-17T09:27:14.0042278Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0078297Z Entering 'third_party/mimalloc' 2025-07-17T09:27:14.0115589Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0149265Z Entering 'third_party/nlohmann' 2025-07-17T09:27:14.0188487Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0224140Z Entering 'third_party/onnx' 2025-07-17T09:27:14.0261203Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0314990Z Entering 'third_party/onnx/third_party/pybind11' 2025-07-17T09:27:14.0351813Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0387472Z Entering 'third_party/opentelemetry-cpp' 2025-07-17T09:27:14.0426401Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0461961Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-07-17T09:27:14.0500643Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0534541Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-07-17T09:27:14.0573052Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0607382Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-07-17T09:27:14.0643725Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0677463Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-07-17T09:27:14.0713122Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0747757Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-07-17T09:27:14.0786428Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0819730Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-07-17T09:27:14.0855819Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0890930Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-07-17T09:27:14.0927248Z http.https://github.com/.extraheader 2025-07-17T09:27:14.0959960Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-07-17T09:27:14.0997714Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1036026Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-07-17T09:27:14.1074728Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1110722Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-07-17T09:27:14.1147199Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1202583Z Entering 'third_party/pocketfft' 2025-07-17T09:27:14.1241143Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1276675Z Entering 'third_party/protobuf' 2025-07-17T09:27:14.1314128Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1352373Z Entering 'third_party/protobuf/third_party/benchmark' 2025-07-17T09:27:14.1389866Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1422675Z Entering 'third_party/protobuf/third_party/googletest' 2025-07-17T09:27:14.1459098Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1494589Z Entering 'third_party/psimd' 2025-07-17T09:27:14.1531908Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1571534Z Entering 'third_party/pthreadpool' 2025-07-17T09:27:14.1609935Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1644092Z Entering 'third_party/pybind11' 2025-07-17T09:27:14.1682083Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1716737Z Entering 'third_party/python-peachpy' 2025-07-17T09:27:14.1754827Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1791954Z Entering 'third_party/sleef' 2025-07-17T09:27:14.1831771Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1866234Z Entering 'third_party/tensorpipe' 2025-07-17T09:27:14.1905313Z http.https://github.com/.extraheader 2025-07-17T09:27:14.1939638Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-07-17T09:27:14.1977633Z http.https://github.com/.extraheader 2025-07-17T09:27:14.2011208Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-07-17T09:27:14.2047722Z http.https://github.com/.extraheader 2025-07-17T09:27:14.2082503Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-07-17T09:27:14.2120065Z http.https://github.com/.extraheader 2025-07-17T09:27:14.2155956Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-07-17T09:27:14.2193700Z http.https://github.com/.extraheader 2025-07-17T09:27:14.2226956Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-07-17T09:27:14.2264232Z http.https://github.com/.extraheader 2025-07-17T09:27:14.2392501Z A job completed hook has been configured by the self-hosted runner administrator 2025-07-17T09:27:14.2424767Z ##[group]Run '/home/ec2-user/runner-scripts/after_job.sh' 2025-07-17T09:27:14.2429899Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-07-17T09:27:14.2430301Z ##[endgroup] 2025-07-17T09:27:23.6015189Z Cleaning up orphan processes